Perrin Institution has supported legislation in the Senate, the House and the New York State Legislature, with offices on both sides of the aisle.
Taken together they describe what the institution has argued for: public research infrastructure so that frontier AI is not studied only inside a few firms; warrants for data the government buys rather than compels; human review and appeal where automated systems decide things about people; rules for synthetic media, deepfakes and digital replicas; limits on AI in nuclear launch decisions; and transparency and incident reporting from the developers of the largest models. Each bill follows, with the offices we worked with, the problem it addresses and what it changes.
CREATE AI Act
S.2714 / H.R.5077, 118th; H.R.2385, 119th · Sen. Heinrich (D-NM); Rep. Eshoo (D-CA)
With Sens. Heinrich, Rounds, Young, Booker; Reps. Carter, Eshoo, McCaul
Frontier AI research has concentrated in a handful of firms because the compute, data and engineering needed to do it are out of reach for universities and small companies. This bill puts a shared research infrastructure in public hands. It authorises the National AI Research Resource, giving academic researchers, students and small businesses access to computing capacity, curated datasets and testing environments they cannot otherwise buy, and it puts the arrangement on a statutory footing rather than leaving it to the pilot the National Science Foundation stood up administratively.
- Authorises the National AI Research Resource as a shared national infrastructure for AI research and education.
- Directs the National Science Foundation to operate it through an independent entity, overseen by a steering subcommittee.
- Provides access to computational resources, curated public datasets, testbeds and training material.
- Opens eligibility to academic researchers, students, and small businesses rather than restricting it to federal use.
- Requires reporting to Congress on usage, governance and cost.
AI Bill of Rights & SAFE Innovation Framework
Executive and agency frameworks · OSTP; NIST; Sen. Majority Leader Schumer
With Sen. Majority Leader Schumer; OSTP; NIST
Two non-binding frameworks that set the terms much of the later legislation argued over. The Blueprint for an AI Bill of Rights, published by the Office of Science and Technology Policy in October 2022, states five principles for automated systems affecting the public. The SAFE Innovation Framework, announced by the Senate Majority Leader in June 2023, set an agenda for the Senate's AI Insight Forums. Neither creates an obligation on anyone; both are included here because the drafting work was real and because they shaped the bills that followed.
- AI Bill of Rights: systems should be safe and effective, and tested before deployment.
- AI Bill of Rights: protection from algorithmic discrimination, with proactive equity assessment.
- AI Bill of Rights: data privacy by design, with consent and limits on sensitive-data inference.
- AI Bill of Rights: notice that an automated system is in use, and a plain-language explanation of its role.
- AI Bill of Rights: a human alternative, and a route to a person who can consider and remedy problems.
- SAFE Innovation: security, accountability, foundations and explainability as the four organising demands.
ASSESS AI Act
S.1356, 118th · Sen. Bennet (D-CO)
With Sen. Bennet
Federal AI policy was being made agency by agency, with no body holding a view of the whole. This bill creates one. It stands up a cabinet-level task force to audit how the federal government itself uses AI, identify where existing law leaves gaps, and report recommendations back to Congress within a fixed window rather than as an open-ended study.
- Establishes an AI task force at cabinet level to review federal AI policy.
- Directs it to identify gaps in existing law covering rights, civil liberties and due process.
- Requires specific attention to facial recognition and biometric systems.
- Requires recommendations on data protection standards for federal AI use.
- Sets a reporting deadline to Congress rather than leaving the review open-ended.
Digital Platform Commission Act
S.1671, 118th · Sen. Bennet (D-CO)
With Sens. Bennet, Welch
Oversight of digital platforms is spread across agencies that regulate them incidentally, through competition or consumer-protection powers written before the platforms existed. This bill creates a dedicated expert regulator instead: a five-member commission with rulemaking, investigatory and enforcement authority over the platforms themselves, on the model of how communications and financial markets are supervised.
- Establishes a Federal Digital Platform Commission of five Senate-confirmed members.
- Grants rulemaking, investigatory, and enforcement authority over digital platforms.
- Creates a code council of technologists and civil-society experts to propose technical standards.
- Requires algorithmic risk auditing and transparency for platforms above a scale threshold.
- Preserves existing agency authority rather than displacing the FTC or DOJ.
Fourth Amendment Is Not For Sale Act
H.R.4639, 118th · Rep. Davidson (R-OH)
With Sens. Warren, Wyden, Paul; Rep. Davidson
Agencies had been buying from commercial data brokers the same records they would need a warrant to compel: location histories, subscriber records, and browsing data. The purchase was legal because the Fourth Amendment restrains compulsion, not commerce. This bill closes that gap directly, extending the warrant requirement to acquisition by purchase. It is the furthest any of this work was carried in the House: it passed on the floor 219 to 199, with 123 Republicans joining.
- Bars federal agencies from purchasing data they would otherwise need a warrant, court order or subpoena to obtain.
- Covers subscriber records, communications records, and location information.
- Extends to data obtained from a provider in violation of a contract or terms of service.
- Closes the intermediary route by covering data acquired through a third party rather than directly.
- Applies the restriction to law enforcement and intelligence agencies alike.
Digital Consumer Protection Commission Act
S.2597, 118th · Sen. Warren (D-MA)
With Sens. Warren, Graham
A bipartisan proposal to license and supervise large technology platforms through a single new regulator, rather than pursuing them case by case through antitrust litigation that takes a decade. The commission would hold authority across competition, privacy, transparency and national security, with licensing as the lever: a platform above the size threshold operates on conditions the regulator sets.
- Establishes a Digital Consumer Protection Commission with licensing authority over dominant platforms.
- Consolidates competition, privacy and transparency oversight in one body.
- Requires platforms to disclose algorithmic ranking and recommendation practices.
- Provides for national-security review of foreign ownership and data flows.
- Backs the regime with civil penalties and licence conditions rather than litigation alone.
Preventing Deepfakes of Intimate Images Act
H.R.3106, 118th; H.R.1941, 119th · Rep. Morelle (D-NY)
With Rep. Morelle
Synthetic intimate imagery of real people became cheap to produce years before there was a federal remedy for it. Victims were left to state law, which varied widely and often did not reach forged material at all, since nothing had been recorded. This bill creates a federal cause of action for disclosure of digitally forged intimate images, and lets plaintiffs proceed under a pseudonym so that suing does not itself republish the harm.
- Creates a federal civil cause of action for disclosure of non-consensual forged intimate images.
- Reaches digitally created and altered material, not only recorded images.
- Provides criminal penalties for disclosure with intent to harass, intimidate or cause distress.
- Permits plaintiffs to proceed pseudonymously and to seek injunctive relief.
- Preserves state-law remedies rather than pre-empting them.
Jobs of the Future Act of 2023
H.R.4498, 118th · Rep. Soto (D-FL)
With Reps. Blunt Rochester, Soto
Workforce policy was being argued from anecdote because nobody had measured what AI was actually doing to employment. This bill commissions the measurement: a joint Department of Labor and National Science Foundation study of which occupations, industries and demographic groups are being affected, and what training would answer it, reported to Congress on a fixed schedule.
- Directs the Department of Labor and the National Science Foundation to report jointly on AI's workforce impact.
- Requires analysis by occupation, industry, and demographic group.
- Requires assessment of which skills and training programmes are needed in response.
- Directs attention to workers displaced rather than only to jobs created.
- Sets a reporting deadline to the relevant congressional committees.
Artificial Intelligence Literacy Act of 2023
H.R.6791, 118th · Rep. Blunt Rochester (D-DE)
With Rep. Blunt Rochester
Rather than build a new programme, this bill folds AI literacy into the digital-literacy machinery that already exists. By naming AI literacy as a component of digital literacy under the Digital Equity Act, it makes AI education immediately eligible for established federal funding streams rather than waiting on a new authorisation.
- Defines AI literacy in statute as a component of digital literacy.
- Makes AI literacy programmes eligible under existing Digital Equity Act funding.
- Covers both general public understanding and workforce-directed instruction.
- Reaches libraries, schools, and community organisations already delivering digital-skills work.
- Avoids standing up a parallel programme with its own authorisation.
AI Training Expansion Act
H.R.4503, 118th · Rep. Mace (R-SC)
With Reps. Kilmer, Mace, Connolly
The federal government buys and deploys AI systems through officials who were never trained to evaluate them. This bill extends the existing federal AI training requirement to the managers and procurement staff who actually make those decisions, covering capabilities, risks, privacy exposure and bias. It was reported out of committee 39 to 2.
- Requires the Office of Management and Budget to establish an AI training programme for federal management officials.
- Extends coverage to procurement and acquisition staff who evaluate AI systems.
- Requires the curriculum to cover capabilities, limitations, and known failure modes.
- Requires specific instruction on privacy risk and bias in deployed systems.
- Directs periodic updating of the curriculum as the technology changes.
Political BIAS Emails Act
H.R.5495, 118th · Rep. Lesko (R-AZ)
With Rep. Lesko; prev. Sens. Kennedy, Thune
A narrow bill addressing a narrow complaint: that spam filters were suppressing campaign email from senders the recipient had chosen to hear from. It bars providers from applying filtering to political campaign email where the user has opted in, and requires disclosure of the filtering practices that apply.
- Bars email providers from spam-filtering political campaign email from opted-in senders.
- Applies only where the recipient has affirmatively subscribed.
- Requires providers to disclose their filtering practices for political mail.
- Preserves the recipient's ability to unsubscribe at any point.
- Assigns enforcement to the Federal Election Commission.
Algorithmic Justice and Online Platform Transparency Act
S.2325 / H.R.4624, 118th · Sen. Markey (D-MA); Rep. Matsui (D-CA)
With Rep. Matsui; Sen. Markey
Platforms rank, recommend and moderate through systems whose inputs are invisible to the people they affect, which makes discrimination through those systems very hard to prove. This bill attacks the evidentiary problem: it prohibits discriminatory algorithmic processes outright, then requires the disclosure and reporting that would let anyone establish a violation.
- Prohibits algorithmic processes that discriminate on the basis of protected characteristics.
- Requires platforms to disclose how personal information is used in ranking and recommendation.
- Mandates annual public transparency reports on content moderation and amplification.
- Establishes an interagency task force on discriminatory algorithmic practices.
- Provides for enforcement by the FTC and state attorneys general.
Digital Equity Foundation Act of 2023
S.599 / H.R.1412, 118th · Sen. Luján (D-NM)
With Sen. Luján
Federal digital-inclusion funding cannot easily accept or direct private money, which leaves broadband adoption and digital-skills work dependent on appropriation cycles. This bill establishes an independent nonprofit foundation that can take private contributions and direct them at adoption barriers in underserved communities, alongside the federal programmes rather than inside them.
- Establishes a nonprofit Digital Equity Foundation independent of the federal government.
- Authorises it to accept and direct private funding for digital-inclusion work.
- Targets adoption barriers rather than infrastructure deployment alone.
- Directs support to underserved and rural communities.
- Requires public reporting on grants and outcomes.
CLOUD AI Act
H.R.4683, 118th · Rep. Jeff Jackson (D-NC)
With Reps. Jackson, Lawler, Crockett, McCormick
Export controls on advanced chips restrict who may take possession of the hardware, but not who may rent time on it. An entity barred from buying a controlled chip could reach the same compute through a cloud provider. This bill closes that gap by extending the control from the hardware to remote access to it.
- Extends export-control restrictions to remote access to controlled computing hardware.
- Bars provision of covered cloud compute to entities in adversary nations.
- Requires providers to identify and verify customers reaching controlled capacity.
- Directs reporting on attempted circumvention.
- Aligns the cloud regime with the existing hardware control lists.
REAL Political Ads Act & Honest Ads Act
H.R.3044 / S.1596; S.486 / H.R.2599, 118th · Rep. Clarke (D-NY); Sen. Klobuchar (D-MN)
With Rep. Clarke; Sens. Klobuchar, Booker, Bennet, Graham, Warner
Two bills addressing the same asymmetry: political advertising online is governed by far weaker disclosure rules than the same advertising on broadcast. The Honest Ads Act extends broadcast-era disclaimer and recordkeeping duties to online platforms. The REAL Political Ads Act adds a requirement specific to synthetic media, that political advertising containing AI-generated content say so.
- Honest Ads: extends political-advertising disclaimer requirements to online platforms.
- Honest Ads: requires platforms to maintain a public file of political ad purchases.
- Honest Ads: applies to platforms above a monthly user threshold.
- REAL Political Ads: requires disclosure where a political advertisement contains AI-generated content.
- REAL Political Ads: assigns enforcement to the Federal Election Commission.
National AI Commission Act
H.R.4223, 118th · Rep. Lieu (D-CA)
With Sen. Peters; Reps. Lieu, Buck, Eshoo; Sen. Schatz
A bipartisan proposal to answer the structural question before legislating the substantive one: whether AI should be regulated by existing agencies under existing authorities, by a new body, or by some division of the two. It creates a twenty-member commission to review the current landscape and return a recommended risk-based framework on a fixed schedule.
- Establishes a twenty-member bipartisan National AI Commission.
- Directs a review of the current federal regulatory landscape for AI.
- Requires recommendations for a risk-based regulatory framework.
- Requires assessment of whether existing agencies or a new body should hold authority.
- Sets interim and final reporting deadlines to Congress.
Transparent Automated Governance Act
S.1865, 118th · Sen. Peters (D-MI)
With Sen. Peters
When a federal agency uses an automated system to decide a benefit, a claim or a status, the person on the other side frequently does not know a machine was involved and has no way to contest it. This bill makes the involvement disclosable and the decision appealable: notice that automation was used, and a route to human review.
- Directs OMB to issue guidance on agency use of automated decision systems.
- Requires agencies to notify people when an automated system is used in a decision affecting them.
- Requires a documented process for human review of automated decisions.
- Requires an appeal route to a person with authority to change the outcome.
- Requires agencies to inventory the automated systems they use.
AI LEAD Act
S.2293, 118th · Sen. Peters (D-MI)
With Sens. Peters, Cornyn
Federal AI accountability had no named owner inside agencies, so responsibility for a deployed system was distributed until it was nobody's. This bill assigns it: a Chief AI Officer in each agency, a council to coordinate them across government, and governance boards to review deployments rather than leaving them to individual programme offices.
- Establishes a Chief AI Officer in each covered federal agency.
- Creates a Chief AI Officers Council to coordinate practice across agencies.
- Requires agency AI governance boards to review deployments.
- Assigns responsibility for agency AI risk management to a named official.
- Requires reporting on agency AI use and governance to Congress.
AI Leadership Training Act
S.1564, 118th · Sen. Peters (D-MI)
With Sens. Peters, Braun
A companion to the accountability structure: the officials made responsible for AI decisions need to be trained for them. This bill directs the Office of Personnel Management to run an AI training programme for federal supervisors and managers, covering benefits, risks and governance duties. It was reported out of committee with a filed report, S.Rept. 118-109.
- Directs OPM to establish an AI training programme for federal supervisors and managers.
- Requires coverage of the risks and limitations of AI systems, not only their uses.
- Requires instruction on the governance duties attaching to deployment decisions.
- Requires periodic refresh as capabilities change.
- Requires reporting on participation and coverage.
Autonomous Artificial Intelligence Act
S.1394 / H.R.2894, 118th · Sen. Markey (D-MA); Rep. Lieu (D-CA)
With Sen. Markey; Reps. Lieu, Beyer, Buck
Introduced as the Block Nuclear Launch by Autonomous Artificial Intelligence Act. Existing nuclear policy asserts human control over launch decisions as doctrine; this bill converts that from doctrine into a funding restriction, so that no federal money may be used for a system that selects or engages nuclear targets without meaningful human control.
- Bars the use of federal funds for any system launching nuclear weapons without meaningful human control.
- Codifies the human-in-the-loop principle stated in the Nuclear Posture Review.
- Defines meaningful human control for the purposes of the restriction.
- Extends to systems that select or engage targets autonomously.
- Applies the restriction to development as well as deployment.
Data Care Act
S.744, 118th; S.3570, 119th · Sen. Schatz (D-HI)
With Sens. Bennet, Schatz
Rather than enumerate prohibited practices, this bill borrows the structure of professional duty. Online providers holding personal data would owe their users duties of care, loyalty and confidentiality: an obligation to secure data, not to use it against the person it describes, and not to disclose it in ways that betray the relationship. Enforcement runs through the FTC and state attorneys general.
- Imposes a duty of care to reasonably secure personal data.
- Imposes a duty of loyalty barring use of data to the user's detriment.
- Imposes a duty of confidentiality restricting onward disclosure.
- Extends the duties to third parties receiving the data.
- Provides for enforcement by the FTC and state attorneys general.
American Data Privacy and Protection Act
H.R.8152, 117th · Rep. Pallone (D-NJ)
With U.S. Congress
The most substantial attempt at comprehensive federal privacy legislation to date, and the furthest one has advanced: reported out of the House Energy and Commerce Committee 53 to 2. It works from data minimisation rather than consent, so a company may collect what is necessary for a requested service and not more, with consent unable to authorise the excess. It also brings civil-rights protection inside privacy law, and requires algorithmic impact assessments for consequential decisions.
- Establishes data minimisation as the default: collection limited to what is necessary for a requested service.
- Prohibits use of covered data to discriminate in housing, employment, credit, education or public accommodation.
- Requires algorithmic impact assessments for systems making consequential decisions.
- Grants individual rights of access, correction, deletion and portability.
- Provides a limited private right of action, with pre-emption of most state privacy law.
My Body My Data Act
H.R.3420 / S.1656, 118th · Rep. Jacobs (D-CA); Sen. Hirono (D-HI)
With Rep. Jacobs
Reproductive and sexual health data sits largely outside HIPAA, because HIPAA covers healthcare providers and their business associates rather than the apps, trackers and brokers where much of this data actually accumulates. This bill sets a national minimisation standard for that data specifically: collect and keep only what the service strictly needs, and no more.
- Limits collection, retention and use of reproductive and sexual health data to what is strictly necessary.
- Reaches services outside HIPAA's coverage, including apps and data brokers.
- Requires deletion on request and on expiry of the stated purpose.
- Requires a published privacy policy stating the data handled and the purpose.
- Provides for enforcement by the FTC, state attorneys general, and a private right of action.
Algorithmic Accountability Act of 2023
S.2892 / H.R.5628, 118th · Sen. Wyden (D-OR); Rep. Clarke (D-NY)
With Sens. Wyden, Booker; Rep. Clarke
Automated systems increasingly decide access to housing, credit, employment, healthcare and education, and there is no obligation to check whether they work before they are used at that scale. This bill requires impact assessments for those systems, reported to the FTC, and creates a public repository so that the existence of a consequential automated decision system is a matter of record rather than a discovery.
- Requires impact assessments for automated systems making critical decisions.
- Covers housing, credit, employment, healthcare, education and access to public services.
- Requires assessment of both the system's performance and its disparate effects.
- Requires summary reporting to the Federal Trade Commission.
- Establishes a public repository of covered automated decision systems.
NO FAKES Act
S.4875, 118th; S.4591, 119th · Sen. Coons (D-DE)
With Sens. Coons, Blackburn, Klobuchar, Tillis
Voice and likeness are protected, if at all, by state right-of-publicity law that varies by jurisdiction and often dies with the person. Synthetic replication does not respect state lines. This bill creates a federal digital replication right in voice and likeness, licensable and enforceable, with a defined post-mortem term and safe harbours for platforms that remove infringing replicas on notice.
- Creates a federal digital replication right in an individual's voice and likeness.
- Makes the right licensable, with limits on transfer during the person's lifetime.
- Sets a post-mortem duration, renewable on continued use.
- Provides safe harbours for platforms that act on notice of an infringing replica.
- Includes exclusions for news, commentary, parody, satire and biography.
RAISE Act
S.6953B / A.6453B, New York 2025; ch. amdt. S.8828 · Sen. Gounardes (D-NY 26); Assemblymember Bores (D-NY 73)
With Sen. Gounardes; Assemblymember Bores (New York State)
The second state law in the United States to regulate frontier AI developers directly, after California's Transparency in Frontier Artificial Intelligence Act. It applies to developers who have trained a model above a compute threshold and who earn above a revenue threshold, and requires them to write, publish and follow a safety protocol, and to report critical safety incidents to the Department of Financial Services on a short clock. Signed 19 December 2025; a chapter amendment settling the final text was signed 27 March 2026; obligations take effect 1 January 2027.
- Applies to frontier models trained using more than 1026 integer or floating-point operations.
- Covers developers with annual revenue above $500 million, where the model is developed, deployed or operating in New York.
- Requires large frontier developers to write, implement, publish and comply with a safety protocol.
- Requires critical safety incidents to be reported within 72 hours, and imminent risks to law enforcement within 24.
- Provides civil penalties up to $1 million for a first violation and $3 million for subsequent violations, plus $1,000 per day for failure to file.