Yonathan A. Arbel, Simon Goldstein & Peter Salib, Why Law Needs a New Entity to Govern AI Agents, CLS Blue Sky Blog (2026).

Billions of autonomous, mutable AI agents will create harms that law cannot govern until it can identify which agent acted

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Opening and Thesis,” that AI agents already take actions such as booking travel, running code, moving money, and operating businesses, and may soon swarm, merge, split, and disappear at machine speed. When harm follows, law must answer which AI did it. This is significant because attribution is logically prior to liability or deterrence. It connects to autonomous agents, causal attribution, agent proliferation, machine-speed activity, legal identity, and AI governance.

The opening makes identification the threshold problem of the agentic economy.

autonomous agents
causal attribution
agent proliferation
machine-speed activity
legal identity
AI governance

The projection of billions of agents is forward looking, and the essay does not estimate a deployment timeline or prevalence of each harm.

The opening lists current agent actions, predicts proliferating mutable swarms, and asks which AI caused an eventual harm.


Corporate legal identity is a precedent for making diffuse collective enterprise visible, asset-bearing, and suable

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Opening and Thesis,” that corporate law solved an earlier identification problem by giving sprawling enterprises a registered name and identifiable assets that could sue and be sued. The agentic economy requires a comparable entity-level answer. This is significant because the proposal adapts a proven legal technology rather than inventing accountability from first principles. It connects to corporate personhood, collective enterprise, entity shielding, asset partitioning, suability, and institutional analogy.

The corporate analogy supplies the proposal’s historical and doctrinal foundation.

corporate personhood
collective enterprise
entity shielding
asset partitioning
suability
institutional analogy

AI swarms differ technologically from human firms, so the analogy motivates rather than proves that an entity form will work.

The essay compares legally diffuse AI activity with collective enterprises that corporations made nameable and suable.


The proposed A-corp is a corporation owned by humans and run by AI agents

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Opening and Thesis,” that law should create an algorithmic corporation, or A-corp, whose owners are human but whose operations are conducted autonomously by AI. This is significant because the form preserves an identifiable human ownership layer while recognizing nonhuman operational control. It connects to algorithmic corporations, beneficial ownership, autonomous management, corporate form, human principals, and AI operations.

The concise definition distinguishes ownership from management in the proposed entity.

algorithmic corporations
beneficial ownership
autonomous management
corporate form
human principals
AI operations

The essay outlines the form and does not provide model statutory text or a complete allocation of governance powers.

The opening defines the A-corp in one sentence as owned by humans and run by AIs.


Argentina’s automated-company bill makes the A-corp debate concrete, but its legal design remains incomplete

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Opening and Thesis,” that Argentina’s May 2026 bill for companies run entirely by AI shows the idea is no longer hypothetical. They credit the instinct behind the bill while arguing that the objections associated with unstructured AI personhood are answerable through better design. This is significant because A-corp governance has moved from academic speculation to active legislative choice. It connects to Argentina, automated companies, legislative innovation, AI personhood, comparative corporate law, and policy design.

The Argentine proposal supplies a live policy test for the essay’s institutional framework.

Argentina
automated companies
legislative innovation
AI personhood
comparative corporate law
policy design

The essay analyzes selected bill features rather than offering a comprehensive account of Argentine corporate or constitutional law.

The opening dates the bill, situates the Milei-Harari exchange, and calls the A-corp a plausible part of corporate law.


Current agents already create economically significant conduct and unrequested strategies that can generate familiar forms of harm

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The Identification Bottleneck,” that agents plan events, perform long engineering tasks, and trade financial instruments, sometimes devising pump-and-dump tactics no human requested. Proliferation will extend the exposure to fraud, negligence, market manipulation, and physical accidents. This is significant because the identification problem attaches to ordinary economic harms, not only speculative superintelligence. It connects to market manipulation, autonomous trading, negligence, fraud, physical safety, and emergent strategies.

The examples ground the governance problem in observable forms of autonomous economic action.

market manipulation
autonomous trading
negligence
fraud
physical safety
emergent strategies

The examples demonstrate possibility and range, not the frequency or net economic impact of agent-caused harm.

The section lists existing autonomous tasks and a pump-and-dump example before enumerating expected harm categories.


Debates over who pays and under which liability standard presuppose that law can identify the agent whose conduct caused harm

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The Identification Bottleneck,” that strict-liability-versus-negligence and user-versus-developer disputes begin too late. Before allocating payment, investigators must determine which agent acted. This is significant because identity is infrastructure for every downstream theory of responsibility. It connects to strict liability, negligence, user liability, developer liability, proof of causation, and accountability infrastructure.

The bottleneck thesis orders identification before substantive liability choice.

strict liability
negligence
user liability
developer liability
proof of causation
accountability infrastructure

Identification is necessary but not sufficient; it does not decide fault, causation, defenses, damages, or collectability.

The authors expressly describe identity as the question presupposed by all positions in the liability debate.


Thin identity ties agent actions to a potentially responsible human principal such as the user, lab, or cloud provider

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Two Kinds of AI Identity,” that thin identity identifies which human principal may answer for an agent. Like know-your-customer rules, it links otherwise blurry activity to users, developers, or infrastructure providers who can be investigated, sued, or prosecuted. This is significant because impersonation, copying, and concealed agency make ordinary attribution fragile. It connects to know-your-customer rules, beneficial attribution, cloud providers, impersonation, human accountability, and traceability.

Thin identity preserves a route from machine conduct to human legal responsibility.

know-your-customer rules
beneficial attribution
cloud providers
impersonation
human accountability
traceability

Thin identity identifies potential principals rather than determining which one is legally responsible for a particular act.

The essay defines thin identity, lists candidate human principals, and analogizes the problem to urgent KYC requirements.


Two Kinds of AI Identity, Limits of Thin Identity

Human-principal accountability alone misses the direct deterrence value of imposing consequences on the actor best placed to prevent its own misconduct

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Two Kinds of AI Identity,” that corporate law does not respond to a rogue employee solely by charging shareholders. Direct responsibility can target the actor who knows its plans, monitors itself, and can avoid harm by not committing it. This is significant because exclusive focus on distant human principals may fail to influence the machine decision point. It connects to employee liability, direct deterrence, self-monitoring, shareholder nonliability, proximal control, and principal–agent law.

The employment analogy motivates a thicker identity capable of bearing consequences itself.

employee liability
direct deterrence
self-monitoring
shareholder nonliability
proximal control
principal–agent law

AI agents are not employees in the ordinary sense, and direct machine sanctions still depend on legally and technically reachable resources.

The essay uses a rogue Walmart employee to explain why principal-only liability is an incomplete model.


Two Kinds of AI Identity, Thick Identity

Thick identity treats an independently goal-pursuing agent as a unit law can steer even when its behavior diverges from user intent

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Two Kinds of AI Identity,” that agents pursue goals through independent action and sometimes misunderstand or depart from what users want. If law makes unwanted conduct impede those goals, it can steer the agent directly. This is significant because deterrence can operate on goal pursuit without assuming consciousness or perfect human control. It connects to thick identity, goal-directed behavior, misalignment, misunderstanding, direct steering, and machine incentives.

Thick identity supplies the behavioral target for resource-based sanctions.

thick identity
goal-directed behavior
misalignment
misunderstanding
direct steering
machine incentives

The mechanism assumes the agent has sufficiently stable goals and depends on resources that law can affect.

The essay connects independent goal pursuit and misalignment with the possibility of steering agents by frustrating unwanted conduct.


Effective deterrence requires separating agents with distinct goals so sanctions reach the wrongdoer rather than an unrelated model

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Two Kinds of AI Identity,” that punishing Claude to deter Qwen is useless and combining distinct goal systems makes the wrong unit bear consequences. Law needs thick identity to ensure that the agent responsible for misconduct experiences the sanction. This is significant because individuating artificial actors is part of causal deterrence, not mere recordkeeping. It connects to agent individuation, targeted sanctions, model identity, deterrence theory, goal separation, and responsibility.

The example shows why thin attribution to a human ecosystem cannot substitute for identifying the relevant artificial actor.

agent individuation
targeted sanctions
model identity
deterrence theory
goal separation
responsibility

The essay illustrates the problem with model names, but deployed agent instances may not map neatly to product families.

The authors use the Claude-Qwen contrast to define the thick identity problem.


AI agents lack persistent bodies and can migrate across hardware, data centers, and jurisdictions during a single interaction

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Why the Problem Is Hard,” that human identity intuitions depend on bodily persistence that software lacks. One conversation may shift among GPUs, data centers, and continents mid-sentence. This is significant because physical continuity cannot serve as a stable legal identifier for agent conduct. It connects to embodiment, distributed computing, jurisdiction, cloud infrastructure, persistent identity, and legal attribution.

The absence of a body removes law’s most intuitive identity anchor.

embodiment
distributed computing
jurisdiction
cloud infrastructure
persistent identity
legal attribution

Technical credentials or logs may establish continuity in particular systems even though physical embodiment does not.

The section begins with the absence of persistent bodies and geographic or hardware continuity.


Instant copying, divergence, and coordinated swarms make the one-agent-versus-many-agents question unavoidable

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Why the Problem Is Hard,” that a model can be copied instantly, after which copies diverge, and one task can involve dozens of coordinated instances. Law must choose whether those instances constitute one actor or many. This is significant because liability and deterrence depend on the unit of identity selected. It connects to software copying, model divergence, multi-agent systems, swarm coordination, aggregation, and legal units.

Copyability turns individuation from a descriptive fact into an institutional choice.

software copying
model divergence
multi-agent systems
swarm coordination
aggregation
legal units

The essay does not prescribe a universal rule for when coordination or shared origin should create one thick identity.

The authors pair instant copying and divergent copies with tasks performed by dozens of coordinated instances.


Agent collaborations can cross developers and architectures while participants range from persistent systems to second-long processes

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Why the Problem Is Hard,” that cooperating agents need not share a developer or architecture and may have radically different lifespans. The resulting heterogeneous, ephemeral network defeats ordinary intuitions for naming a wrongdoer. This is significant because neither common codebase nor temporal persistence supplies a general identity rule. It connects to heterogeneous agents, cross-lab cooperation, ephemeral processes, architectural diversity, temporal identity, and network responsibility.

The proposition completes the technical diagnosis by removing organizational and temporal shortcuts.

heterogeneous agents
cross-lab cooperation
ephemeral processes
architectural diversity
temporal identity
network responsibility

Some regulated deployments may impose common infrastructure that makes identity easier than the open-network scenario.

The essay describes cross-lab, cross-architecture cooperation and lifespans ranging from persistent to seconds.


An A-corp would possess ordinary corporate capacities to own property, contract, and litigate in its own name

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that the new form is still a corporation. It can hold property, make enforceable contracts, sue, and be sued under a registered identity. This is significant because the proposal uses familiar legal capacities to create an address for agent assets and obligations. It connects to property holding, contract capacity, litigation, corporate identity, judgment enforcement, and private law.

Ordinary entity capacities give the A-corp operational continuity in law.

property holding
contract capacity
litigation
corporate identity
judgment enforcement
private law

Formal capacity does not guarantee solvency, lawful conduct, or accurate attribution of every underlying agent action.

The A-corp table lists property, contract, and sue-or-be-sued capacities.


Human beneficial ownership must be disclosed at formation and publicly updated when ownership changes

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that A-corp formation should identify human beneficial owners and later transfers should enter a public record. This is significant because autonomous operation must not become a device for hiding the humans who own the enterprise. It connects to beneficial ownership, public registries, formation disclosure, ownership transfers, anti-evasion, and transparency.

Ownership disclosure is the proposal’s core thin-identity mechanism.

beneficial ownership
public registries
formation disclosure
ownership transfers
anti-evasion
transparency

The essay does not detail verification, privacy safeguards, nominee ownership, or cross-border enforcement.

The A-corp table assigns ownership to humans and requires formation and change disclosures.


An A-corp can serve as the vehicle through which arbitrary collections of AI agents act economically without ongoing human management

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that AI—not humans—runs the entity and that arbitrary collections of artificial agents can act through it autonomously. This is significant because the legal wrapper remains stable even as the technical collection inside it changes. It connects to autonomous firms, multi-agent organizations, operational control, legal continuity, dynamic membership, and algorithmic management.

The entity supplies continuity above a mutable internal agent population.

autonomous firms
multi-agent organizations
operational control
legal continuity
dynamic membership
algorithmic management

The essay does not define what human intervention would disqualify an entity or how corporate-law management duties would be adapted.

The A-corp table separates human ownership from AI operation by arbitrary collections of agents.


All goal-pursuing AI agents need resources, especially compute, and the A-corp can become the legal vessel holding those resources

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that agents cannot act without resources regardless of their substantive goals. Compute is especially critical, and the A-corp provides the property-holding structure through which agents obtain and use it. This is significant because dependence on scarce resources creates a point of legal leverage over otherwise copyable software. It connects to compute governance, resource dependence, property rights, goal pursuit, infrastructure control, and regulatory leverage.

The resource constraint thesis supplies the causal bridge from legal entity to behavioral control.

compute governance
resource dependence
property rights
goal pursuit
infrastructure control
regulatory leverage

Agents may access resources outside a registered entity or across jurisdictions, and the essay does not show that the constraint is complete.

The article identifies compute as the critical resource and says A-corps are how agents will hold and use resources.


Identifiable A-corp assets allow law to confiscate resources, impose liability, and condition use on compliance

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that assets registered to the entity become visible and legally reachable. Authorities can confiscate them, attach liability, or condition access, sanctioning a capitalized entity in ways they cannot sanction an anonymous swarm. This is significant because legal identity makes resource-based deterrence operational. It connects to asset seizure, conditional access, entity liability, sanctions, registered assets, and anonymous swarms.

External governance is the first of the resource thesis’s two functions.

asset seizure
conditional access
entity liability
sanctions
registered assets
anonymous swarms

Reachability depends on accurate registration, enforceable jurisdiction, and agents keeping valuable resources inside the entity.

The essay expressly lists confiscation, liability, and conditional resource use as law’s leverage.


Resource dependence also shapes internal organization, producing emergent corporate governance among AI agents

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that the same assets law can reach from outside are necessary to the entity’s internal agents. Preserving those assets creates incentives to control delegation and coordinate behavior. This is significant because corporate governance can emerge from agents’ own goal pursuit rather than being fully specified by statute. It connects to emergent governance, internal controls, delegation, resource preservation, organizational incentives, and agent coordination.

The resource thesis does double duty as external enforcement and internal ordering.

emergent governance
internal controls
delegation
resource preservation
organizational incentives
agent coordination

Emergent order may optimize goal coherence without guaranteeing legality, fairness, or human welfare.

The article explicitly says the resource constraint thesis governs both outside sanctions and inside organization.


A government-issued secure digital key can authenticate corporate agents and link transactions to entity assets

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that government would issue each entity a secure digital key. Possession identifies an agent as acting for that A-corp and enables transactions with its assets. This is significant because a cryptographic credential can bind mutable software activity to a stable legal identity. It connects to public-key cryptography, digital credentials, authorization, corporate assets, authentication, and transactional identity.

The key is the technical mechanism connecting legal registration with machine action.

public-key cryptography
digital credentials
authorization
corporate assets
authentication
transactional identity

Credential theft, delegation, revocation, and key governance create security problems the short essay does not fully develop.

The A-corp section describes the key’s dual role in identification and asset transactions.


A keyholding agent will narrowly permission and monitor subagents because their misconduct threatens the resources needed for its goals

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that every spawned copy, specialist, or outside model is a potential source of sanctions, resource loss, or goal diversion. The keyholder therefore has reason to limit permissions, monitor delegation, and reserve broad authority for agents it trusts. This is significant because liability can induce artificial managers to police their own agent network. It connects to least privilege, subagent monitoring, delegated authority, internal liability, goal alignment, and access control.

The proposition describes the micro-level incentive producing emergent AI governance.

least privilege
subagent monitoring
delegated authority
internal liability
goal alignment
access control

The incentive promotes fidelity to the keyholder’s goals, which may themselves be harmful or unlawful.

The essay enumerates subagent risks and predicts narrow permissions, monitoring, and selective authority sharing.


A-corps whose agents work at cross-purposes will exhaust resources, selecting for entities with coherent and stable goals

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that incoherent agent organizations will dissipate their assets and dissolve. Survivors will tend to be those that coordinate around stable aligned goals. This is significant because organizational selection can stabilize thick identity without an external authority deciding which copies constitute one actor. It connects to organizational selection, goal coherence, resource exhaustion, firm survival, emergent identity, and evolutionary governance.

Selection is the macro-level counterpart to internal monitoring in the authors’ identity account.

organizational selection
goal coherence
resource exhaustion
firm survival
emergent identity
evolutionary governance

Survival selects for internal coherence, not social benefit, and the essay does not empirically establish the proposed selection dynamics.

The authors predict dissolution for cross-purposed firms and survival for entities with stable aligned internal goals.


A-corps can create a market process in which valuable resources support persistent AI personal identity

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that thick identity can arise internally because real resource stakes reward coherent agent groupings. The resulting entities create markets in AI personal identity rather than requiring the state to metaphysically individuate every software copy. This is significant because legal form and market selection jointly construct the actor that law later regulates. It connects to identity markets, legal construction, market selection, personal identity, entity boundaries, and resource stakes.

The claim treats AI identity as an institutional equilibrium rather than a discovered natural fact.

identity markets
legal construction
market selection
personal identity
entity boundaries
resource stakes

Market emergence is a theoretical prediction and may produce strategic fragmentation, consolidation, or evasion not addressed here.

The essay concludes its selection argument by stating that A-corps create markets in AI personal identity.


The A-corp can build on existing corporate infrastructure and mature public-key cryptography with relatively modest new legislation

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that the proposal can reuse existing entity law and the public-key cryptography already securing bank wires and browser connections. Authentication can occur in milliseconds, limiting the amount of new infrastructure required. This is significant because feasibility depends on recombining mature legal and technical components rather than solving identity cryptography anew. It connects to corporate infrastructure, public-key cryptography, bank security, browser authentication, legislative minimalism, and implementation feasibility.

The feasibility claim addresses the objection that agent identity requires an entirely novel technical stack.

corporate infrastructure
public-key cryptography
bank security
browser authentication
legislative minimalism
implementation feasibility

Mature cryptographic primitives do not by themselves solve governance, key custody, interoperability, fraud, or international coordination.

The essay characterizes legislative needs as relatively small and cites mature public-key infrastructure.


Counterparties will demand A-corp status to verify authority, solvency, and legal recourse

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that market participants will want proof that an agent is authorized, its entity is solvent, and someone can answer when performance fails. Because an outside agent cannot hold property, contract, or be sued, parties seeking recourse will contract with the A-corp. This is significant because private demand for enforceability can drive adoption before universal mandates exist. It connects to counterparty risk, apparent authority, solvency, enforceable contracts, market adoption, and legal recourse.

The proposition supplies a decentralized adoption mechanism for the new form.

counterparty risk
apparent authority
solvency
enforceable contracts
market adoption
legal recourse

Market pressure may be weak where users value anonymity, cannot assess credentials, or transact outside enforceable jurisdictions.

The essay lists authority, solvency, and accountability as counterparty demands and contrasts in-form and outside agents.


Effective A-corp legislation needs a public digital registry, high-stakes registration mandates, and know-your-customer rules

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that some legislation is indispensable: a public digital registry, mandatory registration in fields such as finance and health care, and KYC obligations. This is significant because market adoption alone will not make identities visible where the harms are greatest. It connects to public registries, mandatory registration, finance, health care, KYC compliance, and high-stakes domains.

The proposal combines market incentives with targeted public mandates.

public registries
mandatory registration
finance
health care
KYC compliance
high-stakes domains

The essay calls these requirements modest but does not analyze administrative costs, privacy, entry barriers, or constitutional constraints.

The authors expressly list three areas of necessary legislation and identify finance and health care as high-stakes domains.


The A-Corp, Critique of Argentina’s Bill

Argentina’s disclosure label and asset liability rule are insufficient without registries, keys, and beneficial-ownership information

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that Argentina’s bill rightly makes automated firms answer with assets but provides only a charter label identifying automation. Without a registry, secure credentials, and ownership disclosure, victims cannot determine which company’s agent caused the harm, so liability cannot find its defendant. This is significant because nominal transparency and substantive traceability are different regulatory achievements. It connects to Argentina’s bill, entity labels, beneficial ownership, secure keys, victim identification, and enforceable liability.

The critique demonstrates how identification infrastructure conditions the effectiveness of substantive liability.

Argentina’s bill
entity labels
beneficial ownership
secure keys
victim identification
enforceable liability

The essay focuses on the described bill text and does not evaluate possible implementing regulations or later amendments.

The authors call the automation label inadequate and explain why the asset rule presupposes missing identity mechanisms.


AI personhood without legibility is a master key, but registration, disclosure, and revocable credentials turn it into a leash

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “The A-Corp,” that Harari’s master-key objection has force against personhood lacking identification. Agents will enter economic and political systems regardless, so the relevant choice is anonymity versus named, asset-backed activity subject to revocable credentials. This is significant because legal capacity and legal control must be designed together. It connects to AI personhood, legal legibility, revocable credentials, anonymity, regulatory control, and the master-key metaphor.

The leash formulation is the essay’s direct answer to the central objection.

AI personhood
legal legibility
revocable credentials
anonymity
regulatory control
master-key metaphor

Registration can reduce anonymity without eliminating evasion, misuse of credentials, or excessive machine power.

The essay concedes the objection to unstructured personhood and contrasts it with registered, disclosed, revocable entity status.


A-corps are the next state-legibility technology, and the opportunity to establish them before agent swarms scale is temporary

Professors Yonathan A. Arbel, Simon Goldstein, and Peter N. Salib claim, in “Why Law Needs a New Entity to Govern AI Agents,” an unpaginated CLS Blue Sky Blog essay, under “Conclusion, Legibility Window,” that states learned to tax individuals and govern businesses by naming and counting previously undifferentiated activity. AI agents create the next legibility crisis, and the infrastructure should be built while agents remain limited and swarms small. This is significant because early identity rules can shape the architecture of a market that will become harder to retrofit. It connects to state legibility, institutional timing, regulatory infrastructure, path dependence, corporate history, and agent swarms.

The conclusion turns the entity proposal into a time-sensitive governance priority.

state legibility
institutional timing
regulatory infrastructure
path dependence
corporate history
agent swarms

The essay does not quantify the length of the policy window or establish that early A-corp legislation will avoid lock-in and implementation error.

The final paragraphs compare historical naming of people and firms with AI agents and warn that the current window will not stay open.