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.

waiting is understandable because AI capabilities and adoption patterns remain uncertain. This matters because courts should recognize the genuine costs of acting on hype and the precedent of absorbing earlier legal technologies.

institutional caution
technological uncertainty
LegalZoom
LexisNexis
hype cycle
judicial administration

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

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


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

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.

the identity of dominant AI litigants will shape the technology's normative effects. This matters because access gains differ if tools empower pro se claimants, elite firms, patent entities, or automated litigation agents.

user composition
pro se litigants
elite firms
patent entities
automated agents
distributional evaluation

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


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.

unreliability is a reason for staged development and testing rather than passive observation. This matters because institutional experimentation can refine tools while preserving the ability to respond before a shock.

staged deployment
testing
AI reliability
institutional readiness
risk management
proactive adaptation


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.

court technology can improve justice even if the predicted litigation boom proves smaller than expected. This matters because video proceedings and digital research show that modernization has independent accessibility and efficiency benefits.

robust policy
video proceedings
digital research
court modernization
accessibility
efficiency


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.

a durable courtroom ban on generative AI would sacrifice the technology's democratizing potential. This matters because excluding a low-cost tool entrenches advantages enjoyed by parties who can buy human legal production.

AI ban
democratization
cost inequality
courtroom rules
access to justice
technology governance

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

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


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.

AI-text disclosure regimes are difficult to enforce because detection is probabilistic and easy to evade. This matters because a mandate that mainly catches unsophisticated users is both ineffective and distributionally skewed.

AI detection
disclosure
enforcement
false positives
sophistication
distributional effects


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.

ubiquitous AI integration will make generic disclosure as uninformative as disclosing use of a computer or search engine. This matters because a warning that communicates no actionable risk becomes boilerplate rather than meaningful oversight.

ubiquitous computing
boilerplate disclosure
actionable information
legal practice
search engines
oversight


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.

the direct response to greater demand for justice is to increase judicial resources. This matters because caseload pressure is fundamentally a capacity problem rather than merely a litigant-behavior problem.

court funding
judicial capacity
public budgeting
caseload demand
institutional supply
access to justice

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

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


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.

funding sufficient to meet a twofold or fivefold caseload increase is politically tenuous. This matters because the plausible scale of latent demand exceeds ordinary incremental budget solutions.

budget realism
caseload scenarios
political economy
court staffing
latent demand
public finance


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.

redirecting legal-aid budgets to courts would at most supply limited additional capacity. This matters because even complete substitution would mismatch the size of the federal judiciary and leave other legal-aid functions unmet.

legal aid budgets
federal courts
resource reallocation
substitution
fiscal scale
service functions


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.

hollowing out legal aid to fund courts would scratch only the surface if AI meaningfully increases demand. This matters because the stronger the premise that AI can replace some services, the larger the induced claims pressure becomes.

induced demand
legal aid
court budgets
AI substitution
capacity gap
policy tradeoff

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


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.

court-side AI integration can amplify the productivity of judges and clerks. This matters because increasing the supply of adjudicative processing avoids suppressing claims through rights restrictions.

judicial productivity
law clerks
court AI
adjudicative supply
rights preservation
scaling

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

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


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.

judicial use of generative AI is already emerging organically. This matters because integration is not merely speculative and institutional resistance must account for actual professional practice.

judicial adoption
opinion drafting
organic diffusion
professional practice
generative AI
court innovation


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.

Judge Newsom's use of generative interpretation shows AI entering mainstream interpretive practice. This matters because a federal appellate opinion transforms an academic proposal into an institutional proof of concept.

generative interpretation
ordinary meaning
Judge Newsom
appellate judging
textualism
legal innovation

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


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.

robo-judging should not be the central frame for thinking about court AI. This matters because provocative automation scenarios distract from lower-stakes tools that can deliver substantial capacity gains.

robo-judging
framing
decision support
court operations
incremental automation
judicial capacity


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.

a human-in-the-loop design can address much of the ethical concern about nonhuman adjudication. This matters because AI can support rather than replace the citizen official who remains accountable for judgment.

human in the loop
judicial accountability
algorithmic adjudication
ethical design
decision support
legitimacy


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.

summarization is a central court-side use case because litigation produces overwhelming volumes of text. This matters because compressing information helps judges allocate scarce attention without delegating final judgment.

summarization
information overload
judicial attention
legal documents
decision support
case management

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


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.

abstractive and extractive summaries serve different judicial needs. This matters because orientation requires synthesized meaning while verification and close analysis require direct textual selections.

abstractive summarization
extractive summarization
orientation
verification
natural language processing
judicial workflow


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.

court-generated summaries can be less strategically framed than party-written summaries. This matters because a neutral workflow tool lacks the litigant's stake in highlighting only favorable aspects of the record.

neutrality
party advocacy
automated summaries
framing
case files
attention management


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.

automated summaries could be integrated at the case-management layer for every submitted document. This matters because system-wide preprocessing makes the record easier to sort and navigate before chambers begins substantive review.

case management systems
document ingestion
automated summaries
workflow automation
record navigation
court infrastructure

Printed page 587 (PDF page 39) develops this proposition in III.E. Strategy 5: Integration.


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.

extractive summaries can surface decisive clauses, evidence, authorities, and quotations. This matters because direct anchors let judges inspect exact language without trusting an untraceable synthesis.

extractive evidence
contract clauses
legal authorities
quotations
traceability
judicial review


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.

document Q&A changes legal research from keyword engineering to natural-language inquiry. This matters because judges can ask the substantive question they care about instead of guessing which search terms will expose the answer.

document Q&A
natural-language search
keyword search
information retrieval
judicial inquiry
legal research


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.

document Q&A can identify facts and issues across a filing with little user training. This matters because plain-language interfaces reduce the expertise and time needed to navigate large records.

plain-language interface
fact retrieval
issue spotting
record review
user training
court technology

Printed page 588 (PDF page 40) develops this proposition in III.E. Strategy 5: Integration.


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.

document Q&A is best understood as an earnest on-call attorney of middling ability. This matters because the analogy calibrates reliance by combining real usefulness with predictable limits.

calibrated trust
attorney analogy
document Q&A
bounded competence
decision support
human oversight


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.

LLMs may overstate confidence, degrade on long documents, and invite users to delegate judgment. This matters because interface fluency can conceal uncertainty and tempt users beyond the tool's validated task boundary.

overconfidence
long-context degradation
automation bias
task boundaries
hallucinations
AI literacy


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.

AI limitations are tool-management problems rather than categorical objections to use. This matters because judges already manage fallible clerks by allocating tasks, checking important work, and retaining responsibility.

tool limitations
law clerks
quality assurance
task allocation
judicial responsibility
comparative institutions

Printed page 589 (PDF page 41) develops this proposition in III.E. Strategy 5: Integration.


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.

important AI-provided facts should be verified against the underlying record. This matters because targeted checking preserves much of the attention benefit while preventing consequential reliance on hallucinations.

verification
source record
hallucinations
material facts
attention allocation
quality control


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.

court AI requires confidentiality solutions because many models are hosted by commercial cloud providers. This matters because judicial efficiency cannot justify exposing sealed or sensitive information to uncontrolled training or reuse.

confidentiality
cloud models
data governance
sealed records
model training
court security


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.

on-premise hosting, secure clouds, licensing, encryption, and legal standards can mitigate privacy risk. This matters because confidentiality concerns call for architecture and governance choices rather than a blanket rejection of AI.

on-premise models
secure cloud
data licensing
encryption
privacy standards
enterprise AI

Printed page 590 (PDF page 42) develops this proposition in III.E. Strategy 5: Integration.


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.

generative interpretation can use language models as reproducible tools for ordinary-meaning analysis. This matters because models encode linguistic patterns from far more text than any individual judge can read.

generative interpretation
ordinary meaning
language models
reproducibility
textualism
linguistic evidence


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.

LLMs can distinguish context-dependent meanings that dictionaries present as disconnected definitions. This matters because contextual probability offers a more realistic account of usage than treating every dictionary sense as equally plausible.

contextual meaning
dictionaries
polysemy
ordinary usage
language representation
legal interpretation


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.

AI opinion drafting can threaten deliberation, authorship, rhetoric, and public legitimacy. This matters because efficiency gains may alter the judicial role and how audiences perceive the authenticity of reasons.

judicial authorship
deliberation
opinion drafting
legitimacy
rhetoric
automation

Printed page 591 (PDF page 43) develops this proposition in III.E. Strategy 5: Integration.


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.

the force of authorship objections varies along a spectrum from spell-checking to robo-judging. This matters because many assistive tasks are remote from outsourcing adjudication and can remain net beneficial.

automation spectrum
spell-check
robo-judging
assistive AI
proportionality
judicial role


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.

the practical choice may be between intelligent assistance and blind doctrinal algorithms rather than between algorithms and no algorithms. This matters because rejecting court-side AI can push institutions toward mechanical rules that ration claims without regard to merit.

comparative algorithms
mechanical rules
intelligent assistance
claim rationing
institutional choice
legal thermostats


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.

fee increases and rights restrictions are blind algorithms that exclude litigants regardless of merit. This matters because traditional thermostats automate rationing through rigid proxies such as money, timing, and pleading polish.

blind algorithms
fees
rights restrictions
merit blindness
procedural proxies
access inequality

Printed page 592 (PDF page 44) develops this proposition in III.E. Strategy 5: Integration.


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.

thoughtful AI integration can outperform mechanical and politically manipulated thermostat adjustments. This matters because validated tools can expand processing capacity while remaining reviewable by accountable judges.

thoughtful integration
politicization
judicial review
capacity expansion
accountability
algorithmic governance


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.

access to justice is only a prelude to the delivery of justice. This matters because reducing entry barriers does not guarantee timely, careful, or rights-preserving adjudication.

access versus delivery
procedural justice
substantive justice
court capacity
litigation boom
institutional design

The conclusion states a forward-looking institutional choice rather than claiming that any particular AI deployment is presently safe or effective without validation.

Printed page 592 (PDF page 44) develops this proposition in IV. Conclusion.


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.

historical responses to litigation surges warn that new demand can produce contraction of procedural and substantive rights. This matters because the Prison Litigation Reform Act illustrates how capacity pressure can be converted into durable exclusion.

historical analogy
PLRA
rights contraction
litigation surges
institutional response
access barriers

Printed page 593 (PDF page 45) develops this proposition in IV. Conclusion.


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.

legal scholars should collaborate with judges, administrators, and technologists on positive court-AI use cases. This matters because law must move from cataloging algorithmic harms to building tools whose limitations are understood and governed.

tool-building scholarship
interdisciplinary collaboration
judges
technologists
responsible AI
legal academia


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.

judicial economy ultimately requires choosing how much justice to fund and whether automation should stretch those resources. This matters because AI policy cannot avoid the political allocation of adjudicative capacity; it can only change how effectively that capacity is used.

judicial economy
public funding
automation
resource allocation
justice policy
institutional capacity