# Propositions from Judicial Economy in the Age of AI

**Citation:** Yonathan A. Arbel, Judicial Economy in the Age of AI, 96 U. Colo. L. Rev. 549 (2025).

**Source:** [published journal PDF](https://works.battleoftheforms.com/papers/ssrn-4873649/paper.pdf)

**Review status:** 136 model-drafted, source-checked; 0 human-reviewed. Page references use the printed pagination and, separately, the 1-based PDF page number.

## 1. AI can sharply reduce the cost of generating legal materials for lawyers and nonlawyers

**Location:** Abstract, printed pp. 549 (PDF pp. 1)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 549, that AI can sharply reduce the cost of generating legal materials for lawyers and nonlawyers. The discussion places this proposition within Abstract and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because lower production costs could dismantle entrenched barriers that leave most legal problems without effective redress. It connects to access to justice, legal-service costs, generative AI, legal materials, unmet legal need, technology adoption.

**Evidence anchor:** Printed page 549 (PDF page 1) develops this proposition in Abstract.

**Boundary:** The claim is a thesis-level forecast; the article later acknowledges uncertainty about adoption, filing behavior, and institutional response.

**Connections:** access to justice; legal-service costs; generative AI; legal materials; unmet legal need; technology adoption

**Record:** `ssrn-4873649-p001` · `machine-drafted-source-checked`

## 2. greater access generated by AI can paradoxically undermine the delivery of justice

**Location:** Abstract, printed pp. 549 (PDF pp. 1)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 549, that greater access generated by AI can paradoxically undermine the delivery of justice. The discussion places this proposition within Abstract and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because opening the courthouse door increases demand on a system whose adjudicative resources remain scarce. It connects to access versus delivery, judicial economy, institutional capacity, litigation volume, resource scarcity, AI governance.

**Evidence anchor:** Printed page 549 (PDF page 1) develops this proposition in Abstract.

**Boundary:** The claim is a thesis-level forecast; the article later acknowledges uncertainty about adoption, filing behavior, and institutional response.

**Connections:** access versus delivery; judicial economy; institutional capacity; litigation volume; resource scarcity; AI governance

**Record:** `ssrn-4873649-p002` · `machine-drafted-source-checked`

## 3. AI affects the naming, blaming, and claiming stages that precede formal litigation

**Location:** Abstract, printed pp. 549 (PDF pp. 1)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 549, that AI affects the naming, blaming, and claiming stages that precede formal litigation. The discussion places this proposition within Abstract and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because its effects begin before drafting a complaint and therefore reach claims that conventional access measures may never observe. It connects to naming blaming claiming, legal consciousness, dispute transformation, upstream barriers, claim formation, access to justice.

**Evidence anchor:** Printed page 549 (PDF page 1) develops this proposition in Abstract.

**Boundary:** The claim is a thesis-level forecast; the article later acknowledges uncertainty about adoption, filing behavior, and institutional response.

**Connections:** naming blaming claiming; legal consciousness; dispute transformation; upstream barriers; claim formation; access to justice

**Record:** `ssrn-4873649-p003` · `machine-drafted-source-checked`

## 4. the legal system should respond to AI adoption through proactive integration rather than continual restriction of litigants

**Location:** Abstract, printed pp. 549 (PDF pp. 1)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 549, that the legal system should respond to AI adoption through proactive integration rather than continual restriction of litigants. The discussion places this proposition within Abstract and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because scaling judicial capacity can preserve new access gains without shrinking procedural or substantive rights. It connects to proactive integration, legal thermostats, procedural rights, substantive rights, court technology, judicial capacity.

**Evidence anchor:** Printed page 549 (PDF page 1) develops this proposition in Abstract.

**Boundary:** The claim is a thesis-level forecast; the article later acknowledges uncertainty about adoption, filing behavior, and institutional response.

**Connections:** proactive integration; legal thermostats; procedural rights; substantive rights; court technology; judicial capacity

**Record:** `ssrn-4873649-p004` · `machine-drafted-source-checked`

## 5. most legal disputes never become filed cases

**Location:** Introduction, printed pp. 550 (PDF pp. 2)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 550, that most legal disputes never become filed cases. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the visible docket represents only a fraction of the underlying demand for legal remedies. It connects to unfiled disputes, unmet legal need, case selection, civil justice, access barriers, litigation demand.

**Evidence anchor:** Printed page 550 (PDF page 2) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** unfiled disputes; unmet legal need; case selection; civil justice; access barriers; litigation demand

**Record:** `ssrn-4873649-p005` · `machine-drafted-source-checked`

## 6. estimates of roughly 120 million unresolved legal problems reveal a potential caseload far larger than current dockets

**Location:** Introduction, printed pp. 550 (PDF pp. 2)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 550, that estimates of roughly 120 million unresolved legal problems reveal a potential caseload far larger than current dockets. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because even a modest conversion of latent problems into claims could materially alter judicial economy. It connects to unresolved legal problems, latent demand, caseload forecasting, court capacity, access to justice, civil litigation.

**Evidence anchor:** Printed page 550 (PDF page 2) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** unresolved legal problems; latent demand; caseload forecasting; court capacity; access to justice; civil litigation

**Record:** `ssrn-4873649-p006` · `machine-drafted-source-checked`

## 7. low-income Americans face both frequent civil legal problems and extremely low rates of legal assistance

**Location:** Introduction, printed pp. 550 (PDF pp. 2)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 550, that low-income Americans face both frequent civil legal problems and extremely low rates of legal assistance. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because AI enters a system in which need is widespread but professional help is rationed. It connects to legal aid gap, low-income litigants, civil legal needs, rationing, distributional justice, AI assistance.

**Evidence anchor:** Printed page 550 (PDF page 2) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** legal aid gap; low-income litigants; civil legal needs; rationing; distributional justice; AI assistance

**Record:** `ssrn-4873649-p007` · `machine-drafted-source-checked`

## 8. many access-to-justice barriers can be translated into costs

**Location:** Introduction, printed pp. 551 (PDF pp. 3)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 551, that many access-to-justice barriers can be translated into costs. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because fees for lawyers and litigation make formal rights practically unusable for ordinary people and small businesses. It connects to legal costs, lawyer fees, practical rights, small claims, access barriers, legal markets.

**Evidence anchor:** Printed page 551 (PDF page 3) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** legal costs; lawyer fees; practical rights; small claims; access barriers; legal markets

**Record:** `ssrn-4873649-p008` · `machine-drafted-source-checked`

## 9. the way an injured person describes a wrong can reveal the absence of legal consciousness

**Location:** Introduction, printed pp. 551 (PDF pp. 3)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 551, that the way an injured person describes a wrong can reveal the absence of legal consciousness. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because calling wage theft being stiffed rather than a breach or rights violation shows that claim formation fails before court costs arise. It connects to legal consciousness, wage theft, framing, naming harms, claim formation, sociolegal barriers.

**Evidence anchor:** Printed page 551 (PDF page 3) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** legal consciousness; wage theft; framing; naming harms; claim formation; sociolegal barriers

**Record:** `ssrn-4873649-p009` · `machine-drafted-source-checked`

## 10. large increases in legal-aid funding have made only a limited dent in unmet need

**Location:** Introduction, printed pp. 551 (PDF pp. 3)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 551, that large increases in legal-aid funding have made only a limited dent in unmet need. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the scale of demand makes a lawyer-by-lawyer solution structurally inadequate on its own. It connects to legal aid, funding constraints, service capacity, unmet demand, lawyer scarcity, institutional scale.

**Evidence anchor:** Printed page 551 (PDF page 3) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** legal aid; funding constraints; service capacity; unmet demand; lawyer scarcity; institutional scale

**Record:** `ssrn-4873649-p010` · `machine-drafted-source-checked`

## 11. legal-aid organizations must turn away enormous numbers of eligible people because lawyers are scarce

**Location:** Introduction, printed pp. 552 (PDF pp. 4)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 552, that legal-aid organizations must turn away enormous numbers of eligible people because lawyers are scarce. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the existing delivery model cannot supply individualized professional service to everyone who needs it. It connects to legal aid rationing, lawyer-client ratios, service denial, resource scarcity, civil justice, scalability.

**Evidence anchor:** Printed page 552 (PDF page 4) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** legal aid rationing; lawyer-client ratios; service denial; resource scarcity; civil justice; scalability

**Record:** `ssrn-4873649-p011` · `machine-drafted-source-checked`

## 12. technology can reinforce inequality when repeat-player firms automate litigation while individuals remain comparatively analog

**Location:** Introduction, printed pp. 552 (PDF pp. 4)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 552, that technology can reinforce inequality when repeat-player firms automate litigation while individuals remain comparatively analog. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because unequal adoption can let organizational plaintiffs scale claims against defendants who lack comparable tools. It connects to technology asymmetry, repeat players, debt collection, automation, default judgments, distributional power.

**Evidence anchor:** Printed page 552 (PDF page 4) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** technology asymmetry; repeat players; debt collection; automation; default judgments; distributional power

**Record:** `ssrn-4873649-p012` · `machine-drafted-source-checked`

## 13. the claim that individuals use only analog legal tools is overstated but contains an important asymmetry

**Location:** Introduction, printed pp. 552 (PDF pp. 4)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 552, that the claim that individuals use only analog legal tools is overstated but contains an important asymmetry. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because ordinary people do use the internet and digital tools, yet sophisticated firms retain advantages in systematization and automation. It connects to legal technology, individual litigants, organizational capacity, digital tools, automation gap, nuanced diagnosis.

**Evidence anchor:** Printed page 552 (PDF page 4) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** legal technology; individual litigants; organizational capacity; digital tools; automation gap; nuanced diagnosis

**Record:** `ssrn-4873649-p013` · `machine-drafted-source-checked`

## 14. stories about lawyers filing hallucinated AI output obscure evidence of real adoption

**Location:** Introduction, printed pp. 553 (PDF pp. 5)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 553, that stories about lawyers filing hallucinated AI output obscure evidence of real adoption. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because spectacular failures attract attention while quietly demonstrating that legal professionals already find the tools useful enough to deploy. It connects to AI hallucinations, media narratives, legal practice, technology adoption, selection effects, professional behavior.

**Evidence anchor:** Printed page 553 (PDF page 5) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** AI hallucinations; media narratives; legal practice; technology adoption; selection effects; professional behavior

**Record:** `ssrn-4873649-p014` · `machine-drafted-source-checked`

## 15. small law firms are adopting generative AI despite not usually being early adopters

**Location:** Introduction, printed pp. 553 (PDF pp. 5)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 553, that small law firms are adopting generative AI despite not usually being early adopters. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because diffusion beyond elite firms suggests that low cost and accessibility can broaden the technology's litigation impact. It connects to small firms, diffusion, generative AI, legal innovation, adoption patterns, litigation technology.

**Evidence anchor:** Printed page 553 (PDF page 5) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** small firms; diffusion; generative AI; legal innovation; adoption patterns; litigation technology

**Record:** `ssrn-4873649-p015` · `machine-drafted-source-checked`

## 16. convenience can drive AI adoption even when users know the tools are imperfect

**Location:** Introduction, printed pp. 553 (PDF pp. 5)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 553, that convenience can drive AI adoption even when users know the tools are imperfect. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because practical uptake depends on comparative usefulness rather than flawless performance. It connects to convenience, imperfect technology, bounded reliability, user incentives, adoption behavior, legal services.

**Evidence anchor:** Printed page 553 (PDF page 5) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** convenience; imperfect technology; bounded reliability; user incentives; adoption behavior; legal services

**Record:** `ssrn-4873649-p016` · `machine-drafted-source-checked`

## 17. democratized litigation technology is likely to produce a litigation boom by sharply lowering material-production costs

**Location:** Introduction, printed pp. 554 (PDF pp. 6)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 554, that democratized litigation technology is likely to produce a litigation boom by sharply lowering material-production costs. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because reduced filing costs activate claims that current frictions leave dormant. It connects to litigation boom, democratization, production costs, latent claims, filing incentives, access to justice.

**Evidence anchor:** Printed page 554 (PDF page 6) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** litigation boom; democratization; production costs; latent claims; filing incentives; access to justice

**Record:** `ssrn-4873649-p017` · `machine-drafted-source-checked`

## 18. courts should begin integrating AI before increased caseloads force emergency responses

**Location:** Introduction, printed pp. 554 (PDF pp. 6)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 554, that courts should begin integrating AI before increased caseloads force emergency responses. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because early preparation permits testing and institutional learning instead of crisis-driven rights restrictions. It connects to proactive governance, court readiness, institutional learning, AI testing, caseload growth, rights preservation.

**Evidence anchor:** Printed page 554 (PDF page 6) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** proactive governance; court readiness; institutional learning; AI testing; caseload growth; rights preservation

**Record:** `ssrn-4873649-p018` · `machine-drafted-source-checked`

## 19. unreliable AI should be a catalyst for careful integration rather than a reason for institutional paralysis

**Location:** Introduction, printed pp. 554 (PDF pp. 6)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 554, that unreliable AI should be a catalyst for careful integration rather than a reason for institutional paralysis. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because known limitations are easier to study and manage before systems are deployed under acute workload pressure. It connects to responsible innovation, AI reliability, testing, institutional design, risk management, judicial administration.

**Evidence anchor:** Printed page 554 (PDF page 6) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** responsible innovation; AI reliability; testing; institutional design; risk management; judicial administration

**Record:** `ssrn-4873649-p019` · `machine-drafted-source-checked`

## 20. the naming-blaming-claiming model identifies invisible filters that keep injuries from becoming legal claims

**Location:** Introduction, printed pp. 555 (PDF pp. 7)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 555, that the naming-blaming-claiming model identifies invisible filters that keep injuries from becoming legal claims. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because access reform must address conceptual and social barriers that arise before a person seeks counsel or court access. It connects to dispute transformation, upstream filters, legal consciousness, sociolegal theory, claim recognition, access reform.

**Evidence anchor:** Printed page 555 (PDF page 7) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** dispute transformation; upstream filters; legal consciousness; sociolegal theory; claim recognition; access reform

**Record:** `ssrn-4873649-p020` · `machine-drafted-source-checked`

## 21. AI can shepherd individuals through naming, blaming, and claiming by translating misfortune into legally cognizable terms

**Location:** Introduction, printed pp. 555 (PDF pp. 7)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 555, that AI can shepherd individuals through naming, blaming, and claiming by translating misfortune into legally cognizable terms. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because cheap interactive guidance can activate pent-up claims that cost statistics and filed-case data omit. It connects to interactive guidance, legal framing, latent claims, generative AI, claim articulation, access to justice.

**Evidence anchor:** Printed page 555 (PDF page 7) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** interactive guidance; legal framing; latent claims; generative AI; claim articulation; access to justice

**Record:** `ssrn-4873649-p021` · `machine-drafted-source-checked`

## 22. removing access filters will enable both meritorious and abusive litigation

**Location:** Introduction, printed pp. 555 (PDF pp. 7)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 555, that removing access filters will enable both meritorious and abusive litigation. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because some existing frictions exclude socially valuable claims while also deterring harassment and fabricated allegations. It connects to governance friction, meritorious claims, abusive litigation, filtering, tradeoffs, judicial economy.

**Evidence anchor:** Printed page 555 (PDF page 7) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** governance friction; meritorious claims; abusive litigation; filtering; tradeoffs; judicial economy

**Record:** `ssrn-4873649-p022` · `machine-drafted-source-checked`

## 23. procedural and substantive doctrines can operate as legal thermostats that stabilize caseload

**Location:** Introduction, printed pp. 556 (PDF pp. 8)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 556, that procedural and substantive doctrines can operate as legal thermostats that stabilize caseload. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because rules framed as rights doctrine may also be adjusted in response to pressure on finite judicial resources. It connects to legal thermostats, control theory, caseload management, procedure, substantive law, institutional adaptation.

**Evidence anchor:** Printed page 556 (PDF page 8) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** legal thermostats; control theory; caseload management; procedure; substantive law; institutional adaptation

**Record:** `ssrn-4873649-p023` · `machine-drafted-source-checked`

## 24. thermostat adjustments can erase access gains by narrowing the rights available after litigants reach court

**Location:** Introduction, printed pp. 556 (PDF pp. 8)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 556, that thermostat adjustments can erase access gains by narrowing the rights available after litigants reach court. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because formal entry into the system is not meaningful if proof burdens and remedies become increasingly restrictive. It connects to rights contraction, access versus delivery, proof burdens, remedies, procedural justice, system capacity.

**Evidence anchor:** Printed page 556 (PDF page 8) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** rights contraction; access versus delivery; proof burdens; remedies; procedural justice; system capacity

**Record:** `ssrn-4873649-p024` · `machine-drafted-source-checked`

## 25. integrating AI into case management and chambers can scale processing without sacrificing individual rights

**Location:** Introduction, printed pp. 556 (PDF pp. 8)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 556, that integrating AI into case management and chambers can scale processing without sacrificing individual rights. The discussion places this proposition within Introduction and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because court-side productivity improvements target the supply of adjudication rather than suppressing demand. It connects to court AI, case management, chambers, productivity, rights preservation, judicial capacity.

**Evidence anchor:** Printed page 556 (PDF page 8) develops this proposition in Introduction.

**Boundary:** The cited figures and examples establish scale and mechanisms, but the article cautions that civil-justice data are incomplete and future effects remain uncertain.

**Connections:** court AI; case management; chambers; productivity; rights preservation; judicial capacity

**Record:** `ssrn-4873649-p025` · `machine-drafted-source-checked`

## 26. debate about legal AI is distorted by treating it as either omnipotent or useless

**Location:** I.A. AI Legal Efficacy, printed pp. 557 (PDF pp. 9)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 557, that debate about legal AI is distorted by treating it as either omnipotent or useless. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because a task-specific middle position is necessary to evaluate capabilities, failures, and realistic substitutes. It connects to AI evaluation, capability spectrum, technological realism, task specificity, legal AI, false dichotomy.

**Evidence anchor:** Printed page 557 (PDF page 9) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** AI evaluation; capability spectrum; technological realism; task specificity; legal AI; false dichotomy

**Record:** `ssrn-4873649-p026` · `machine-drafted-source-checked`

## 27. current capability evidence establishes tentative floors while observed limits establish only tentative ceilings

**Location:** I.A. AI Legal Efficacy, printed pp. 557 (PDF pp. 9)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 557, that current capability evidence establishes tentative floors while observed limits establish only tentative ceilings. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because rapid development makes both positive and negative performance claims time-sensitive. It connects to capability floors, limitation ceilings, technical change, forecast uncertainty, model evaluation, legal technology.

**Evidence anchor:** Printed page 557 (PDF page 9) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** capability floors; limitation ceilings; technical change; forecast uncertainty; model evaluation; legal technology

**Record:** `ssrn-4873649-p027` · `machine-drafted-source-checked`

## 28. adequacy rather than perfection is the relevant threshold for estimating litigation effects

**Location:** I.A. AI Legal Efficacy, printed pp. 557 (PDF pp. 9)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 557, that adequacy rather than perfection is the relevant threshold for estimating litigation effects. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because tools can change behavior and filing volume even when they do not match elite professional quality. It connects to adequate performance, adoption effects, comparative quality, litigation incentives, technology diffusion, access to justice.

**Evidence anchor:** Printed page 557 (PDF page 9) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** adequate performance; adoption effects; comparative quality; litigation incentives; technology diffusion; access to justice

**Record:** `ssrn-4873649-p028` · `machine-drafted-source-checked`

## 29. GPT-4 performed contract issue identification at roughly the level of junior lawyers in a cited study

**Location:** I.A. AI Legal Efficacy, printed pp. 558 (PDF pp. 10)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 558, that GPT-4 performed contract issue identification at roughly the level of junior lawyers in a cited study. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because near-professional performance on a bounded task makes substitution and augmentation plausible. It connects to contract review, junior lawyers, issue spotting, benchmarking, legal AI, professional substitution.

**Evidence anchor:** Printed page 558 (PDF page 10) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** contract review; junior lawyers; issue spotting; benchmarking; legal AI; professional substitution

**Record:** `ssrn-4873649-p029` · `machine-drafted-source-checked`

## 30. AI completed contract-review tasks in a small fraction of lawyer time and at a tiny operating cost

**Location:** I.A. AI Legal Efficacy, printed pp. 558 (PDF pp. 10)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 558, that AI completed contract-review tasks in a small fraction of lawyer time and at a tiny operating cost. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because large speed and cost differentials can transform the economics and volume of legal-material production. It connects to productivity, operating cost, contract analysis, automation, legal-service pricing, scale.

**Evidence anchor:** Printed page 558 (PDF page 10) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** productivity; operating cost; contract analysis; automation; legal-service pricing; scale

**Record:** `ssrn-4873649-p030` · `machine-drafted-source-checked`

## 31. the model's preference for precision over recall resembled a junior lawyer's failure pattern

**Location:** I.A. AI Legal Efficacy, printed pp. 558 (PDF pp. 10)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 558, that the model's preference for precision over recall resembled a junior lawyer's failure pattern. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because comparison of error structure is more informative than demanding error-free output from machines alone. It connects to precision and recall, error profiles, human benchmark, F-score, quality assurance, comparative evaluation.

**Evidence anchor:** Printed page 558 (PDF page 10) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** precision and recall; error profiles; human benchmark; F-score; quality assurance; comparative evaluation

**Record:** `ssrn-4873649-p031` · `machine-drafted-source-checked`

## 32. newer models correctly answered illustrative contract-review errors made by an earlier model

**Location:** I.A. AI Legal Efficacy, printed pp. 559 (PDF pp. 11)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 559, that newer models correctly answered illustrative contract-review errors made by an earlier model. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because some prominent failures may be transient artifacts rather than durable technological limits. It connects to model improvement, transient errors, contract review, technical progress, replication, capability ceilings.

**Evidence anchor:** Printed page 559 (PDF page 11) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** model improvement; transient errors; contract review; technical progress; replication; capability ceilings

**Record:** `ssrn-4873649-p032` · `machine-drafted-source-checked`

## 33. smart readers can greatly shorten and simplify consumer legal documents without losing essential information

**Location:** I.A. AI Legal Efficacy, printed pp. 559 (PDF pp. 11)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 559, that smart readers can greatly shorten and simplify consumer legal documents without losing essential information. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because comprehension tools can reduce reading time and literacy barriers as well as direct legal fees. It connects to smart readers, consumer contracts, readability, summarization, no-reading problem, accessibility.

**Evidence anchor:** Printed page 559 (PDF page 11) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** smart readers; consumer contracts; readability; summarization; no-reading problem; accessibility

**Record:** `ssrn-4873649-p033` · `machine-drafted-source-checked`

## 34. some smart-reader failures reflected context-window limits that later systems substantially mitigated

**Location:** I.A. AI Legal Efficacy, printed pp. 559 (PDF pp. 11)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 559, that some smart-reader failures reflected context-window limits that later systems substantially mitigated. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because technology-sensitive diagnosis prevents temporary engineering constraints from being mistaken for conceptual impossibility. It connects to context windows, document length, system improvement, smart readers, failure analysis, technical change.

**Evidence anchor:** Printed page 559 (PDF page 11) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** context windows; document length; system improvement; smart readers; failure analysis; technical change

**Record:** `ssrn-4873649-p034` · `machine-drafted-source-checked`

## 35. LLMs achieved substantial above-chance accuracy on complex tax-law questions

**Location:** I.A. AI Legal Efficacy, printed pp. 560 (PDF pp. 12)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 560, that LLMs achieved substantial above-chance accuracy on complex tax-law questions. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because bounded legal reasoning performance can be useful even when accuracy falls well short of perfection. It connects to tax law, legal reasoning, accuracy, retrieval augmentation, benchmarking, bounded competence.

**Evidence anchor:** Printed page 560 (PDF page 12) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** tax law; legal reasoning; accuracy; retrieval augmentation; benchmarking; bounded competence

**Record:** `ssrn-4873649-p035` · `machine-drafted-source-checked`

## 36. the realistic margin of substitution is often a low-cost lay service provider rather than a white-shoe lawyer

**Location:** I.A. AI Legal Efficacy, printed pp. 560 (PDF pp. 12)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 560, that the realistic margin of substitution is often a low-cost lay service provider rather than a white-shoe lawyer. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because distributional and market effects depend on what service users would otherwise obtain. It connects to margin of substitution, legal services market, lay preparers, professional hierarchy, access to advice, comparative baseline.

**Evidence anchor:** Printed page 560 (PDF page 12) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** margin of substitution; legal services market; lay preparers; professional hierarchy; access to advice; comparative baseline

**Record:** `ssrn-4873649-p036` · `machine-drafted-source-checked`

## 37. legal hallucinations are a serious but sometimes cheaply verifiable failure mode

**Location:** I.A. AI Legal Efficacy, printed pp. 560 (PDF pp. 12)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 560, that legal hallucinations are a serious but sometimes cheaply verifiable failure mode. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because source checking and technical mitigation can make some errors manageable without making them harmless. It connects to hallucinations, source verification, error mitigation, legal research, quality control, AI reliability.

**Evidence anchor:** Printed page 560 (PDF page 12) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** hallucinations; source verification; error mitigation; legal research; quality control; AI reliability

**Record:** `ssrn-4873649-p037` · `machine-drafted-source-checked`

## 38. bar-exam claims about GPT-4 depend materially on the human comparison group and test administration

**Location:** I.A. AI Legal Efficacy, printed pp. 561 (PDF pp. 13)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 561, that bar-exam claims about GPT-4 depend materially on the human comparison group and test administration. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because headline percentiles can overstate capability when repeat takers and seasonal cohorts are ignored. It connects to bar exam, benchmark design, comparison groups, percentiles, evaluation validity, legal competence.

**Evidence anchor:** Printed page 561 (PDF page 13) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** bar exam; benchmark design; comparison groups; percentiles; evaluation validity; legal competence

**Record:** `ssrn-4873649-p038` · `machine-drafted-source-checked`

## 39. corrected estimates place GPT-4 near the median of successful test takers overall but much lower on essays

**Location:** I.A. AI Legal Efficacy, printed pp. 561 (PDF pp. 13)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 561, that corrected estimates place GPT-4 near the median of successful test takers overall but much lower on essays. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because aggregate performance can conceal important task-level weaknesses relevant to actual lawyering. It connects to essay performance, aggregate scores, task decomposition, lawyering skills, human benchmarks, model limits.

**Evidence anchor:** Printed page 561 (PDF page 13) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** essay performance; aggregate scores; task decomposition; lawyering skills; human benchmarks; model limits

**Record:** `ssrn-4873649-p039` · `machine-drafted-source-checked`

## 40. bar and law-school tests imperfectly predict practice but remain relevant because they are legal gatekeepers

**Location:** I.A. AI Legal Efficacy, printed pp. 561 (PDF pp. 13)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 561, that bar and law-school tests imperfectly predict practice but remain relevant because they are legal gatekeepers. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the same institutions that license human lawyers cannot dismiss comparable machine performance as wholly irrelevant. It connects to professional licensing, bar examination, gatekeeping, ecological validity, legal education, AI competence.

**Evidence anchor:** Printed page 561 (PDF page 13) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** professional licensing; bar examination; gatekeeping; ecological validity; legal education; AI competence

**Record:** `ssrn-4873649-p040` · `machine-drafted-source-checked`

## 41. blind referees preferred an AI-drafted employment complaint letter to a trained lawyer's letter in a cited study

**Location:** I.A. AI Legal Efficacy, printed pp. 562 (PDF pp. 14)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 562, that blind referees preferred an AI-drafted employment complaint letter to a trained lawyer's letter in a cited study. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because real-world output evaluation can reveal usefulness that abstract benchmark scores miss. It connects to complaint drafting, blind evaluation, employment law, writing quality, real-world evidence, legal AI.

**Evidence anchor:** Printed page 562 (PDF page 14) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** complaint drafting; blind evaluation; employment law; writing quality; real-world evidence; legal AI

**Record:** `ssrn-4873649-p041` · `machine-drafted-source-checked`

## 42. legal-aid lawyers reported productivity gains from GPT-4 while remaining concerned about the technology

**Location:** I.A. AI Legal Efficacy, printed pp. 562 (PDF pp. 14)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 562, that legal-aid lawyers reported productivity gains from GPT-4 while remaining concerned about the technology. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because practitioner experience supports augmentation without eliminating the need for professional caution. It connects to legal aid, field study, productivity, professional judgment, AI concerns, augmentation.

**Evidence anchor:** Printed page 562 (PDF page 14) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** legal aid; field study; productivity; professional judgment; AI concerns; augmentation

**Record:** `ssrn-4873649-p042` · `machine-drafted-source-checked`

## 43. AI faults must be measured against realistic alternatives, including self-help and doing nothing

**Location:** I.A. AI Legal Efficacy, printed pp. 562 (PDF pp. 14)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 562, that AI faults must be measured against realistic alternatives, including self-help and doing nothing. The discussion places this proposition within I.A. AI Legal Efficacy and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because many underserved people are choosing between imperfect AI and no legal assistance, not between AI and elite counsel. It connects to realistic alternatives, doing nothing, self-help, access inequality, comparative evaluation, legal assistance.

**Evidence anchor:** Printed page 562 (PDF page 14) develops this proposition in I.A. AI Legal Efficacy.

**Boundary:** The capability evidence is time-sensitive, task-specific, and benchmark-dependent; it does not establish that current systems can replace expert lawyers across all legal work.

**Connections:** realistic alternatives; doing nothing; self-help; access inequality; comparative evaluation; legal assistance

**Record:** `ssrn-4873649-p043` · `machine-drafted-source-checked`

## 44. poor households are especially likely to take no action on legal problems

**Location:** I.B. AI Uptake, printed pp. 563 (PDF pp. 15)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 563, that poor households are especially likely to take no action on legal problems. The discussion places this proposition within I.B. AI Uptake and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the distributional value of middling AI is greater where the baseline is inaction. It connects to poverty, inaction, distributional effects, legal needs, baseline comparison, access to justice.

**Evidence anchor:** Printed page 563 (PDF page 15) develops this proposition in I.B. AI Uptake.

**Boundary:** The surveys are snapshots from a rapidly changing market and measure reported use or attitudes rather than long-run filing effects.

**Connections:** poverty; inaction; distributional effects; legal needs; baseline comparison; access to justice

**Record:** `ssrn-4873649-p044` · `machine-drafted-source-checked`

## 45. lawyers broadly believe AI can be applied to legal work even when fewer view its use as appropriate

**Location:** I.B. AI Uptake, printed pp. 563 (PDF pp. 15)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 563, that lawyers broadly believe AI can be applied to legal work even when fewer view its use as appropriate. The discussion places this proposition within I.B. AI Uptake and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because capability judgments and professional norms are diverging during early adoption. It connects to professional attitudes, appropriateness, capability, legal ethics, adoption barriers, generative AI.

**Evidence anchor:** Printed page 563 (PDF page 15) develops this proposition in I.B. AI Uptake.

**Boundary:** The surveys are snapshots from a rapidly changing market and measure reported use or attitudes rather than long-run filing effects.

**Connections:** professional attitudes; appropriateness; capability; legal ethics; adoption barriers; generative AI

**Record:** `ssrn-4873649-p045` · `machine-drafted-source-checked`

## 46. early surveys already showed meaningful AI use among lawyers and legal-aid practitioners

**Location:** I.B. AI Uptake, printed pp. 563 (PDF pp. 15)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 563, that early surveys already showed meaningful AI use among lawyers and legal-aid practitioners. The discussion places this proposition within I.B. AI Uptake and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because nontrivial uptake supplies a pathway from technical capability to actual changes in legal production. It connects to lawyer surveys, legal aid, technology uptake, practice change, diffusion, legal production.

**Evidence anchor:** Printed page 563 (PDF page 15) develops this proposition in I.B. AI Uptake.

**Boundary:** The surveys are snapshots from a rapidly changing market and measure reported use or attitudes rather than long-run filing effects.

**Connections:** lawyer surveys; legal aid; technology uptake; practice change; diffusion; legal production

**Record:** `ssrn-4873649-p046` · `machine-drafted-source-checked`

## 47. common legal AI uses include drafting, brainstorming, summarizing, and writing communications

**Location:** I.B. AI Uptake, printed pp. 564 (PDF pp. 16)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 564, that common legal AI uses include drafting, brainstorming, summarizing, and writing communications. The discussion places this proposition within I.B. AI Uptake and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because integration is occurring across routine workflow tasks rather than only in spectacular automated adjudication. It connects to workflow integration, drafting, brainstorming, summarization, legal communication, augmentation.

**Evidence anchor:** Printed page 564 (PDF page 16) develops this proposition in I.B. AI Uptake.

**Boundary:** The surveys are snapshots from a rapidly changing market and measure reported use or attitudes rather than long-run filing effects.

**Connections:** workflow integration; drafting; brainstorming; summarization; legal communication; augmentation

**Record:** `ssrn-4873649-p047` · `machine-drafted-source-checked`

## 48. AI use among knowledge workers accelerated dramatically in a short period

**Location:** I.B. AI Uptake, printed pp. 564 (PDF pp. 16)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 564, that AI use among knowledge workers accelerated dramatically in a short period. The discussion places this proposition within I.B. AI Uptake and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because law firms face strong diffusion pressure and are unlikely to remain persistent outliers. It connects to knowledge workers, rapid adoption, organizational diffusion, law firms, workplace AI, technology trajectory.

**Evidence anchor:** Printed page 564 (PDF page 16) develops this proposition in I.B. AI Uptake.

**Boundary:** The surveys are snapshots from a rapidly changing market and measure reported use or attitudes rather than long-run filing effects.

**Connections:** knowledge workers; rapid adoption; organizational diffusion; law firms; workplace AI; technology trajectory

**Record:** `ssrn-4873649-p048` · `machine-drafted-source-checked`

## 49. law-firm adoption supplies a model that courts could adapt for chambers and case-management workflows

**Location:** I.B. AI Uptake, printed pp. 564 (PDF pp. 16)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 564, that law-firm adoption supplies a model that courts could adapt for chambers and case-management workflows. The discussion places this proposition within I.B. AI Uptake and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because private-sector experimentation can reveal tasks, controls, and training practices useful to judicial institutions. It connects to institutional learning, law firms, courts, case management, workflow design, technology transfer.

**Evidence anchor:** Printed page 564 (PDF page 16) develops this proposition in I.B. AI Uptake.

**Boundary:** The surveys are snapshots from a rapidly changing market and measure reported use or attitudes rather than long-run filing effects.

**Connections:** institutional learning; law firms; courts; case management; workflow design; technology transfer

**Record:** `ssrn-4873649-p049` · `machine-drafted-source-checked`

## 50. access to justice is a contested umbrella that includes formal, substantive, representative, and psychological dimensions

**Location:** I.C. AI Impact on Access to Justice, printed pp. 565 (PDF pp. 17)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 565, that access to justice is a contested umbrella that includes formal, substantive, representative, and psychological dimensions. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because a narrow focus on court filing or lawyer supply misses important ways people are excluded. It connects to multidimensional access, formal justice, substantive justice, representation, psychological barriers, legal institutions.

**Evidence anchor:** Printed page 565 (PDF page 17) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** multidimensional access; formal justice; substantive justice; representation; psychological barriers; legal institutions

**Record:** `ssrn-4873649-p050` · `machine-drafted-source-checked`

## 51. access barriers are regressive and help the haves come out ahead

**Location:** I.C. AI Impact on Access to Justice, printed pp. 565 (PDF pp. 17)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 565, that access barriers are regressive and help the haves come out ahead. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because institutional friction distributes practical legal power rather than merely reducing administrative volume. It connects to Galanter, repeat players, distributional justice, legal inequality, access barriers, institutional power.

**Evidence anchor:** Printed page 565 (PDF page 17) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** Galanter; repeat players; distributional justice; legal inequality; access barriers; institutional power

**Record:** `ssrn-4873649-p051` · `machine-drafted-source-checked`

## 52. AI creates a holistic shock to access barriers that reaches costs, social framing, and psychology

**Location:** I.C. AI Impact on Access to Justice, printed pp. 565 (PDF pp. 17)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 565, that AI creates a holistic shock to access barriers that reaches costs, social framing, and psychology. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the technology can alter both the price of services and the processes through which people recognize and pursue rights. It connects to holistic disruption, cost barriers, social barriers, psychological barriers, legal consciousness, AI assistance.

**Evidence anchor:** Printed page 565 (PDF page 17) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** holistic disruption; cost barriers; social barriers; psychological barriers; legal consciousness; AI assistance

**Record:** `ssrn-4873649-p052` · `machine-drafted-source-checked`

## 53. disputes are constructed through transformations rather than discovered as ready-made legal objects

**Location:** I.C. AI Impact on Access to Justice, printed pp. 566 (PDF pp. 18)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 566, that disputes are constructed through transformations rather than discovered as ready-made legal objects. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because injury must be perceived, attributed, and converted into a rights claim before litigation can begin. It connects to social construction, naming blaming claiming, injury attribution, rights consciousness, dispute emergence, legal sociology.

**Evidence anchor:** Printed page 566 (PDF page 18) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** social construction; naming blaming claiming; injury attribution; rights consciousness; dispute emergence; legal sociology

**Record:** `ssrn-4873649-p053` · `machine-drafted-source-checked`

## 54. naming-blaming-claiming filters disproportionately burden people with less educational, social, and financial capital

**Location:** I.C. AI Impact on Access to Justice, printed pp. 566 (PDF pp. 18)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 566, that naming-blaming-claiming filters disproportionately burden people with less educational, social, and financial capital. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because upstream claim attrition is itself a mechanism of inequality. It connects to capital inequality, upstream attrition, legal consciousness, poverty, claim filtering, distributional justice.

**Evidence anchor:** Printed page 566 (PDF page 18) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** capital inequality; upstream attrition; legal consciousness; poverty; claim filtering; distributional justice

**Record:** `ssrn-4873649-p054` · `machine-drafted-source-checked`

## 55. a simple AI response to a landlord-mold question can move a user through all three claim-formation stages

**Location:** I.C. AI Impact on Access to Justice, printed pp. 566 (PDF pp. 18)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 566, that a simple AI response to a landlord-mold question can move a user through all three claim-formation stages. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because generic legal orientation can be transformative for a person who lacks the lawyer's curse of knowledge. It connects to landlord tenant law, legal orientation, habitability, naming harms, claim formation, generative AI.

**Evidence anchor:** Printed page 566 (PDF page 18) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** landlord tenant law; legal orientation; habitability; naming harms; claim formation; generative AI

**Record:** `ssrn-4873649-p055` · `machine-drafted-source-checked`

## 56. routine consultation with AI could change ordinary people's legal consciousness at scale

**Location:** I.C. AI Impact on Access to Justice, printed pp. 567 (PDF pp. 19)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 567, that routine consultation with AI could change ordinary people's legal consciousness at scale. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because small framing interventions accumulate when embedded in the daily information practices of millions of users. It connects to legal consciousness, framing effects, daily AI use, scale, claim activation, sociolegal change.

**Evidence anchor:** Printed page 567 (PDF page 19) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** legal consciousness; framing effects; daily AI use; scale; claim activation; sociolegal change

**Record:** `ssrn-4873649-p056` · `machine-drafted-source-checked`

## 57. AI can help individuals select strategies after recognizing a claim

**Location:** I.C. AI Impact on Access to Justice, printed pp. 567 (PDF pp. 19)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 567, that AI can help individuals select strategies after recognizing a claim. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because guidance about demand letters, agencies, lawyers, and litigation addresses a stage where most people currently rely on informal sources. It connects to legal strategy, demand letters, government agencies, informal advice, decision support, access to justice.

**Evidence anchor:** Printed page 567 (PDF page 19) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** legal strategy; demand letters; government agencies; informal advice; decision support; access to justice

**Record:** `ssrn-4873649-p057` · `machine-drafted-source-checked`

## 58. AI can assist with complaints, motions, filing logistics, and other materials throughout a case

**Location:** I.C. AI Impact on Access to Justice, printed pp. 567 (PDF pp. 19)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 567, that AI can assist with complaints, motions, filing logistics, and other materials throughout a case. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the technology reduces procedural-navigation costs for pro se litigants and can also help represented parties. It connects to pro se litigation, document drafting, motions practice, filing logistics, procedural navigation, legal representation.

**Evidence anchor:** Printed page 567 (PDF page 19) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** pro se litigation; document drafting; motions practice; filing logistics; procedural navigation; legal representation

**Record:** `ssrn-4873649-p058` · `machine-drafted-source-checked`

## 59. predictive and classification tools can reduce uncertainty through document review, outcome prediction, and venue selection

**Location:** I.C. AI Impact on Access to Justice, printed pp. 568 (PDF pp. 20)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 568, that predictive and classification tools can reduce uncertainty through document review, outcome prediction, and venue selection. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because access depends not only on drafting cost but also on the ability to find information and evaluate risk. It connects to predictive analytics, document review, venue selection, case outcomes, litigation uncertainty, legal tech.

**Evidence anchor:** Printed page 568 (PDF page 20) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** predictive analytics; document review; venue selection; case outcomes; litigation uncertainty; legal tech

**Record:** `ssrn-4873649-p059` · `machine-drafted-source-checked`

## 60. the scale of unmet need makes a substantial AI litigation boom plausible even if only a fraction of latent claims are activated

**Location:** I.C. AI Impact on Access to Justice, printed pp. 568 (PDF pp. 20)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 568, that the scale of unmet need makes a substantial AI litigation boom plausible even if only a fraction of latent claims are activated. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because existing caseloads could be transformed by conversion at the margin rather than universal adoption. It connects to latent demand, litigation boom, unmet legal need, marginal conversion, case volume, forecasting.

**Evidence anchor:** Printed page 568 (PDF page 20) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** latent demand; litigation boom; unmet legal need; marginal conversion; case volume; forecasting

**Record:** `ssrn-4873649-p060` · `machine-drafted-source-checked`

## 61. AI threatens judicial economy through verbosity as well as through the number of filings

**Location:** I.C. AI Impact on Access to Justice, printed pp. 568 (PDF pp. 20)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 568, that AI threatens judicial economy through verbosity as well as through the number of filings. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because cheap generation increases the amount of material judges must process inside each case. It connects to filing verbosity, attention scarcity, document volume, judicial workload, generative AI, case complexity.

**Evidence anchor:** Printed page 568 (PDF page 20) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** filing verbosity; attention scarcity; document volume; judicial workload; generative AI; case complexity

**Record:** `ssrn-4873649-p061` · `machine-drafted-source-checked`

## 62. behavioral adaptation, settlement, regulation, and compliance could moderate the predicted litigation boom

**Location:** I.C. AI Impact on Access to Justice, printed pp. 569 (PDF pp. 21)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 569, that behavioral adaptation, settlement, regulation, and compliance could moderate the predicted litigation boom. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the article's forecast allows countervailing feedback rather than assuming a mechanical one-way effect. It connects to behavioral adaptation, settlement, compliance, AI regulation, feedback effects, forecast uncertainty.

**Evidence anchor:** Printed page 569 (PDF page 21) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** behavioral adaptation; settlement; compliance; AI regulation; feedback effects; forecast uncertainty

**Record:** `ssrn-4873649-p062` · `machine-drafted-source-checked`

## 63. some access frictions serve salutary screening functions even though they also block worthy claims

**Location:** I.C. AI Impact on Access to Justice, printed pp. 569 (PDF pp. 21)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 569, that some access frictions serve salutary screening functions even though they also block worthy claims. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because evaluation must distinguish the gross benefit of access from the composition and quality of additional litigation. It connects to beneficial friction, screening, merit, vexatious claims, governance seams, access tradeoffs.

**Evidence anchor:** Printed page 569 (PDF page 21) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** beneficial friction; screening; merit; vexatious claims; governance seams; access tradeoffs

**Record:** `ssrn-4873649-p063` · `machine-drafted-source-checked`

## 64. AI can scale strategic debt-collection claims that current filing costs make uneconomic

**Location:** I.C. AI Impact on Access to Justice, printed pp. 569 (PDF pp. 21)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 569, that AI can scale strategic debt-collection claims that current filing costs make uneconomic. The discussion places this proposition within I.C. AI Impact on Access to Justice and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because organizational plaintiffs as well as underserved individuals will exploit lower litigation costs. It connects to debt buyers, mass litigation, organizational plaintiffs, filing thresholds, automation, distributional effects.

**Evidence anchor:** Printed page 569 (PDF page 21) develops this proposition in I.C. AI Impact on Access to Justice.

**Boundary:** The analysis predicts mechanisms and direction more confidently than magnitude, and it recognizes that AI can enable meritorious, abusive, and strategic claims alike.

**Connections:** debt buyers; mass litigation; organizational plaintiffs; filing thresholds; automation; distributional effects

**Record:** `ssrn-4873649-p064` · `machine-drafted-source-checked`

## 65. an AI-driven rise in caseload can reduce the scrutiny courts give unrelated cases

**Location:** II. Legal Thermostats, printed pp. 570 (PDF pp. 22)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 570, that an AI-driven rise in caseload can reduce the scrutiny courts give unrelated cases. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because fixed judicial time creates spillovers across litigants and subject matters. It connects to caseload spillovers, lightened scrutiny, judicial time, civil appeals, resource constraints, systemic effects.

**Evidence anchor:** Printed page 570 (PDF page 22) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** caseload spillovers; lightened scrutiny; judicial time; civil appeals; resource constraints; systemic effects

**Record:** `ssrn-4873649-p065` · `machine-drafted-source-checked`

## 66. control theory provides a model for understanding how legal institutions maintain equilibrium under shocks

**Location:** II. Legal Thermostats, printed pp. 570 (PDF pp. 22)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 570, that control theory provides a model for understanding how legal institutions maintain equilibrium under shocks. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because courts respond to disturbances through feedback mechanisms rather than leaving doctrine independent of workload. It connects to control theory, feedback loops, equilibrium, institutional response, caseload shocks, legal doctrine.

**Evidence anchor:** Printed page 570 (PDF page 22) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** control theory; feedback loops; equilibrium; institutional response; caseload shocks; legal doctrine

**Record:** `ssrn-4873649-p066` · `machine-drafted-source-checked`

## 67. judicial economy is a closed-loop system in which outputs and workload influence later legal inputs

**Location:** II. Legal Thermostats, printed pp. 570 (PDF pp. 22)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 570, that judicial economy is a closed-loop system in which outputs and workload influence later legal inputs. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because doctrinal responses can endogenously change who files and what claims survive. It connects to closed-loop control, endogenous regulation, filing behavior, doctrinal feedback, judicial economy, dynamic systems.

**Evidence anchor:** Printed page 570 (PDF page 22) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** closed-loop control; endogenous regulation; filing behavior; doctrinal feedback; judicial economy; dynamic systems

**Record:** `ssrn-4873649-p067` · `machine-drafted-source-checked`

## 68. judges modulate litigation through the strictness or leniency of procedural and substantive doctrines

**Location:** II. Legal Thermostats, printed pp. 571 (PDF pp. 23)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 571, that judges modulate litigation through the strictness or leniency of procedural and substantive doctrines. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because legal standards function as actuators that change the flow of cases toward an institutional setpoint. It connects to judicial discretion, legal actuators, procedural doctrine, substantive doctrine, caseload control, setpoints.

**Evidence anchor:** Printed page 571 (PDF page 23) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** judicial discretion; legal actuators; procedural doctrine; substantive doctrine; caseload control; setpoints

**Record:** `ssrn-4873649-p068` · `machine-drafted-source-checked`

## 69. thermostat adjustments inevitably affect rights when doctrine is used to manage resources

**Location:** II. Legal Thermostats, printed pp. 571 (PDF pp. 23)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 571, that thermostat adjustments inevitably affect rights when doctrine is used to manage resources. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because administrative homeostasis is not normatively neutral for individual litigants. It connects to rights effects, administrative adjustment, homeostasis, individual justice, procedure, substantive law.

**Evidence anchor:** Printed page 571 (PDF page 23) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** rights effects; administrative adjustment; homeostasis; individual justice; procedure; substantive law

**Record:** `ssrn-4873649-p069` · `machine-drafted-source-checked`

## 70. court fees are a direct legal thermostat because they deter claims below a litigant's expected value threshold

**Location:** II. Legal Thermostats, printed pp. 571 (PDF pp. 23)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 571, that court fees are a direct legal thermostat because they deter claims below a litigant's expected value threshold. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because price can regulate docket demand without reliably separating socially valuable from trivial claims. It connects to court fees, expected value, claim deterrence, docket control, screening errors, judicial economy.

**Evidence anchor:** Printed page 571 (PDF page 23) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** court fees; expected value; claim deterrence; docket control; screening errors; judicial economy

**Record:** `ssrn-4873649-p070` · `machine-drafted-source-checked`

## 71. fees and de minimis rules screen out socially important litigation as well as low-value cases

**Location:** II. Legal Thermostats, printed pp. 572 (PDF pp. 24)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 572, that fees and de minimis rules screen out socially important litigation as well as low-value cases. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because monetary size is an unreliable proxy for legal or social importance. It connects to de minimis, social value, court fees, screening, small claims, rights enforcement.

**Evidence anchor:** Printed page 572 (PDF page 24) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** de minimis; social value; court fees; screening; small claims; rights enforcement

**Record:** `ssrn-4873649-p071` · `machine-drafted-source-checked`

## 72. even modest logistical barriers such as courthouse distance have large effects on poor litigants

**Location:** II. Legal Thermostats, printed pp. 572 (PDF pp. 24)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 572, that even modest logistical barriers such as courthouse distance have large effects on poor litigants. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because seemingly minor friction can determine participation in life-changing proceedings. It connects to courthouse distance, participation, poverty, eviction, administrative burden, access to justice.

**Evidence anchor:** Printed page 572 (PDF page 24) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** courthouse distance; participation; poverty; eviction; administrative burden; access to justice

**Record:** `ssrn-4873649-p072` · `machine-drafted-source-checked`

## 73. Twombly and Iqbal heightened pleading standards partly to control discovery costs

**Location:** II. Legal Thermostats, printed pp. 572 (PDF pp. 24)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 572, that Twombly and Iqbal heightened pleading standards partly to control discovery costs. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because a doctrine framed as factual plausibility also regulates downstream expenditure of judicial and party resources. It connects to pleading standards, Twombly, Iqbal, discovery costs, plausibility, procedural thermostat.

**Evidence anchor:** Printed page 572 (PDF page 24) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** pleading standards; Twombly; Iqbal; discovery costs; plausibility; procedural thermostat

**Record:** `ssrn-4873649-p073` · `machine-drafted-source-checked`

## 74. heightened pleading standards appear to burden pro se plaintiffs more than represented parties

**Location:** II. Legal Thermostats, printed pp. 573 (PDF pp. 25)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 573, that heightened pleading standards appear to burden pro se plaintiffs more than represented parties. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because rules of formal sufficiency can translate sophistication gaps into case dismissal. It connects to pro se litigants, dismissals, pleading inequality, representation, procedural barriers, empirical civil procedure.

**Evidence anchor:** Printed page 573 (PDF page 25) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** pro se litigants; dismissals; pleading inequality; representation; procedural barriers; empirical civil procedure

**Record:** `ssrn-4873649-p074` · `machine-drafted-source-checked`

## 75. Lone Pine orders manage complex litigation by demanding preliminary injury and causation evidence

**Location:** II. Legal Thermostats, printed pp. 573 (PDF pp. 25)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 573, that Lone Pine orders manage complex litigation by demanding preliminary injury and causation evidence. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because front-loaded proof can cull weak claims while imposing potentially unrealistic burdens on plaintiffs. It connects to Lone Pine orders, toxic torts, causation, case management, front-loaded proof, mass litigation.

**Evidence anchor:** Printed page 573 (PDF page 25) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** Lone Pine orders; toxic torts; causation; case management; front-loaded proof; mass litigation

**Record:** `ssrn-4873649-p075` · `machine-drafted-source-checked`

## 76. exhaustion requirements operate as thermostats by forcing claimants through administrative processes before court

**Location:** II. Legal Thermostats, printed pp. 573 (PDF pp. 25)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 573, that exhaustion requirements operate as thermostats by forcing claimants through administrative processes before court. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because procedural sequencing can substantially reduce the number of claims that reach judges. It connects to administrative exhaustion, prisoner rights, procedural sequencing, claim attrition, agency process, judicial efficiency.

**Evidence anchor:** Printed page 573 (PDF page 25) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** administrative exhaustion; prisoner rights; procedural sequencing; claim attrition; agency process; judicial efficiency

**Record:** `ssrn-4873649-p076` · `machine-drafted-source-checked`

## 77. the Prison Litigation Reform Act illustrates an explicit legislative response to perceived caseload pressure

**Location:** II. Legal Thermostats, printed pp. 574 (PDF pp. 26)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 574, that the Prison Litigation Reform Act illustrates an explicit legislative response to perceived caseload pressure. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because concern about frivolous filings can produce durable restrictions on a politically marginalized claimant group. It connects to PLRA, prison litigation, frivolous claims, legislative response, marginalized litigants, rights restriction.

**Evidence anchor:** Printed page 574 (PDF page 26) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** PLRA; prison litigation; frivolous claims; legislative response; marginalized litigants; rights restriction

**Record:** `ssrn-4873649-p077` · `machine-drafted-source-checked`

## 78. exhaustion serves both agency authority and judicial-efficiency rationales

**Location:** II. Legal Thermostats, printed pp. 574 (PDF pp. 26)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 574, that exhaustion serves both agency authority and judicial-efficiency rationales. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because a single doctrine can pursue institutional values while also filtering access. It connects to agency authority, judicial efficiency, exhaustion, dual purpose, administrative law, claim filtering.

**Evidence anchor:** Printed page 574 (PDF page 26) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** agency authority; judicial efficiency; exhaustion; dual purpose; administrative law; claim filtering

**Record:** `ssrn-4873649-p078` · `machine-drafted-source-checked`

## 79. only a small fraction of discrimination charges appear to become federal lawsuits

**Location:** II. Legal Thermostats, printed pp. 574 (PDF pp. 26)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 574, that only a small fraction of discrimination charges appear to become federal lawsuits. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because administrative exhaustion and related filters produce substantial attrition between grievance and adjudication. It connects to EEOC, employment discrimination, claim attrition, federal litigation, administrative process, empirical estimation.

**Evidence anchor:** Printed page 574 (PDF page 26) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** EEOC; employment discrimination; claim attrition; federal litigation; administrative process; empirical estimation

**Record:** `ssrn-4873649-p079` · `machine-drafted-source-checked`

## 80. the Supreme Court selected a stricter causation standard for retaliation partly out of floodgate concerns

**Location:** II. Legal Thermostats, printed pp. 575 (PDF pp. 27)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 575, that the Supreme Court selected a stricter causation standard for retaliation partly out of floodgate concerns. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because substantive proof rules can ration court resources while making meritorious claims harder to win. It connects to Title VII retaliation, but-for causation, floodgates, proof standards, resource rationing, substantive rights.

**Evidence anchor:** Printed page 575 (PDF page 27) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** Title VII retaliation; but-for causation; floodgates; proof standards; resource rationing; substantive rights

**Record:** `ssrn-4873649-p080` · `machine-drafted-source-checked`

## 81. statutes of limitations sometimes operate as volume and quality controls rather than only as evidence-preservation rules

**Location:** II. Legal Thermostats, printed pp. 575 (PDF pp. 27)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 575, that statutes of limitations sometimes operate as volume and quality controls rather than only as evidence-preservation rules. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because time bars can function as litigation filters even when delay is unrelated to claim merit. It connects to statutes of limitations, claim volume, evidence preservation, arbitrary deadlines, litigation filtering, procedural justice.

**Evidence anchor:** Printed page 575 (PDF page 27) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** statutes of limitations; claim volume; evidence preservation; arbitrary deadlines; litigation filtering; procedural justice

**Record:** `ssrn-4873649-p081` · `machine-drafted-source-checked`

## 82. legal thermostats commonly work by adding friction with an often-unverified hope that weaker claims will be deterred

**Location:** II. Legal Thermostats, printed pp. 575 (PDF pp. 27)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 575, that legal thermostats commonly work by adding friction with an often-unverified hope that weaker claims will be deterred. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because administrative burdens do not reliably discriminate between just and unjust claims. It connects to regulatory friction, merit screening, administrative burden, false positives, procedural design, access to justice.

**Evidence anchor:** Printed page 575 (PDF page 27) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** regulatory friction; merit screening; administrative burden; false positives; procedural design; access to justice

**Record:** `ssrn-4873649-p082` · `machine-drafted-source-checked`

## 83. AI makes some existing thermostats fragile by helping users meet deadlines, exhaust remedies, and draft plausible pleadings

**Location:** II. Legal Thermostats, printed pp. 576 (PDF pp. 28)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 576, that AI makes some existing thermostats fragile by helping users meet deadlines, exhaust remedies, and draft plausible pleadings. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because filters based on information and labor costs lose force when machines supply those inputs cheaply. It connects to AI-proof regulation, deadlines, administrative exhaustion, pleading assistance, proof of work, regulatory adaptation.

**Evidence anchor:** Printed page 576 (PDF page 28) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** AI-proof regulation; deadlines; administrative exhaustion; pleading assistance; proof of work; regulatory adaptation

**Record:** `ssrn-4873649-p083` · `machine-drafted-source-checked`

## 84. plausibility pleading filters poor framing and polish as well as genuinely implausible claims

**Location:** II. Legal Thermostats, printed pp. 576 (PDF pp. 28)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 576, that plausibility pleading filters poor framing and polish as well as genuinely implausible claims. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because AI can remove the sophistication penalty without improving the merits of the underlying case. It connects to plausibility, legal polish, pro se litigants, framing, merit, generative drafting.

**Evidence anchor:** Printed page 576 (PDF page 28) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** plausibility; legal polish; pro se litigants; framing; merit; generative drafting

**Record:** `ssrn-4873649-p084` · `machine-drafted-source-checked`

## 85. a doubling of litigation volume is plausible but the forecast is expressly falsifiable

**Location:** II. Legal Thermostats, printed pp. 576 (PDF pp. 28)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 576, that a doubling of litigation volume is plausible but the forecast is expressly falsifiable. The discussion places this proposition within II. Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the article offers a concrete time-sensitive prediction rather than insulating its thesis from evidence. It connects to doubling forecast, falsifiability, litigation patterns, empirical prediction, AI effect, research design.

**Evidence anchor:** Printed page 576 (PDF page 28) develops this proposition in II. Legal Thermostats.

**Boundary:** The examples show that legal rules can regulate caseload without proving that docket control is the sole or conscious cause of every doctrinal choice.

**Connections:** doubling forecast; falsifiability; litigation patterns; empirical prediction; AI effect; research design

**Record:** `ssrn-4873649-p085` · `machine-drafted-source-checked`

## 86. AI is likely to increase both the number and intricacy of legal filings

**Location:** III.A. Strategy 1: Legal Thermostats, printed pp. 577 (PDF pp. 29)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 577, that AI is likely to increase both the number and intricacy of legal filings. The discussion places this proposition within III.A. Strategy 1: Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because judicial workload depends on material per case as well as case count. It connects to filing volume, filing intricacy, verbosity, judicial workload, litigation boom, attention management.

**Evidence anchor:** Printed page 577 (PDF page 29) develops this proposition in III.A. Strategy 1: Legal Thermostats.

**Boundary:** The discussion evaluates likely systemic effects; particular fees, pleading rules, and substantive standards may differ in purpose, legality, and distributional impact.

**Connections:** filing volume; filing intricacy; verbosity; judicial workload; litigation boom; attention management

**Record:** `ssrn-4873649-p086` · `machine-drafted-source-checked`

## 87. courts could respond by increasing fees, heightening pleading demands, or narrowing substantive rights

**Location:** III.A. Strategy 1: Legal Thermostats, printed pp. 577 (PDF pp. 29)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 577, that courts could respond by increasing fees, heightening pleading demands, or narrowing substantive rights. The discussion places this proposition within III.A. Strategy 1: Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because historically available levers can suppress demand but place justice costs on litigants. It connects to fees, pleading standards, substantive rights, demand suppression, court response, legal thermostats.

**Evidence anchor:** Printed page 577 (PDF page 29) develops this proposition in III.A. Strategy 1: Legal Thermostats.

**Boundary:** The discussion evaluates likely systemic effects; particular fees, pleading rules, and substantive standards may differ in purpose, legality, and distributional impact.

**Connections:** fees; pleading standards; substantive rights; demand suppression; court response; legal thermostats

**Record:** `ssrn-4873649-p087` · `machine-drafted-source-checked`

## 88. the best available time before a litigation boom should be used to build and test court-side AI

**Location:** III.A. Strategy 1: Legal Thermostats, printed pp. 577 (PDF pp. 29)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 577, that the best available time before a litigation boom should be used to build and test court-side AI. The discussion places this proposition within III.A. Strategy 1: Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because institutional preparation expands the option set before caseload pressure makes blunt controls politically attractive. It connects to preparation, AI testing, institutional options, caseload pressure, court modernization, proactive governance.

**Evidence anchor:** Printed page 577 (PDF page 29) develops this proposition in III.A. Strategy 1: Legal Thermostats.

**Boundary:** The discussion evaluates likely systemic effects; particular fees, pleading rules, and substantive standards may differ in purpose, legality, and distributional impact.

**Connections:** preparation; AI testing; institutional options; caseload pressure; court modernization; proactive governance

**Record:** `ssrn-4873649-p088` · `machine-drafted-source-checked`

## 89. higher court fees are a crude filter with disproportionate effects on people who lack capital

**Location:** III.A. Strategy 1: Legal Thermostats, printed pp. 578 (PDF pp. 30)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 578, that higher court fees are a crude filter with disproportionate effects on people who lack capital. The discussion places this proposition within III.A. Strategy 1: Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because liquidity constraints and the risk of ruin prevent even holders of meritorious claims from borrowing to litigate. It connects to court fees, liquidity, risk of ruin, litigation finance, poverty, meritorious claims.

**Evidence anchor:** Printed page 578 (PDF page 30) develops this proposition in III.A. Strategy 1: Legal Thermostats.

**Boundary:** The discussion evaluates likely systemic effects; particular fees, pleading rules, and substantive standards may differ in purpose, legality, and distributional impact.

**Connections:** court fees; liquidity; risk of ruin; litigation finance; poverty; meritorious claims

**Record:** `ssrn-4873649-p089` · `machine-drafted-source-checked`

## 90. pleading standards can be understood as proof-of-work mechanisms

**Location:** III.A. Strategy 1: Legal Thermostats, printed pp. 578 (PDF pp. 30)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 578, that pleading standards can be understood as proof-of-work mechanisms. The discussion places this proposition within III.A. Strategy 1: Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because front-end effort is supposed to signal a claimant's private confidence and screen low-value filings. It connects to proof of work, pleading, signaling, front-end costs, claimant confidence, screening.

**Evidence anchor:** Printed page 578 (PDF page 30) develops this proposition in III.A. Strategy 1: Legal Thermostats.

**Boundary:** The discussion evaluates likely systemic effects; particular fees, pleading rules, and substantive standards may differ in purpose, legality, and distributional impact.

**Connections:** proof of work; pleading; signaling; front-end costs; claimant confidence; screening

**Record:** `ssrn-4873649-p090` · `machine-drafted-source-checked`

## 91. word limits are also crude judicial-economy tools and are not robust to AI

**Location:** III.A. Strategy 1: Legal Thermostats, printed pp. 578 (PDF pp. 30)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 578, that word limits are also crude judicial-economy tools and are not robust to AI. The discussion places this proposition within III.A. Strategy 1: Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because making a filing concise traditionally consumes skill and time that automated summarization can cheaply supply. It connects to word limits, summarization, filing regulation, judicial economy, AI circumvention, legal writing.

**Evidence anchor:** Printed page 578 (PDF page 30) develops this proposition in III.A. Strategy 1: Legal Thermostats.

**Boundary:** The discussion evaluates likely systemic effects; particular fees, pleading rules, and substantive standards may differ in purpose, legality, and distributional impact.

**Connections:** word limits; summarization; filing regulation; judicial economy; AI circumvention; legal writing

**Record:** `ssrn-4873649-p091` · `machine-drafted-source-checked`

## 92. generative AI undermines pleading proof of work by converting vague claims into polished legal arguments

**Location:** III.A. Strategy 1: Legal Thermostats, printed pp. 579 (PDF pp. 31)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 579, that generative AI undermines pleading proof of work by converting vague claims into polished legal arguments. The discussion places this proposition within III.A. Strategy 1: Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because surface quality no longer reliably signals costly human investment or underlying merit. It connects to generative drafting, proof of work, surface plausibility, signal degradation, pleadings, claim merit.

**Evidence anchor:** Printed page 579 (PDF page 31) develops this proposition in III.A. Strategy 1: Legal Thermostats.

**Boundary:** The discussion evaluates likely systemic effects; particular fees, pleading rules, and substantive standards may differ in purpose, legality, and distributional impact.

**Connections:** generative drafting; proof of work; surface plausibility; signal degradation; pleadings; claim merit

**Record:** `ssrn-4873649-p092` · `machine-drafted-source-checked`

## 93. AI hallucinations can make a weak filing appear facially plausible

**Location:** III.A. Strategy 1: Legal Thermostats, printed pp. 579 (PDF pp. 31)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 579, that AI hallucinations can make a weak filing appear facially plausible. The discussion places this proposition within III.A. Strategy 1: Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because fabricated facts and authorities increase the cost of validation even when they do not improve substantive truth. It connects to hallucinations, facial plausibility, validation costs, false facts, legal authority, quality control.

**Evidence anchor:** Printed page 579 (PDF page 31) develops this proposition in III.A. Strategy 1: Legal Thermostats.

**Boundary:** The discussion evaluates likely systemic effects; particular fees, pleading rules, and substantive standards may differ in purpose, legality, and distributional impact.

**Connections:** hallucinations; facial plausibility; validation costs; false facts; legal authority; quality control

**Record:** `ssrn-4873649-p093` · `machine-drafted-source-checked`

## 94. judges can conserve resources by quietly demanding more through substantive standards

**Location:** III.A. Strategy 1: Legal Thermostats, printed pp. 579 (PDF pp. 31)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 579, that judges can conserve resources by quietly demanding more through substantive standards. The discussion places this proposition within III.A. Strategy 1: Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because shifts in concepts such as reasonableness may ration claims without appearing as explicit docket policy. It connects to substantive standards, reasonable person, implicit rationing, doctrinal drift, judicial resources, transparency.

**Evidence anchor:** Printed page 579 (PDF page 31) develops this proposition in III.A. Strategy 1: Legal Thermostats.

**Boundary:** The discussion evaluates likely systemic effects; particular fees, pleading rules, and substantive standards may differ in purpose, legality, and distributional impact.

**Connections:** substantive standards; reasonable person; implicit rationing; doctrinal drift; judicial resources; transparency

**Record:** `ssrn-4873649-p094` · `machine-drafted-source-checked`

## 95. thermostat adjustment can narrow civil rights and subsidize wrongdoing

**Location:** III.A. Strategy 1: Legal Thermostats, printed pp. 580 (PDF pp. 32)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 580, that thermostat adjustment can narrow civil rights and subsidize wrongdoing. The discussion places this proposition within III.A. Strategy 1: Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because fewer enforceable claims reduce the expected legal cost of socially harmful conduct. It connects to civil rights, wrongdoing subsidy, deterrence, rights contraction, enforcement, externalities.

**Evidence anchor:** Printed page 580 (PDF page 32) develops this proposition in III.A. Strategy 1: Legal Thermostats.

**Boundary:** The discussion evaluates likely systemic effects; particular fees, pleading rules, and substantive standards may differ in purpose, legality, and distributional impact.

**Connections:** civil rights; wrongdoing subsidy; deterrence; rights contraction; enforcement; externalities

**Record:** `ssrn-4873649-p095` · `machine-drafted-source-checked`

## 96. AI-vulnerable thermostats may require repeated escalation

**Location:** III.A. Strategy 1: Legal Thermostats, printed pp. 580 (PDF pp. 32)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 580, that AI-vulnerable thermostats may require repeated escalation. The discussion places this proposition within III.A. Strategy 1: Legal Thermostats and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because each new restriction can be circumvented by better generation, producing unstable and increasingly demanding barriers. It connects to regulatory escalation, AI circumvention, unstable equilibrium, procedural barriers, arms race, legal thermostats.

**Evidence anchor:** Printed page 580 (PDF page 32) develops this proposition in III.A. Strategy 1: Legal Thermostats.

**Boundary:** The discussion evaluates likely systemic effects; particular fees, pleading rules, and substantive standards may differ in purpose, legality, and distributional impact.

**Connections:** regulatory escalation; AI circumvention; unstable equilibrium; procedural barriers; arms race; legal thermostats

**Record:** `ssrn-4873649-p096` · `machine-drafted-source-checked`

## 97. waiting is understandable because AI capabilities and adoption patterns remain uncertain

**Location:** III.B. Strategy 2: Sit and Wait, printed pp. 580 (PDF pp. 32)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 580, that waiting is understandable because AI capabilities and adoption patterns remain uncertain. The discussion places this proposition within III.B. Strategy 2: Sit and Wait and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because courts should recognize the genuine costs of acting on hype and the precedent of absorbing earlier legal technologies. It connects to institutional caution, technological uncertainty, LegalZoom, LexisNexis, hype cycle, judicial administration.

**Evidence anchor:** Printed page 580 (PDF page 32) develops this proposition in III.B. Strategy 2: Sit and Wait.

**Boundary:** The recommendation depends on a forecast of substantial AI-driven litigation growth that the article expressly treats as empirically falsifiable.

**Connections:** institutional caution; technological uncertainty; LegalZoom; LexisNexis; hype cycle; judicial administration

**Record:** `ssrn-4873649-p097` · `machine-drafted-source-checked`

## 98. the identity of dominant AI litigants will shape the technology's normative effects

**Location:** III.B. Strategy 2: Sit and Wait, printed pp. 581 (PDF pp. 33)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 581, that the identity of dominant AI litigants will shape the technology's normative effects. The discussion places this proposition within III.B. Strategy 2: Sit and Wait and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because access gains differ if tools empower pro se claimants, elite firms, patent entities, or automated litigation agents. It connects to user composition, pro se litigants, elite firms, patent entities, automated agents, distributional evaluation.

**Evidence anchor:** Printed page 581 (PDF page 33) develops this proposition in III.B. Strategy 2: Sit and Wait.

**Boundary:** The recommendation depends on a forecast of substantial AI-driven litigation growth that the article expressly treats as empirically falsifiable.

**Connections:** user composition; pro se litigants; elite firms; patent entities; automated agents; distributional evaluation

**Record:** `ssrn-4873649-p098` · `machine-drafted-source-checked`

## 99. unreliability is a reason for staged development and testing rather than passive observation

**Location:** III.B. Strategy 2: Sit and Wait, printed pp. 581 (PDF pp. 33)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 581, that unreliability is a reason for staged development and testing rather than passive observation. The discussion places this proposition within III.B. Strategy 2: Sit and Wait and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because institutional experimentation can refine tools while preserving the ability to respond before a shock. It connects to staged deployment, testing, AI reliability, institutional readiness, risk management, proactive adaptation.

**Evidence anchor:** Printed page 581 (PDF page 33) develops this proposition in III.B. Strategy 2: Sit and Wait.

**Boundary:** The recommendation depends on a forecast of substantial AI-driven litigation growth that the article expressly treats as empirically falsifiable.

**Connections:** staged deployment; testing; AI reliability; institutional readiness; risk management; proactive adaptation

**Record:** `ssrn-4873649-p099` · `machine-drafted-source-checked`

## 100. court technology can improve justice even if the predicted litigation boom proves smaller than expected

**Location:** III.B. Strategy 2: Sit and Wait, printed pp. 581 (PDF pp. 33)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 581, that court technology can improve justice even if the predicted litigation boom proves smaller than expected. The discussion places this proposition within III.B. Strategy 2: Sit and Wait and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because video proceedings and digital research show that modernization has independent accessibility and efficiency benefits. It connects to robust policy, video proceedings, digital research, court modernization, accessibility, efficiency.

**Evidence anchor:** Printed page 581 (PDF page 33) develops this proposition in III.B. Strategy 2: Sit and Wait.

**Boundary:** The recommendation depends on a forecast of substantial AI-driven litigation growth that the article expressly treats as empirically falsifiable.

**Connections:** robust policy; video proceedings; digital research; court modernization; accessibility; efficiency

**Record:** `ssrn-4873649-p100` · `machine-drafted-source-checked`

## 101. a durable courtroom ban on generative AI would sacrifice the technology's democratizing potential

**Location:** III.C. Strategy 3: Ban and Mark, printed pp. 582 (PDF pp. 34)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 582, that a durable courtroom ban on generative AI would sacrifice the technology's democratizing potential. The discussion places this proposition within III.C. Strategy 3: Ban and Mark and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because excluding a low-cost tool entrenches advantages enjoyed by parties who can buy human legal production. It connects to AI ban, democratization, cost inequality, courtroom rules, access to justice, technology governance.

**Evidence anchor:** Printed page 582 (PDF page 34) develops this proposition in III.C. Strategy 3: Ban and Mark.

**Boundary:** The critique concerns broad, durable bans and disclosure mandates; it does not reject targeted duties of candor, verification, or sanctions for false filings.

**Connections:** AI ban; democratization; cost inequality; courtroom rules; access to justice; technology governance

**Record:** `ssrn-4873649-p101` · `machine-drafted-source-checked`

## 102. AI-text disclosure regimes are difficult to enforce because detection is probabilistic and easy to evade

**Location:** III.C. Strategy 3: Ban and Mark, printed pp. 582 (PDF pp. 34)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 582, that AI-text disclosure regimes are difficult to enforce because detection is probabilistic and easy to evade. The discussion places this proposition within III.C. Strategy 3: Ban and Mark and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because a mandate that mainly catches unsophisticated users is both ineffective and distributionally skewed. It connects to AI detection, disclosure, enforcement, false positives, sophistication, distributional effects.

**Evidence anchor:** Printed page 582 (PDF page 34) develops this proposition in III.C. Strategy 3: Ban and Mark.

**Boundary:** The critique concerns broad, durable bans and disclosure mandates; it does not reject targeted duties of candor, verification, or sanctions for false filings.

**Connections:** AI detection; disclosure; enforcement; false positives; sophistication; distributional effects

**Record:** `ssrn-4873649-p102` · `machine-drafted-source-checked`

## 103. ubiquitous AI integration will make generic disclosure as uninformative as disclosing use of a computer or search engine

**Location:** III.C. Strategy 3: Ban and Mark, printed pp. 582 (PDF pp. 34)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 582, that ubiquitous AI integration will make generic disclosure as uninformative as disclosing use of a computer or search engine. The discussion places this proposition within III.C. Strategy 3: Ban and Mark and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because a warning that communicates no actionable risk becomes boilerplate rather than meaningful oversight. It connects to ubiquitous computing, boilerplate disclosure, actionable information, legal practice, search engines, oversight.

**Evidence anchor:** Printed page 582 (PDF page 34) develops this proposition in III.C. Strategy 3: Ban and Mark.

**Boundary:** The critique concerns broad, durable bans and disclosure mandates; it does not reject targeted duties of candor, verification, or sanctions for false filings.

**Connections:** ubiquitous computing; boilerplate disclosure; actionable information; legal practice; search engines; oversight

**Record:** `ssrn-4873649-p103` · `machine-drafted-source-checked`

## 104. the direct response to greater demand for justice is to increase judicial resources

**Location:** III.D. Strategy 4: Massive Funding, printed pp. 583 (PDF pp. 35)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 583, that the direct response to greater demand for justice is to increase judicial resources. The discussion places this proposition within III.D. Strategy 4: Massive Funding and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because caseload pressure is fundamentally a capacity problem rather than merely a litigant-behavior problem. It connects to court funding, judicial capacity, public budgeting, caseload demand, institutional supply, access to justice.

**Evidence anchor:** Printed page 583 (PDF page 35) develops this proposition in III.D. Strategy 4: Massive Funding.

**Boundary:** The budget comparison is an order-of-magnitude argument, not a complete fiscal model of federal, state, and local courts or legal-aid substitution.

**Connections:** court funding; judicial capacity; public budgeting; caseload demand; institutional supply; access to justice

**Record:** `ssrn-4873649-p104` · `machine-drafted-source-checked`

## 105. funding sufficient to meet a twofold or fivefold caseload increase is politically tenuous

**Location:** III.D. Strategy 4: Massive Funding, printed pp. 583 (PDF pp. 35)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 583, that funding sufficient to meet a twofold or fivefold caseload increase is politically tenuous. The discussion places this proposition within III.D. Strategy 4: Massive Funding and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the plausible scale of latent demand exceeds ordinary incremental budget solutions. It connects to budget realism, caseload scenarios, political economy, court staffing, latent demand, public finance.

**Evidence anchor:** Printed page 583 (PDF page 35) develops this proposition in III.D. Strategy 4: Massive Funding.

**Boundary:** The budget comparison is an order-of-magnitude argument, not a complete fiscal model of federal, state, and local courts or legal-aid substitution.

**Connections:** budget realism; caseload scenarios; political economy; court staffing; latent demand; public finance

**Record:** `ssrn-4873649-p105` · `machine-drafted-source-checked`

## 106. redirecting legal-aid budgets to courts would at most supply limited additional capacity

**Location:** III.D. Strategy 4: Massive Funding, printed pp. 583 (PDF pp. 35)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 583, that redirecting legal-aid budgets to courts would at most supply limited additional capacity. The discussion places this proposition within III.D. Strategy 4: Massive Funding and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because even complete substitution would mismatch the size of the federal judiciary and leave other legal-aid functions unmet. It connects to legal aid budgets, federal courts, resource reallocation, substitution, fiscal scale, service functions.

**Evidence anchor:** Printed page 583 (PDF page 35) develops this proposition in III.D. Strategy 4: Massive Funding.

**Boundary:** The budget comparison is an order-of-magnitude argument, not a complete fiscal model of federal, state, and local courts or legal-aid substitution.

**Connections:** legal aid budgets; federal courts; resource reallocation; substitution; fiscal scale; service functions

**Record:** `ssrn-4873649-p106` · `machine-drafted-source-checked`

## 107. hollowing out legal aid to fund courts would scratch only the surface if AI meaningfully increases demand

**Location:** III.D. Strategy 4: Massive Funding, printed pp. 584 (PDF pp. 36)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 584, that hollowing out legal aid to fund courts would scratch only the surface if AI meaningfully increases demand. The discussion places this proposition within III.D. Strategy 4: Massive Funding and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the stronger the premise that AI can replace some services, the larger the induced claims pressure becomes. It connects to induced demand, legal aid, court budgets, AI substitution, capacity gap, policy tradeoff.

**Evidence anchor:** Printed page 584 (PDF page 36) develops this proposition in III.D. Strategy 4: Massive Funding.

**Boundary:** The budget comparison is an order-of-magnitude argument, not a complete fiscal model of federal, state, and local courts or legal-aid substitution.

**Connections:** induced demand; legal aid; court budgets; AI substitution; capacity gap; policy tradeoff

**Record:** `ssrn-4873649-p107` · `machine-drafted-source-checked`

## 108. court-side AI integration can amplify the productivity of judges and clerks

**Location:** III.E. Strategy 5: Integration, printed pp. 584 (PDF pp. 36)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 584, that court-side AI integration can amplify the productivity of judges and clerks. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because increasing the supply of adjudicative processing avoids suppressing claims through rights restrictions. It connects to judicial productivity, law clerks, court AI, adjudicative supply, rights preservation, scaling.

**Evidence anchor:** Printed page 584 (PDF page 36) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** judicial productivity; law clerks; court AI; adjudicative supply; rights preservation; scaling

**Record:** `ssrn-4873649-p108` · `machine-drafted-source-checked`

## 109. judicial use of generative AI is already emerging organically

**Location:** III.E. Strategy 5: Integration, printed pp. 584 (PDF pp. 36)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 584, that judicial use of generative AI is already emerging organically. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because integration is not merely speculative and institutional resistance must account for actual professional practice. It connects to judicial adoption, opinion drafting, organic diffusion, professional practice, generative AI, court innovation.

**Evidence anchor:** Printed page 584 (PDF page 36) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** judicial adoption; opinion drafting; organic diffusion; professional practice; generative AI; court innovation

**Record:** `ssrn-4873649-p109` · `machine-drafted-source-checked`

## 110. Judge Newsom's use of generative interpretation shows AI entering mainstream interpretive practice

**Location:** III.E. Strategy 5: Integration, printed pp. 585 (PDF pp. 37)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 585, that Judge Newsom's use of generative interpretation shows AI entering mainstream interpretive practice. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because a federal appellate opinion transforms an academic proposal into an institutional proof of concept. It connects to generative interpretation, ordinary meaning, Judge Newsom, appellate judging, textualism, legal innovation.

**Evidence anchor:** Printed page 585 (PDF page 37) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** generative interpretation; ordinary meaning; Judge Newsom; appellate judging; textualism; legal innovation

**Record:** `ssrn-4873649-p110` · `machine-drafted-source-checked`

## 111. robo-judging should not be the central frame for thinking about court AI

**Location:** III.E. Strategy 5: Integration, printed pp. 585 (PDF pp. 37)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 585, that robo-judging should not be the central frame for thinking about court AI. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because provocative automation scenarios distract from lower-stakes tools that can deliver substantial capacity gains. It connects to robo-judging, framing, decision support, court operations, incremental automation, judicial capacity.

**Evidence anchor:** Printed page 585 (PDF page 37) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** robo-judging; framing; decision support; court operations; incremental automation; judicial capacity

**Record:** `ssrn-4873649-p111` · `machine-drafted-source-checked`

## 112. a human-in-the-loop design can address much of the ethical concern about nonhuman adjudication

**Location:** III.E. Strategy 5: Integration, printed pp. 585 (PDF pp. 37)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 585, that a human-in-the-loop design can address much of the ethical concern about nonhuman adjudication. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because AI can support rather than replace the citizen official who remains accountable for judgment. It connects to human in the loop, judicial accountability, algorithmic adjudication, ethical design, decision support, legitimacy.

**Evidence anchor:** Printed page 585 (PDF page 37) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** human in the loop; judicial accountability; algorithmic adjudication; ethical design; decision support; legitimacy

**Record:** `ssrn-4873649-p112` · `machine-drafted-source-checked`

## 113. summarization is a central court-side use case because litigation produces overwhelming volumes of text

**Location:** III.E. Strategy 5: Integration, printed pp. 586 (PDF pp. 38)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 586, that summarization is a central court-side use case because litigation produces overwhelming volumes of text. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because compressing information helps judges allocate scarce attention without delegating final judgment. It connects to summarization, information overload, judicial attention, legal documents, decision support, case management.

**Evidence anchor:** Printed page 586 (PDF page 38) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** summarization; information overload; judicial attention; legal documents; decision support; case management

**Record:** `ssrn-4873649-p113` · `machine-drafted-source-checked`

## 114. abstractive and extractive summaries serve different judicial needs

**Location:** III.E. Strategy 5: Integration, printed pp. 586 (PDF pp. 38)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 586, that abstractive and extractive summaries serve different judicial needs. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because orientation requires synthesized meaning while verification and close analysis require direct textual selections. It connects to abstractive summarization, extractive summarization, orientation, verification, natural language processing, judicial workflow.

**Evidence anchor:** Printed page 586 (PDF page 38) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** abstractive summarization; extractive summarization; orientation; verification; natural language processing; judicial workflow

**Record:** `ssrn-4873649-p114` · `machine-drafted-source-checked`

## 115. court-generated summaries can be less strategically framed than party-written summaries

**Location:** III.E. Strategy 5: Integration, printed pp. 586 (PDF pp. 38)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 586, that court-generated summaries can be less strategically framed than party-written summaries. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because a neutral workflow tool lacks the litigant's stake in highlighting only favorable aspects of the record. It connects to neutrality, party advocacy, automated summaries, framing, case files, attention management.

**Evidence anchor:** Printed page 586 (PDF page 38) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** neutrality; party advocacy; automated summaries; framing; case files; attention management

**Record:** `ssrn-4873649-p115` · `machine-drafted-source-checked`

## 116. automated summaries could be integrated at the case-management layer for every submitted document

**Location:** III.E. Strategy 5: Integration, printed pp. 587 (PDF pp. 39)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 587, that automated summaries could be integrated at the case-management layer for every submitted document. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because system-wide preprocessing makes the record easier to sort and navigate before chambers begins substantive review. It connects to case management systems, document ingestion, automated summaries, workflow automation, record navigation, court infrastructure.

**Evidence anchor:** Printed page 587 (PDF page 39) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** case management systems; document ingestion; automated summaries; workflow automation; record navigation; court infrastructure

**Record:** `ssrn-4873649-p116` · `machine-drafted-source-checked`

## 117. extractive summaries can surface decisive clauses, evidence, authorities, and quotations

**Location:** III.E. Strategy 5: Integration, printed pp. 587 (PDF pp. 39)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 587, that extractive summaries can surface decisive clauses, evidence, authorities, and quotations. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because direct anchors let judges inspect exact language without trusting an untraceable synthesis. It connects to extractive evidence, contract clauses, legal authorities, quotations, traceability, judicial review.

**Evidence anchor:** Printed page 587 (PDF page 39) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** extractive evidence; contract clauses; legal authorities; quotations; traceability; judicial review

**Record:** `ssrn-4873649-p117` · `machine-drafted-source-checked`

## 118. document Q&A changes legal research from keyword engineering to natural-language inquiry

**Location:** III.E. Strategy 5: Integration, printed pp. 587 (PDF pp. 39)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 587, that document Q&A changes legal research from keyword engineering to natural-language inquiry. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because judges can ask the substantive question they care about instead of guessing which search terms will expose the answer. It connects to document Q&A, natural-language search, keyword search, information retrieval, judicial inquiry, legal research.

**Evidence anchor:** Printed page 587 (PDF page 39) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** document Q&A; natural-language search; keyword search; information retrieval; judicial inquiry; legal research

**Record:** `ssrn-4873649-p118` · `machine-drafted-source-checked`

## 119. document Q&A can identify facts and issues across a filing with little user training

**Location:** III.E. Strategy 5: Integration, printed pp. 588 (PDF pp. 40)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 588, that document Q&A can identify facts and issues across a filing with little user training. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because plain-language interfaces reduce the expertise and time needed to navigate large records. It connects to plain-language interface, fact retrieval, issue spotting, record review, user training, court technology.

**Evidence anchor:** Printed page 588 (PDF page 40) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** plain-language interface; fact retrieval; issue spotting; record review; user training; court technology

**Record:** `ssrn-4873649-p119` · `machine-drafted-source-checked`

## 120. document Q&A is best understood as an earnest on-call attorney of middling ability

**Location:** III.E. Strategy 5: Integration, printed pp. 588 (PDF pp. 40)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 588, that document Q&A is best understood as an earnest on-call attorney of middling ability. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the analogy calibrates reliance by combining real usefulness with predictable limits. It connects to calibrated trust, attorney analogy, document Q&A, bounded competence, decision support, human oversight.

**Evidence anchor:** Printed page 588 (PDF page 40) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** calibrated trust; attorney analogy; document Q&A; bounded competence; decision support; human oversight

**Record:** `ssrn-4873649-p120` · `machine-drafted-source-checked`

## 121. LLMs may overstate confidence, degrade on long documents, and invite users to delegate judgment

**Location:** III.E. Strategy 5: Integration, printed pp. 588 (PDF pp. 40)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 588, that LLMs may overstate confidence, degrade on long documents, and invite users to delegate judgment. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because interface fluency can conceal uncertainty and tempt users beyond the tool's validated task boundary. It connects to overconfidence, long-context degradation, automation bias, task boundaries, hallucinations, AI literacy.

**Evidence anchor:** Printed page 588 (PDF page 40) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** overconfidence; long-context degradation; automation bias; task boundaries; hallucinations; AI literacy

**Record:** `ssrn-4873649-p121` · `machine-drafted-source-checked`

## 122. AI limitations are tool-management problems rather than categorical objections to use

**Location:** III.E. Strategy 5: Integration, printed pp. 589 (PDF pp. 41)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 589, that AI limitations are tool-management problems rather than categorical objections to use. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because judges already manage fallible clerks by allocating tasks, checking important work, and retaining responsibility. It connects to tool limitations, law clerks, quality assurance, task allocation, judicial responsibility, comparative institutions.

**Evidence anchor:** Printed page 589 (PDF page 41) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** tool limitations; law clerks; quality assurance; task allocation; judicial responsibility; comparative institutions

**Record:** `ssrn-4873649-p122` · `machine-drafted-source-checked`

## 123. important AI-provided facts should be verified against the underlying record

**Location:** III.E. Strategy 5: Integration, printed pp. 589 (PDF pp. 41)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 589, that important AI-provided facts should be verified against the underlying record. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because targeted checking preserves much of the attention benefit while preventing consequential reliance on hallucinations. It connects to verification, source record, hallucinations, material facts, attention allocation, quality control.

**Evidence anchor:** Printed page 589 (PDF page 41) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** verification; source record; hallucinations; material facts; attention allocation; quality control

**Record:** `ssrn-4873649-p123` · `machine-drafted-source-checked`

## 124. court AI requires confidentiality solutions because many models are hosted by commercial cloud providers

**Location:** III.E. Strategy 5: Integration, printed pp. 589 (PDF pp. 41)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 589, that court AI requires confidentiality solutions because many models are hosted by commercial cloud providers. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because judicial efficiency cannot justify exposing sealed or sensitive information to uncontrolled training or reuse. It connects to confidentiality, cloud models, data governance, sealed records, model training, court security.

**Evidence anchor:** Printed page 589 (PDF page 41) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** confidentiality; cloud models; data governance; sealed records; model training; court security

**Record:** `ssrn-4873649-p124` · `machine-drafted-source-checked`

## 125. on-premise hosting, secure clouds, licensing, encryption, and legal standards can mitigate privacy risk

**Location:** III.E. Strategy 5: Integration, printed pp. 590 (PDF pp. 42)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 590, that on-premise hosting, secure clouds, licensing, encryption, and legal standards can mitigate privacy risk. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because confidentiality concerns call for architecture and governance choices rather than a blanket rejection of AI. It connects to on-premise models, secure cloud, data licensing, encryption, privacy standards, enterprise AI.

**Evidence anchor:** Printed page 590 (PDF page 42) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** on-premise models; secure cloud; data licensing; encryption; privacy standards; enterprise AI

**Record:** `ssrn-4873649-p125` · `machine-drafted-source-checked`

## 126. generative interpretation can use language models as reproducible tools for ordinary-meaning analysis

**Location:** III.E. Strategy 5: Integration, printed pp. 590 (PDF pp. 42)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 590, that generative interpretation can use language models as reproducible tools for ordinary-meaning analysis. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because models encode linguistic patterns from far more text than any individual judge can read. It connects to generative interpretation, ordinary meaning, language models, reproducibility, textualism, linguistic evidence.

**Evidence anchor:** Printed page 590 (PDF page 42) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** generative interpretation; ordinary meaning; language models; reproducibility; textualism; linguistic evidence

**Record:** `ssrn-4873649-p126` · `machine-drafted-source-checked`

## 127. LLMs can distinguish context-dependent meanings that dictionaries present as disconnected definitions

**Location:** III.E. Strategy 5: Integration, printed pp. 590 (PDF pp. 42)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 590, that LLMs can distinguish context-dependent meanings that dictionaries present as disconnected definitions. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because contextual probability offers a more realistic account of usage than treating every dictionary sense as equally plausible. It connects to contextual meaning, dictionaries, polysemy, ordinary usage, language representation, legal interpretation.

**Evidence anchor:** Printed page 590 (PDF page 42) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** contextual meaning; dictionaries; polysemy; ordinary usage; language representation; legal interpretation

**Record:** `ssrn-4873649-p127` · `machine-drafted-source-checked`

## 128. AI opinion drafting can threaten deliberation, authorship, rhetoric, and public legitimacy

**Location:** III.E. Strategy 5: Integration, printed pp. 591 (PDF pp. 43)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 591, that AI opinion drafting can threaten deliberation, authorship, rhetoric, and public legitimacy. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because efficiency gains may alter the judicial role and how audiences perceive the authenticity of reasons. It connects to judicial authorship, deliberation, opinion drafting, legitimacy, rhetoric, automation.

**Evidence anchor:** Printed page 591 (PDF page 43) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** judicial authorship; deliberation; opinion drafting; legitimacy; rhetoric; automation

**Record:** `ssrn-4873649-p128` · `machine-drafted-source-checked`

## 129. the force of authorship objections varies along a spectrum from spell-checking to robo-judging

**Location:** III.E. Strategy 5: Integration, printed pp. 591 (PDF pp. 43)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 591, that the force of authorship objections varies along a spectrum from spell-checking to robo-judging. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because many assistive tasks are remote from outsourcing adjudication and can remain net beneficial. It connects to automation spectrum, spell-check, robo-judging, assistive AI, proportionality, judicial role.

**Evidence anchor:** Printed page 591 (PDF page 43) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** automation spectrum; spell-check; robo-judging; assistive AI; proportionality; judicial role

**Record:** `ssrn-4873649-p129` · `machine-drafted-source-checked`

## 130. the practical choice may be between intelligent assistance and blind doctrinal algorithms rather than between algorithms and no algorithms

**Location:** III.E. Strategy 5: Integration, printed pp. 591 (PDF pp. 43)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 591, that the practical choice may be between intelligent assistance and blind doctrinal algorithms rather than between algorithms and no algorithms. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because rejecting court-side AI can push institutions toward mechanical rules that ration claims without regard to merit. It connects to comparative algorithms, mechanical rules, intelligent assistance, claim rationing, institutional choice, legal thermostats.

**Evidence anchor:** Printed page 591 (PDF page 43) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** comparative algorithms; mechanical rules; intelligent assistance; claim rationing; institutional choice; legal thermostats

**Record:** `ssrn-4873649-p130` · `machine-drafted-source-checked`

## 131. fee increases and rights restrictions are blind algorithms that exclude litigants regardless of merit

**Location:** III.E. Strategy 5: Integration, printed pp. 592 (PDF pp. 44)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 592, that fee increases and rights restrictions are blind algorithms that exclude litigants regardless of merit. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because traditional thermostats automate rationing through rigid proxies such as money, timing, and pleading polish. It connects to blind algorithms, fees, rights restrictions, merit blindness, procedural proxies, access inequality.

**Evidence anchor:** Printed page 592 (PDF page 44) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** blind algorithms; fees; rights restrictions; merit blindness; procedural proxies; access inequality

**Record:** `ssrn-4873649-p131` · `machine-drafted-source-checked`

## 132. thoughtful AI integration can outperform mechanical and politically manipulated thermostat adjustments

**Location:** III.E. Strategy 5: Integration, printed pp. 592 (PDF pp. 44)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 592, that thoughtful AI integration can outperform mechanical and politically manipulated thermostat adjustments. The discussion places this proposition within III.E. Strategy 5: Integration and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because validated tools can expand processing capacity while remaining reviewable by accountable judges. It connects to thoughtful integration, politicization, judicial review, capacity expansion, accountability, algorithmic governance.

**Evidence anchor:** Printed page 592 (PDF page 44) develops this proposition in III.E. Strategy 5: Integration.

**Boundary:** Integration is conditional on testing, confidentiality safeguards, task selection, verification, and continued human responsibility for adjudication.

**Connections:** thoughtful integration; politicization; judicial review; capacity expansion; accountability; algorithmic governance

**Record:** `ssrn-4873649-p132` · `machine-drafted-source-checked`

## 133. access to justice is only a prelude to the delivery of justice

**Location:** IV. Conclusion, printed pp. 592 (PDF pp. 44)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 592, that access to justice is only a prelude to the delivery of justice. The discussion places this proposition within IV. Conclusion and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because reducing entry barriers does not guarantee timely, careful, or rights-preserving adjudication. It connects to access versus delivery, procedural justice, substantive justice, court capacity, litigation boom, institutional design.

**Evidence anchor:** Printed page 592 (PDF page 44) develops this proposition in IV. Conclusion.

**Boundary:** The conclusion states a forward-looking institutional choice rather than claiming that any particular AI deployment is presently safe or effective without validation.

**Connections:** access versus delivery; procedural justice; substantive justice; court capacity; litigation boom; institutional design

**Record:** `ssrn-4873649-p133` · `machine-drafted-source-checked`

## 134. historical responses to litigation surges warn that new demand can produce contraction of procedural and substantive rights

**Location:** IV. Conclusion, printed pp. 593 (PDF pp. 45)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 593, that historical responses to litigation surges warn that new demand can produce contraction of procedural and substantive rights. The discussion places this proposition within IV. Conclusion and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because the Prison Litigation Reform Act illustrates how capacity pressure can be converted into durable exclusion. It connects to historical analogy, PLRA, rights contraction, litigation surges, institutional response, access barriers.

**Evidence anchor:** Printed page 593 (PDF page 45) develops this proposition in IV. Conclusion.

**Boundary:** The conclusion states a forward-looking institutional choice rather than claiming that any particular AI deployment is presently safe or effective without validation.

**Connections:** historical analogy; PLRA; rights contraction; litigation surges; institutional response; access barriers

**Record:** `ssrn-4873649-p134` · `machine-drafted-source-checked`

## 135. legal scholars should collaborate with judges, administrators, and technologists on positive court-AI use cases

**Location:** IV. Conclusion, printed pp. 593 (PDF pp. 45)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 593, that legal scholars should collaborate with judges, administrators, and technologists on positive court-AI use cases. The discussion places this proposition within IV. Conclusion and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because law must move from cataloging algorithmic harms to building tools whose limitations are understood and governed. It connects to tool-building scholarship, interdisciplinary collaboration, judges, technologists, responsible AI, legal academia.

**Evidence anchor:** Printed page 593 (PDF page 45) develops this proposition in IV. Conclusion.

**Boundary:** The conclusion states a forward-looking institutional choice rather than claiming that any particular AI deployment is presently safe or effective without validation.

**Connections:** tool-building scholarship; interdisciplinary collaboration; judges; technologists; responsible AI; legal academia

**Record:** `ssrn-4873649-p135` · `machine-drafted-source-checked`

## 136. judicial economy ultimately requires choosing how much justice to fund and whether automation should stretch those resources

**Location:** IV. Conclusion, printed pp. 593 (PDF pp. 45)

Professor Yonathan Arbel claims, in the article “Judicial Economy in the Age of AI” on page 593, that judicial economy ultimately requires choosing how much justice to fund and whether automation should stretch those resources. The discussion places this proposition within IV. Conclusion and ties the immediate point to the paper's broader distinction between opening access and preserving the institutional capacity to deliver justice. This is significant because AI policy cannot avoid the political allocation of adjudicative capacity; it can only change how effectively that capacity is used. It connects to judicial economy, public funding, automation, resource allocation, justice policy, institutional capacity.

**Evidence anchor:** Printed page 593 (PDF page 45) develops this proposition in IV. Conclusion.

**Boundary:** The conclusion states a forward-looking institutional choice rather than claiming that any particular AI deployment is presently safe or effective without validation.

**Connections:** judicial economy; public funding; automation; resource allocation; justice policy; institutional capacity

**Record:** `ssrn-4873649-p136` · `machine-drafted-source-checked`