Overview
Title
To provide a framework for artificial intelligence innovation and accountability, and for other purposes.
ELI5 AI
This bill is like a set of rules to make sure that robots and computers, like the smart assistants and apps we use, are used safely and fairly, especially for important things like jobs, homes, and rules about being fair. It also says that big companies need to show what they're doing with these smart machines and might have to pay money if they don't follow the rules.
Summary AI
S. 3312, known as the “Artificial Intelligence Research, Innovation, and Accountability Act of 2023,” introduces a framework to encourage innovation in artificial intelligence (AI) while ensuring accountability for its use in the United States. The bill aims to standardize processes related to data authenticity, provenance, and the detection of AI-generated content. It also establishes guidelines for AI transparency and risk management, particularly focusing on systems with high or critical impact on areas like housing, employment, and criminal justice. Additionally, the bill outlines the need for consumer education and creates a working group to develop recommendations for responsible AI use.
Published
Keywords AI
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Bill Statistics
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Language
Complexity
AnalysisAI
The "Artificial Intelligence Research, Innovation, and Accountability Act of 2024" aims to establish a structured framework for developing and responsibly utilizing artificial intelligence (AI) technologies in the United States. The bill is divided into two main sections that focus on AI research and innovation and AI accountability. It touches upon critical aspects such as data policy amendments, AI transparency, the detection of AI-generated content, guidelines for federal agencies, risk management, certification, enforcement, and consumer education regarding AI.
General Summary of the Bill
The proposed legislation concentrates on encouraging AI innovation while ensuring that advancements in AI technology do not come at the expense of accountability and transparency. The bill mandates several measures, such as defining clear standards for AI system development, the submission of transparency reports by organizations deploying AI, and creating an oversight mechanism. It aims to foster public trust in AI systems by standardizing the verification of content authenticity and implementing risk management assessments for AI systems that could significantly impact various sectors like housing, employment, and healthcare.
Significant Issues
A critical challenge identified in the bill is the ambiguity surrounding definitions, particularly regarding "high-impact" and "critical-impact" AI systems. Without clear definitions, the scope of regulation and enforcement becomes uncertain. Furthermore, the bill excludes systems used by the Department of Defense and intelligence community from comprehensive oversight, potentially leaving high-risk AI applications unchecked.
Several sections lack detailed enforcement mechanisms and specify penalties for noncompliance, potentially leading to inconsistent enforcement. The discretionary power granted to the Secretary of Commerce in overseeing AI system compliance could introduce subjectivity without strict guidelines. Additionally, the requirements for transparency reports and risk management assessments might disproportionately affect smaller entities, placing a heavy regulatory burden that could deter innovation.
Potential Impact on the Public
The bill's impact on the public is primarily centered around building trust and ensuring safety in AI technologies that affect daily life. By mandating transparency and evaluation of AI systems, the public can be more informed about and protected from potential biases or unintended consequences of AI deployment. Consistency in AI system evaluations may foster safer adoption practices.
Impact on Specific Stakeholders
For tech companies and developers, especially smaller enterprises, the extensive reporting and compliance requirements could represent a significant hurdle. These requirements might necessitate additional resources, potentially challenging their ability to compete with more prominent players who can afford thorough compliance protocols.
On the other hand, organizations focused on consumer rights and privacy advocacy might find the bill's measures a step in the right direction, as it aims to protect public interests by enforcing transparency and accountability in AI technologies.
Conclusion
In conclusion, while the "Artificial Intelligence Research, Innovation, and Accountability Act of 2024" presents a comprehensive framework for managing AI technologies' potential societal impacts, it also presents challenges in terms of definitions and practical application, especially concerning oversight and compliance for diverse stakeholders. The bill's success will largely depend on addressing identified ambiguities and ensuring that the regulatory burdens do not stifle innovation, thereby harmoniously balancing technological progress with public safety and trust.
Financial Assessment
The “Artificial Intelligence Research, Innovation, and Accountability Act of 2023” (S. 3312) contains various sections that touch on financial aspects, primarily through the imposition of penalties and references to exclusions based on financial criteria. However, the bill lacks explicit spending, appropriations, or detailed financial allocations for its implementation or for supporting the outlined programs.
Penalties and Financial Deterrents
The bill introduces financial penalties as a measure to ensure compliance with its regulations. Specifically, Section 208 sets forth a penalty for violations, stipulating that the penalty will be the greater of an amount not exceeding $300,000 or twice the value of the transaction that led to the violation. This penalty structure aims to deter entities from noncompliance by imposing financial repercussions.
However, there is concern about its effectiveness as a deterrent, particularly for large organizations. With substantial financial resources, these organizations may not find a $300,000 penalty sufficiently daunting. The absence of a more substantial penalty for entities with greater financial capabilities could undermine the bill's enforcement objectives and lead to continued noncompliance. This aligns with one of the identified issues that the penalty cap may not be sufficient for large organizations.
Financial Exclusions
The bill also includes financial criteria for defining certain exclusions. For instance, in Section 201, a “covered internet platform” excludes entities that, during the most recent 180-day period, did not employ more than 500 employees, averaged less than $50,000,000 in annual gross receipts over the past three years, and collect or process personal data from less than 1,000,000 individuals annually. These exclusions are designed to relieve smaller businesses and organizations from the burdensome requirements aimed at larger entities. However, this could be a double-edged sword, as it may inadvertently exempt entities that still have significant impacts despite their smaller size or revenue.
Financial Burden on Smaller Companies
The requirement for detailed transparency reports and risk management assessments in Sections 203 and 206 could disproportionately impact smaller organizations. While the exclusions aim to mitigate this, smaller companies that do not meet the exclusion criteria might still face significant financial burdens to comply with these requirements. This concern is aligned with the issue that these detailed requirements could stifle innovation among less resource-equipped entities.
Financial Resources for Advisory and Working Groups
The bill outlines the establishment of advisory and working groups, such as those in Sections 207 and 210, without specifying clear guidelines or sources of funding. This absence raises concerns about potential inefficiencies and lack of oversight in utilizing resources effectively. Ensuring these groups can function effectively without clear financial planning or appropriated budget could lead to wasteful spending, which resonates with the issue of wasteful spending and lack of oversight.
Overall, the financial aspects of the bill through penalties and exclusions attempt to balance enforcement with feasibility. However, the lack of explicit financial provisions for implementation and the potential inadequacy of penalties for larger organizations highlight areas that could benefit from further refinement to strengthen the bill's effectiveness and fairness.
Issues
The definition of critical terms like 'high-impact artificial intelligence system' and 'critical-impact artificial intelligence system' in Sections 201 and 208 are ambiguous and vague, potentially leading to inconsistent interpretation and enforcement.
The exclusion of systems used by the Department of Defense and intelligence community from the definition of 'high-impact artificial intelligence system' in Sections 204 and 22B could omit oversight for some potentially high-risk systems.
Sections 202 and 203 on Generative AI and Transparency Reports lack clear enforcement mechanisms and exact penalties for noncompliance, which might lead to inconsistent enforcement and accountability.
The broad discretionary power given to the Secretary in various sections, such as 102, 208, and 206, without detailed guidelines or oversight, may lead to subjective or inconsistent application across agencies and entities.
There are no clear guidelines or funding sources specified for the establishment and operation of the advisory and working groups, such as in Sections 207 and 210, raising concerns about potential wasteful spending and lack of oversight.
The requirement for detailed transparency reports and risk management assessments in Sections 203 and 206 could impose significant burdens on smaller companies or less resource-equipped organizations, potentially stifling innovation.
The proposed penalty cap of $300,000 or twice the transaction value in Section 208 may not be a sufficient deterrent for large organizations, potentially leading to continued noncompliance.
The omission of a clearly defined appeals process for penalties and enforcement actions in Sections 208 and 207 could result in unfair practices and dissatisfaction among affected organizations.
Sections
Sections are presented as they are annotated in the original legislative text. Any missing headers, numbers, or non-consecutive order is due to the original text.
1. Short title Read Opens in new tab
Summary AI
The Act is officially named the "Artificial Intelligence Research, Innovation, and Accountability Act of 2023."
2. Table of contents Read Opens in new tab
Summary AI
The text outlines the table of contents for a congressional act focused on artificial intelligence. It includes sections on research, innovation, accountability, transparency, risk management, and consumer education related to AI systems.
101. Open data policy amendments Read Opens in new tab
Summary AI
The amendments to Section 3502 of title 44 redefine terms related to open data policy by including "data model" as a type of data asset, clarifying what a data model is, and introducing the concept of an "artificial intelligence system" as a system that can make decisions or predictions with the help of inputs from both machines and humans.
102. Online content authenticity and provenance standards research and development Read Opens in new tab
Summary AI
The section of the bill details the responsibilities of the Under Secretary of Commerce for Standards and Technology to research and develop technologies that provide information on the authenticity and source of digital content, including human and AI-generated material. This involves creating standards, conducting a pilot program with federal agencies, and submitting progress reports to Congress, ultimately aiming to promote the use of technology that ensures content provenance while being easy for content producers to implement.
103. Standards for detection of emergent and anomalous behavior and AI-generated media Read Opens in new tab
Summary AI
The section updates the National Institute of Standards and Technology Act to include best practices for detecting AI-generated content, such as text, audio, images, and videos, and methods to identify and address unusual or risky behaviors from AI systems.
104. Comptroller General study on barriers and best practices to usage of AI in government Read Opens in new tab
Summary AI
The section directs the Comptroller General to review and report on the obstacles and best methods for implementing artificial intelligence (AI) in government within a year of the Act's enactment. Within two years, a report must be submitted to Congress summarizing the findings, identifying laws and policies that hinder AI adoption, and proposing changes to facilitate AI usage for enhancing government functions.
201. Definitions Read Opens in new tab
Summary AI
The section provides definitions for terms used in the title related to artificial intelligence and internet platforms, including what constitutes an "artificial intelligence system," a "covered internet platform," and a "high-impact artificial intelligence system." It also clarifies the roles of "developer" and "deployer" of AI systems, as well as the meaning of terms like "significant risk" and "TEVV," which relates to testing and evaluating these systems.
Money References
- (B) EXCLUSIONS.—The term “covered internet platform” does not include a platform that— (i) is wholly owned, controlled, and operated by a person that— (I) during the most recent 180-day period, did not employ more than 500 employees; (II) during the most recent 3-year period, averaged less than $50,000,000 in annual gross receipts; and (III) on an annual basis, collects or processes the personal data of less than 1,000,000 individuals; or (ii) is operated for the sole purpose of conducting research that is not directly or indirectly made for profit. (5) CRITICAL-IMPACT AI ORGANIZATION.—The term “critical-impact AI organization” means a non-government organization that serves as the deployer of a critical-impact artificial intelligence system.
202. Generative artificial intelligence transparency Read Opens in new tab
Summary AI
The section makes it illegal to run an online platform using generative AI unless the platform clearly informs users that AI is generating content they see. If platforms fail to comply, they will be notified and given 15 days to fix the issue, or face possible enforcement actions.
203. Transparency reports for high-impact artificial intelligence systems Read Opens in new tab
Summary AI
The text outlines transparency and reporting requirements for companies deploying "high-impact" AI systems. Before deployment and annually after, companies must report their AI system's purpose, data use, safety measures, and performance metrics to the Secretary. If changes are made to the AI system's use or data, an updated report must be submitted. Developers must follow specific obligations, and the Secretary must avoid duplicating requirements with other agencies. Noncompliance may lead to enforcement, but trade secrets and confidential business information remain protected.
204. Recommendations to Federal agencies for risk management of high-impact artificial intelligence systems Read Opens in new tab
Summary AI
The section of the bill directs the National Institute of Standards and Technology to create recommendations for federal agencies on overseeing high-impact artificial intelligence systems that could affect important areas like housing, jobs, and healthcare. These recommendations aim to ensure the safe and responsible use of AI, considering possible risks and including input from diverse groups such as civil society and academia.
22B. Recommendations to Federal agencies for sector-specific oversight of artificial intelligence Read Opens in new tab
Summary AI
The section defines "high-impact artificial intelligence systems" as AI technologies that can significantly affect people's access to important services like housing and employment, excluding those used by the Department of Defense or the intelligence community. It requires the Director to create guidelines for federal agencies to safely manage these systems within a year and to update these guidelines as technology evolves.
205. Office of Management and Budget oversight of recommendations to agencies Read Opens in new tab
Summary AI
The section outlines the responsibilities of the Office of Management and Budget in overseeing the implementation of recommendations from NIST to various agencies. It requires agencies to respond to these recommendations, make responses publicly available, report their regulatory status annually, and notify Congress if they fail to report. Additionally, it calls for support in implementing these recommendations and developing performance measures for regulating artificial intelligence.
206. Risk management assessment for critical-impact artificial intelligence systems Read Opens in new tab
Summary AI
Critical-impact AI organizations must conduct risk management assessments before making their AI systems public and update these assessments every two years as long as the systems are available. These assessments should address organizational policies, system capabilities, risk analysis methods, and resource allocation for managing AI risks. Developers must also provide necessary information to comply with these requirements, and the Secretary can set standards that may end certain disclosure obligations, ensuring that no proprietary or confidential information is required to be shared.
207. Certification of critical-impact artificial intelligence systems Read Opens in new tab
Summary AI
The bill section establishes an advisory committee to help set standards for testing and certifying critical-impact AI systems and requires the Secretary to create an AI certification plan. It outlines procedures for creating and updating standards, including public input and cooperation with other entities, and sets rules for exemptions and enforcement of compliance.
208. Enforcement Read Opens in new tab
Summary AI
The section outlines the enforcement measures for noncompliance with regulations related to high-impact artificial intelligence systems. It details possible civil penalties for violations, additional prohibitions for intentional violations, standards for penalty levels based on various factors, and provisions for civil actions by the Attorney General, while ensuring that trade secrets and confidential information are protected.
Money References
- (2) PENALTY DESCRIBED.—The penalty described in this paragraph is the greater of— (A) an amount not to exceed $300,000; or (B) an amount that is twice the value of the transaction that is the basis of the violation with respect to which the penalty is imposed. (c) Violation with intent.
209. Artificial intelligence consumer education Read Opens in new tab
Summary AI
The section mandates the creation of a working group by the Secretary to develop responsible education strategies for artificial intelligence (AI) systems, involving experts from various fields. The group will recommend educational programs about AI for consumers, report their findings to Congress, and will be dissolved two years after the law is enacted.
1. Short title Read Opens in new tab
Summary AI
The first section of this bill provides its official name, which is the “Artificial Intelligence Research, Innovation, and Accountability Act of 2024.”
2. Table of contents Read Opens in new tab
Summary AI
The text outlines the table of contents for a legislative act, which is divided into two titles: Title I—Artificial Intelligence Research and Innovation and Title II—Artificial Intelligence Accountability. Each title includes various sections covering topics like open data policy amendments, AI transparency, standards for detecting AI-generated media, guidelines and oversight for high-impact AI systems, risk management, certification, enforcement, and consumer education on artificial intelligence.
101. Open data policy amendments Read Opens in new tab
Summary AI
Section 101 modifies title 44 of the United States Code by clarifying definitions related to data management, specifically adding what a "data model" and an "artificial intelligence system" represent. A "data model" is defined as a mathematical, economic, or statistical way to help make predictions using things like algorithms, while an "artificial intelligence system" is described as a machine system that learns how to create outputs such as predictions or recommendations based on the information it receives.
102. Online content authenticity and provenance standards research and development Read Opens in new tab
Summary AI
The bill tasks the Under Secretary of Commerce for Standards and Technology with conducting research to develop and standardize ways to verify the authenticity and origin of digital content, including starting a pilot program to test these methods in federal agencies. Additionally, the Under Secretary is to provide technical assistance in creating standards and report progress to Congress, with the pilot program running for up to 10 years.
103. Standards for detection of anomalous behavior and artificial intelligence-generated media Read Opens in new tab
Summary AI
The section of the National Institute of Standards and Technology Act is updated to include new best practices for identifying content created by artificial intelligence, like text and videos, and to establish methods for recognizing and managing unusual and possibly harmful behaviors by AI systems.
104. Comptroller general study on barriers and best practices to usage of AI in government Read Opens in new tab
Summary AI
The section requires the Comptroller General to study and report on barriers and best practices for using artificial intelligence (AI) in the federal government. Within one year, a review of existing legal and policy barriers must be conducted, and best practices identified. A report is due within two years to relevant Senate and House committees, summarizing the findings and offering recommendations to improve AI adoption and address any legislative or policy barriers.
201. Definitions Read Opens in new tab
Summary AI
The section defines various terms related to the regulation and use of artificial intelligence (AI) within government and nongovernmental contexts. It includes definitions for terms like "artificial intelligence system," which refers to machines that analyze inputs to produce outputs affecting environments, "covered agency," which refers to government agencies subject to specific AI guidelines, and "high-impact artificial intelligence system," denoting AI systems used in critical sectors like housing or employment that could significantly impact individuals’ rights or safety.
202. Generative artificial intelligence transparency Read Opens in new tab
Summary AI
People running online platforms that use generative AI must inform users about it before they see AI-created content, and they have an option to alert users only during their first interaction with such content. If these platforms don't comply, they must fix the issue within 15 days after being notified.
203. Transparency reports for high-impact artificial intelligence systems Read Opens in new tab
Summary AI
The text outlines the transparency reporting requirements for those deploying high-impact AI systems, mandating that they regularly submit detailed reports about AI risks, system capabilities, and risk management methods to the Secretary. It also elaborates on the responsibilities of AI developers, considerations for compliance, and actions in case of noncompliance, while protecting trade secrets and allowing consolidated reporting when multiple deployers are involved.
204. Guidelines for Federal agencies and plans for oversight of high-impact artificial intelligence systems Read Opens in new tab
Summary AI
The bill outlines guidelines for federal agencies to oversee high-impact artificial intelligence (AI) systems, focusing on those that replace human decision-making in areas such as housing, employment, and health care. It requires the development of oversight plans to ensure the safe and responsible use of AI, with updates and consultations to address technological changes and involve various stakeholders.
22B. Guidelines for Federal agencies for oversight of artificial intelligence Read Opens in new tab
Summary AI
The section outlines the guidelines for overseeing high-impact artificial intelligence systems in the U.S., which are AI systems that can significantly affect people's access to important services like housing and employment. It describes how federal agencies should develop and update these guidelines to ensure responsible AI use and manage potential risks, consulting with various stakeholders as needed.
205. Office of Management and Budget Oversight guidelines and agency oversight plans Read Opens in new tab
Summary AI
In this section, the bill describes the creation and implementation of "agency oversight plans" by various government agencies, which must be submitted to the Office of Management and Budget and Congress. It also outlines the process for annual reporting on the implementation status, provides for technical assistance to agencies, and involves regular reviews and improvements of regulations related to artificial intelligence.
206. Risk management assessment for critical-impact artificial intelligence systems Read Opens in new tab
Summary AI
Each critical-impact AI organization must conduct and regularly update a risk management assessment for their AI systems, and send a report to the Secretary. They should document how they address AI risks, legal requirements, and trustworthy AI characteristics within their practices, while AI developers must provide necessary information to system deployers. The Secretary cannot prohibit public availability of an AI system based on the review of these reports, and trade secrets must be protected.
207. Certification of critical-impact artificial intelligence systems Read Opens in new tab
Summary AI
The section outlines the establishment of an advisory committee and a plan by the Secretary for certifying critical-impact artificial intelligence systems, focusing on creating and updating testing and certification standards known as TEVV standards. The section also details the procedure for public consultation, compliance requirements for organizations, possible exemptions, and enforcement actions if there is noncompliance.
208. Enforcement Read Opens in new tab
Summary AI
The section outlines that the Secretary can take action if someone doesn't follow the rules of the Act related to artificial intelligence. This includes imposing fines and other penalties, especially if the violation was intentional. The Secretary can work with the Attorney General to investigate and bring legal action if needed, but companies aren't required to share trade secrets.
Money References
- (2) PENALTY DESCRIBED.—The penalty described in this paragraph is the greater of— (A) an amount not to exceed $300,000; or (B) an amount that is twice the value of the artificial intelligence system product deployed that is the basis of the violation with respect to which the penalty is imposed. (c) Violation with intent.
209. Developer and deployer overlap Read Opens in new tab
Summary AI
Entities that act as both deployers and developers must follow the rules applicable to both roles as outlined in this law.
210. Artificial intelligence consumer education Read Opens in new tab
Summary AI
The bill requires the Secretary to create a 15-member working group within 180 days to develop educational programs about artificial intelligence (AI) for public awareness, focusing on its uses, limitations, and safety aspects. This group, which will operate without pay, will provide findings and recommendations to Congress and the public, and will consult with the Federal Trade Commission, disbanding two years after the bill's enactment.
211. Severability Read Opens in new tab
Summary AI
If any part of this section or its amendments is found to be unconstitutional, the rest of the section and its amendments will still remain in effect for everyone else and in other situations.