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Regulations and Documents
Legislation
About these categories

Social Impact: encompasses legislation that specifically addresses the impact of AI on society and individuals, including but not limited to; reducing the carbon footprint of AI systems, holding system developers accountable for the outputs of these systems, the establishment of new fairness and bias metrics to guard against AI-driven discrimination, the use of AI by minors, consumer protections for AI products, regulations that address psychological, physical, or material harm caused by interactions with AI systems, and the role of AI in misinformation, public discourse, and the erosion of trust in public institutions.

Data Governance: encompasses legislation that specifically addresses the secure and accurate collection and management of data within AI systems, including but not limited to; mandates for rectifying inaccuracies in AI data sets, mandates for ensuring AI data sets are free from biases, regulations that address intellectual property concerns with the unauthorized use of protected material in AI data sets, and requirements for data encryption, data anonymization, controlled access, and compliance with consumer privacy laws.

System Integrity: encompasses legislation that specifically addresses the inherent security, transparency, and control of AI systems, including but not limited to; mandates for human intervention and oversight in AI processes, standards for the interoperability of AI systems in essential services, and the implementation of security measures such as threat modeling, penetration testing, and incident response.

Robustness: encompasses legislation that specifically addresses the development and adoption of new benchmarks for AI performance, including but not limited to; the certification of AI systems against new benchmarks, ensuring compliance with international standards, requirements for auditing and transparent reporting to verify continuous regulatory compliance, and the creation of specialized oversight bodies.

About these sectors

Politics and Elections: encompasses legislation that specifically addresses the use and regulation of AI in political campaigns, electoral processes, and related legislative activities.

Government Agencies and Public Services: encompasses legislation that specifically addresses the use and regulation of AI by state and federal government agencies, as well as AI applications in the delivery of public services and enhancing government operations.

Judicial System: encompasses legislation that specifically addresses the use and regulation of AI by judicial and legal systems, including but not limited to the use of AI in case management and legal decision making.

Healthcare: encompasses legislation that specifically addresses the use and regulation of AI in healthcare settings, including but not limited to AI applications within hospitals and clinics, the development of AI-enabled diagnostic tools and related medical technologies, and the management of medical data.

Private Enterprises, Labor, and Employment: encompasses legislation that specifically addresses the use and regulation of AI in business environments, ensuring fair competition, and the effects of AI on labor markets, employment practices, and corporate governance.

Academic and Research Institutions: encompasses legislation that specifically addresses the use and regulation of AI in educational and research contexts.

International Cooperation and Standards: encompasses laws and agreements that address international cooperation on AI development, use, and regulation, including but not limited to multinational standards, cross-border data practices, and global ethical guidelines for AI.

Nonprofits and NGOs: encompasses legislation that specifically addresses the use and regulation of AI by nonprofits and non-governmental organizations and institutions.

Hybrid, Emerging, and Unclassified: encompasses legislation that doesn't neatly fit into other categories, as well as the application of AI in hybrid or emerging sectors.

Clear All

4840 results:


Determination of Metal Concentration on Catalyst Particles (Instrumental Analyzer Procedure)

Summary: The bill establishes a procedure for determining metal concentrations on catalyst particles using instrumental analysis, particularly X-ray fluorescence, to enhance data quality in environmental monitoring.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The provided text is a detailed procedural guide for determining metal concentrations on catalyst particles using instrumental analysis. It primarily focuses on methodological specifics, equipment, and calibrations related to analytical procedures. The text does not reference concepts related to artificial intelligence (AI) or automated decision-making systems. Consequently, there is no connection to Social Impact, Data Governance, System Integrity, or Robustness within the context of AI legislation or its implications. As such, all categories are considered not relevant.


Sector: None (see reasoning)

Similarly, the text does not address or make mention of sectors involved in AI applications. It remains focused on laboratory procedures for metal analysis, with no references to Politics and Elections, Government Agencies and Public Services, the Judicial System, Healthcare, Private Enterprises, Labor, and Employment, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, or any hybrid categories. Thus, all sectors are also deemed not relevant.


Keywords (occurrence): automated (3) show keywords in context

Detergent blenders.

Summary: The bill outlines regulatory requirements for detergent and oxygenate blenders and producers, including registration, reporting, certification, and transfer documentation to ensure compliance with environmental standards.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily deals with regulations concerning fuel manufacturers, specifically dealing with diesel and fuel additives. There are no explicit references to AI or related technologies such as algorithms, machine learning, or automated systems that would warrant relevance to the categories provided (Social Impact, Data Governance, System Integrity, Robustness). Thus, all categories will receive a score of 1, as they do not pertain to the content of this text.


Sector: None (see reasoning)

The text refers to regulatory requirements for fuel manufacturers and blenders and does not engage with any of the sectors described. It does not mention politics, government services, healthcare, labor, academic applications, or any other of the defined sectors. Therefore, all sectors will also score a 1, as they are irrelevant to the text content.


Keywords (occurrence): automated (1) show keywords in context

Information system security.

Summary: This bill establishes security protocols for subcontractors accessing classified information, mandating eligibility verification and security classifications while ensuring compliance with federal guidelines for information system security.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

Category:
Data Governance
System Integrity (see reasoning)

The document encompasses a comprehensive framework for managing and securing information systems, particularly concerning classified information. It heavily emphasizes risk management, security protocols, and compliance with regulations provided by governing bodies such as the CSA and NIST. Although there is no explicit mention of AI technologies or applications, the context implies some relevance to automation and data management practices that could involve machine learning principles for security monitoring and threat assessment. The focus on managing insider threats and monitoring user activity may tangentially relate to AI-driven solutions, but the specificity is limited. Therefore, the relevance to each category is assessed based on the overall emphasis on security and data handling practices rather than direct AI considerations.


Sector:
Government Agencies and Public Services (see reasoning)

The document primarily addresses compliance and security procedures for contractors handling classified information and does not directly mention the application of AI in any of the described sectors. However, the strong focus on security systems and data governance suggests implications for government agencies and contractors. The procedures for managing classified information involve processes that could intersect with the operations of governmental or defense agencies, providing a loose connection to the sectors involved, particularly concerning compliance with national security standards. The absence of specific references to AI application or context results in a low relevance score for most sectors, but 'Government Agencies and Public Services' is somewhat relevant due to implications for data management within these entities.


Keywords (occurrence): automated (2) show keywords in context

The Philosophy of AI: Learning from History, Shaping Our Future

Summary: The bill facilitates a Senate hearing examining the philosophical and historical implications of AI, addressing its potential benefits and risks to democracy, civil liberties, and society at large.
Collection: Congressional Hearings
Status date: Nov. 8, 2023
Status: Issued
Source: Senate

Category:
Societal Impact
Data Governance
System Integrity (see reasoning)

The text heavily discusses the implications of AI on society, ethics, and individual rights, primarily through the lens of a Senate hearing focused on understanding AI's impact on civil liberties, democracy, and human agency. It highlights AI's potential to revolutionize sectors like medicine and culture, while also raising alarms about surveillance, bias, and inequality—core aspects of the Social Impact category. The discussion brings forward the philosophical dimensions of AI legislation, the necessity for alignment with democratic values, and protections against its risks to civil liberties, marking it as very relevant to Social Impact. The details about oversight, transparency, and the ethical frameworks surrounding AI's deployment speak to Dataset Governance and System Integrity, although less directly. Robustness is less pronounced as the dialogue centered more around ethical implications rather than performance benchmarks for AI systems, making it less relevant in this context.


Sector:
Politics and Elections
Government Agencies and Public Services
Judicial system
Academic and Research Institutions (see reasoning)

The text revolves around the intersection of AI and governance, touching on themes relevant to various sectors. It explores the implications of AI within government operations, civil liberties, and democratic frameworks, setting a strong foundation for the 'Government Agencies and Public Services' sector. The testimony highlights the necessity of governance structures in managing AI's rise and risks it poses, while the ethical and philosophical discussions engage with the broader landscape of politics and legislative practices, thus meriting a strong score in Politics and Elections as well. Judicial System is indirectly referenced through mentions of constitutional law and civil liberties but lacks depth, making it marginally relevant. Other sectors like Healthcare and Private Enterprises are not addressed, and thus hold no relevance. Academic and Research Institutions are somewhat connected through the academic backgrounds of the witnesses but do not represent the main focus. The text does not relate to the other sectors in any significant manner.


Keywords (occurrence): artificial intelligence (9) machine learning (1) automated (7) algorithm (1) show keywords in context

Automated monitoring.

Summary: The bill mandates automated monitoring systems for trainsets, ensuring safety through alerting drivers of performance issues and ensuring compliance with operating rules in case of defects.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category:
Societal Impact
Data Governance
System Integrity (see reasoning)

The text discusses several aspects of automated monitoring systems used in trainsets, which encompasses monitoring components like electric brake status, fire detection systems, and temperature sensors. The relevance of specific categories can be assessed based on their connection to the described monitoring systems and their implications. Social Impact considers the safety and operational implications of automated monitoring, particularly in the context of human interaction and risk; thus, it's very relevant. Data Governance is relevant due to the monitoring capabilities that gather data from various systems; the text emphasizes the need for data accuracy and integrity while also hinting at regulatory oversight. System Integrity is extremely relevant since the text details the self-test features and alerts for failures in the automated monitoring systems, directly connected to the need for reliability and transparency in such systems. Robustness is less relevant, as the discussion does not center on performance benchmarks or certification of AI but rather on operational features of monitoring systems.


Sector:
Government Agencies and Public Services (see reasoning)

The text outlines regulations governing automated monitoring systems within trainsets, touching upon safety protocols and operational readiness that relate to public transportation. The Government Agencies and Public Services sector is highly applicable as the context involves regulations aimed at ensuring safe rail transportation, which is often overseen by government authorities. While elements could somewhat align with other sectors like Judicial System (due to compliance measures), the central theme of regulatory oversight in public services is clearer. The text does not particularly address applications in Politics and Elections, Healthcare, Private Enterprises, Academic Institutions, International Cooperation, or Nonprofits, hence these receive lower relevance.


Keywords (occurrence): automated (1)

Automated vessels.

Summary: The bill facilitates the use of automated vessels by allowing reduced crew requirements based on system reliability and allows the temporary hiring of non-U.S. personnel for manning needs abroad.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category:
System Integrity
Data Robustness (see reasoning)

The text discusses regulations related to automated vessels, specifically focusing on the acceptance and reliability of automated systems intended to replace crew members or reduce crew requirements. This clearly relates to the category of System Integrity, as it outlines the standards and oversight necessary for ensuring that automated systems operate safely and dependably. The text partially aligns with Robustness, discussing requirements for the ongoing reliability of automated vessels, although it primarily emphasizes system acceptance rather than performance benchmarks. There is little direct relevance to Data Governance or Social Impact, as the text does not address data management concerns or the societal implications of these automated systems in detail.


Sector:
Government Agencies and Public Services (see reasoning)

The text relates closely to Government Agencies and Public Services, specifically the Coast Guard's regulations regarding automated vessels. The mention of crew safety and the operational standards expected by the Coast Guard falls into this sector. There isn't a significant connection to the other sectors, as the details are specific to maritime regulations and do not address areas such as healthcare, judicial systems, or political applications.


Keywords (occurrence): automated (2) show keywords in context

Daily Digest/House of Representatives

Summary: The bill appropriates funding for financial services and general government for fiscal year 2024, including provisions for enhancing financial literacy, combating terrorism and crime, and addressing various amendments concerning federal activity and regulations.
Collection: Congressional Record
Status date: Nov. 8, 2023
Status: Issued
Source: Congress

Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)

The text contains specific references to the use of artificial intelligence, particularly concerning its application within the Internal Revenue Service (IRS) for compliance efforts and investigations related to taxes. The discussions of AI and chatbot technology used for taxpayer service highlight potential impacts on society (Social Impact) while the provisions on its regulatory use within the IRS touch upon aspects of data collection and management (Data Governance). Additionally, the mention of AI in compliance measures relates to the integrity and safety measures needed for deployment (System Integrity) and the need for related performance benchmarks (Robustness).


Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)

The references to AI in the text primarily pertain to government agencies like the IRS and its chatbot services. This suggests a significant focus on how AI is employed in public services, which resonates strongly with the sector dedicated to Government Agencies and Public Services. Furthermore, elements of financial services regulated by government, such as countering financial crimes through AI tools, touch on aspects relevant to Private Enterprises, Labor, and Employment, albeit to a lesser degree.


Keywords (occurrence): artificial intelligence (1) chatbot (2) show keywords in context

Data available from the Federal Catalog System.

Summary: The bill outlines the availability of Federal Catalog System data to government agencies, detailing various publications and automated outputs that support supply management activities.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

Category:
Data Governance (see reasoning)

The text primarily discusses the Federal Catalog System, focusing on the availability of data related to federal property management and logistics. It mentions automated data output and tailored elements for government agencies, which could touch on AI-related aspects like optimization and decision-making systems. However, it lacks explicit connections to the core AI issues such as bias, fairness, accountability in AI, or performance benchmarks. As a result, while there is some automation aspect mentioned, it does not significantly engage with the social impact, data governance, system integrity, or robustness specifically related to AI legislation.


Sector:
Government Agencies and Public Services (see reasoning)

The text makes clear references to the Federal Catalog System and its relevance to federal supply activities, specifically detailing the government’s organizational structure around data management and cataloging. However, it does not target broader issues that would connect to sectors like political campaigning, healthcare, or judiciary functions. While there are implications for government agencies as users of this system, the focus remains predominantly on logistical aspects rather than giving a full viewpoint on AI application across multiple sectors.


Keywords (occurrence): automated (2) show keywords in context

Michigan SB0606: Environmental protection: cleanups; cleanup to residential and safe drinking water standards; require unless technically infeasible. Amends secs. 20118, 20120a, 20120b, 20120e & 20121 of 1994 PA 451 (MCL 324.20118 et seq.). TIE BAR WITH: SB 0605'23, SB 0607'23

Description: Environmental protection: cleanups; cleanup to residential and safe drinking water standards; require unless technically infeasible. Amends secs. 20118, 20120a, 20120b, 20120e & 20121 of 1994 PA 451 (MCL 324.20118 et seq.). TIE BAR WITH: SB 0605'23, SB 0607'23
Summary: The bill amends Michigan's environmental protection laws to require cleanup of contaminated sites to residential and safe drinking water standards, unless technically infeasible, enhancing public health and environmental safety.
Collection: Legislation
Status date: Oct. 24, 2023
Status: Introduced
Primary sponsor: Jeremy Moss (9 total sponsors)
Last action: Referred To Committee On Energy And Environment (Oct. 24, 2023)

Category: None (see reasoning)

The text concerns environmental protection and cleanup measures rather than AI technology. While it mentions certain processes that might involve algorithms (e.g., risk assessment, cleanup criteria development), there is no explicit reference to AI systems, algorithms, or any AI-related concepts. Thus, the relevance to Social Impact, Data Governance, System Integrity, or Robustness is minimal. The text seems to focus heavily on legal definitions and guidelines for environmental action, which do not explicitly connect to the categories defined regarding AI legislation.


Sector: None (see reasoning)

The text discusses amendments to environmental protection laws, particularly cleanup standards and processes. While the bill may indirectly relate to the public's health and safety and potentially the use of data for environmental assessments, there are no references to AI technologies or systems in the legislative text. Therefore, the relevance to the identified sectors is low as none specifically address the application or regulation of AI systems.


Keywords (occurrence): algorithm (2) show keywords in context

SALUTING THE SERVICE OF CAPTAIN HOWARD McKINNEY, U.S. ARMY, RETIRED

Summary: The bill honors Captain Howard McKinney, a retired U.S. Army officer, for his distinguished military service and contributions to community and veteran organizations, awarding him a Congressional Veteran Commendation.
Collection: Congressional Record
Status date: Dec. 11, 2023
Status: Issued
Source: Congress

Category: None (see reasoning)

The text primarily pays tribute to Captain Howard McKinney for his military service and achievements. While it mentions automated tax systems, it does not delve into the implications or governance of AI technologies or their broader social impacts. Therefore, the relevance of all categories related to AI is minimal. The mention of 'automated' in the context of tax systems does not indicate a focus on AI systems or their governance, and hence holds little significance in terms of data governance, system integrity, robustness, or social impact. Overall, the content of the text is not focused on AI related issues, leading to low relevance across all categories.


Sector: None (see reasoning)

The text is centered on honoring a veteran and does not relate to any specific sector involving AI use or regulation. It mentions automated tax systems but does not discuss any governmental processes or implications of technology governing in the context of politics, healthcare, or other outlined sectors. The content is not applicable to any of the nine sectors provided, leading to low relevance across all sectors.


Keywords (occurrence): automated (1) show keywords in context

Access to records.

Summary: The bill establishes guidelines for the Department of Labor's access to records and audit processes for organizations receiving federal funds, ensuring compliance and addressing audit findings effectively.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text does not specifically address AI or its implications. It focuses on access to records, audit procedures, quality control in auditing, and audit resolutions within the Department of Labor (DOL). While automated systems are mentioned, they refer generally to records management rather than to AI systems or concepts such as machine learning or algorithms. Therefore, the relevance of this text to the categories related to AI is minimal.


Sector:
Government Agencies and Public Services (see reasoning)

This text primarily details regulations concerning the auditing processes of the Department of Labor. It does not make specific reference to the use of AI in the auditing process, nor does it address any sector-specific applications related to AI in areas such as politics, healthcare, or business. Consequently, the relevance of this text to the predefined sectors is low.


Keywords (occurrence): automated (1) show keywords in context

INTRODUCTION OF BILLS AND JOINT RESOLUTIONS

Summary: The bill introduced in the Senate includes various measures addressing law enforcement cooperation, disability support in education, mental health services, school safety, and transparency in funding among other topics. Its purpose is to propose legislative actions for improving community safety, access to education, mental health care, and public health regulations.
Collection: Congressional Record
Status date: March 30, 2023
Status: Issued
Source: Congress

Category: None (see reasoning)

The text primarily outlines a series of bills and joint resolutions introduced in the Senate without any explicit reference to AI-related terms or concepts. None of the key AI terms such as 'Artificial Intelligence', 'Algorithm', 'Machine Learning', etc., are mentioned in this text. Therefore, it does not address any implications of AI on social issues, data governance, system integrity, or robustness. It largely focuses on legislative actions and processes that do not pertain to AI.


Sector: None (see reasoning)

The text lists various bills and resolutions but does not indicate any connection to specific sectors relating to the use or regulation of AI, such as Politics and Elections, Government Agencies and Public Services, or Healthcare. Since there is no mention of AI applications or discussions within any outlined sectors, all sectors also receive the lowest relevance score.


Keywords (occurrence): artificial intelligence (1) show keywords in context

United States SR243: A resolution recognizing the month of June 2023 as "Immigrant Heritage Month", a celebration of the accomplishments and contributions of immigrants and their children in making the United States a healthier, safer, more diverse, prosperous country, and acknowledging the importance of immigrants a...

Description: A resolution recognizing the month of June 2023 as "Immigrant Heritage Month", a celebration of the accomplishments and contributions of immigrants and their children in making the United States a healthier, safer, more diverse, prosperous country, and acknowledging the importance of immigrants and their children to the future successes of the United States.
Summary: The bill designates June 2023 as "Immigrant Heritage Month," celebrating the contributions of immigrants in enhancing the U.S.'s diversity, prosperity, and public health, while advocating for just immigration policies.
Collection: Legislation
Status date: June 8, 2023
Status: Introduced
Primary sponsor: Robert Menendez (20 total sponsors)
Last action: Referred to the Committee on the Judiciary. (text: CR S2033-2034) (June 8, 2023)

Category:
Societal Impact (see reasoning)

This resolution recognizes June 2023 as 'Immigrant Heritage Month' and highlights the contributions of immigrants, particularly in the healthcare sector and the STEM fields, including artificial intelligence. The mention of immigrants filling roles in AI is significant; however, the primary focus of the text is centered around the celebration of immigrant contributions rather than directly addressing the implications, regulations, or governance of AI itself, which affects its scoring in the relevant categories. This results in a moderate to slightly relevant categorization for Social Impact due to the emphasis on contributions but lacking direct legislative action on societal issues arising from AI. Data Governance, System Integrity, and Robustness are not addressed in this resolution at all, leading to scores of 1 or 2. Therefore, overall relevance to AI is limited but respected for its recognition of fields essential to technological advancement.


Sector: None (see reasoning)

The resolution mentions the role of immigrants in STEM fields, including artificial intelligence, but does not delve into specific regulations, practices, or impacts within the defined sectors. Regarding Politics and Elections, Government Agencies and Public Services, and other sectors, while immigration does have implications for employment, efficiency, and social contributions, the absence of direct discussion on AI applications within these contexts leads to low relevance. The significance placed on healthcare roles, while important, is incidental to the immigration theme of the resolution. Hence, scores reflect this with 1s across the sectors, except for possible slight relevance through academic contributions which is not sufficiently detailed.


Keywords (occurrence): artificial intelligence (2) show keywords in context

Appropriations (Executive Session)

Summary: The bill focuses on appropriations for fiscal year 2024, advocating for responsible federal spending cuts, prioritization of critical programs, and adequate funding for national security and law enforcement, while avoiding omnibus packages.
Collection: Congressional Record
Status date: Nov. 29, 2023
Status: Issued
Source: Congress

Category: None (see reasoning)

The text has minimal relevance to the categories related to AI legislation. The only mention of artificial intelligence comes at the end where it states that funding will help understand the 'promise and pitfalls of artificial intelligence.' This indicates a focus on the implications of AI but lacks specific discussion on its societal impact, governance, integrity, or robustness. Therefore, while the mention of AI suggests potential relevance, it lacks sufficient depth to address any of the categories except perhaps Social Impact, which relates to the broader implications of AI on society. However, without specifics, the relevance remains limited.


Sector: None (see reasoning)

The text primarily discusses appropriations for federal spending without delving deeper into the use or regulation of AI within specific sectors such as politics, government services, or healthcare. While there may be indirect implications for public services, there is no concrete mention or focused discussion on the impact of AI in any specified sector. The mention of AI is vague and not tied to specific legislative context that would fit cleanly into any of the defined sectors, resulting in overall low relevance scores.


Keywords (occurrence): artificial intelligence (1) show keywords in context

What definitions must I know?

Summary: The bill outlines definitions and compliance requirements for sewage sludge incineration units under EPA regulations, set to ensure environmental protection and emission standards. It clarifies permit application deadlines and monitoring obligations.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily focuses on regulatory aspects related to environmental protection, specifically concerning sewage sludge incineration units under the Clean Air Act. It includes definitions relevant to air quality management and monitoring systems, rather than directly addressing AI technologies or their societal impacts. AI-related concepts such as algorithmic performance or machine learning advancements are not present in this document. Therefore, its relevance to the designated categories is limited at best. The categories of Social Impact, Data Governance, and Robustness do not relate at all to the content which is centered around environmental regulation and compliance. System Integrity could be seen as slightly relevant since monitoring systems are mentioned, but it does not explicitly address AI systems or their integrity in a technology context.


Sector: None (see reasoning)

The content pertains primarily to environmental regulations rather than sectors involving AI specifically. There are mentions of automated systems, which could be seen as overlapping with some elements in public services; however, the text does not specifically address AI applications within public services or healthcare settings. Therefore, I rate all sectors as either not relevant or only slightly relevant. The Government Agencies and Public Services sector could receive a slightly higher score due to references to compliance with environmental standards, but this does not extend to AI usage.


Keywords (occurrence): automated (3) show keywords in context

United States HB2894: Block Nuclear Launch by Autonomous Artificial Intelligence Act of 2023

Description: To prohibit the use of Federal funds to launch a nuclear weapon using an autonomous weapons system that is not subject to meaningful human control, and for other purposes.
Summary: The Block Nuclear Launch by Autonomous Artificial Intelligence Act of 2023 aims to prohibit federal funding for launching nuclear weapons via autonomous systems lacking meaningful human control, emphasizing the need for human oversight in critical military decisions.
Collection: Legislation
Status date: April 26, 2023
Status: Introduced
Primary sponsor: Ted Lieu (26 total sponsors)
Last action: Referred to the Committee on Armed Services, and in addition to the Committee on Foreign Affairs, for a period to be subsequently determined by the Speaker, in each case for consideration of such provisions as fall within the jurisdiction of the committee concerned. (April 26, 2023)

Category:
Societal Impact
System Integrity (see reasoning)

The text clearly pertains to the social impact of AI as it discusses the implications and ethical considerations of using autonomous weapons systems, specifically regarding nuclear weapons. It examines the potential harms of AI in military applications, including the risk of reduced accountability and the inability of autonomous systems to genuinely understand human life. The emphasis on maintaining meaningful human control over critical military decisions demonstrates significant relevance to the concept of social impact. The issues of accountability, humanitarian law compliance, and the consequences of deploying lethal autonomous systems highlight the societal implications of AI technology in sensitive contexts. Therefore, this categorization is rated highly relevant. Data governance, while potentially relevant due to the collected data involved in autonomous systems, is less directly addressed in the text. The highlighted need for security, transparency, and human intervention aligns somewhat with system integrity, but it primarily centers around ethical considerations rather than technical specifications. Robustness is less relevant since the document focuses less on performance metrics for AI systems. As such, Social Impact receives the highest relevance score, while the other categories receive lower scores.


Sector:
Government Agencies and Public Services (see reasoning)

The text discusses the use of AI in military contexts specifically focused on nuclear weapon systems. While there are references to alignment with humanitarian law and legislative oversight, it does not explicitly focus on political campaigns (Politics and Elections) or judicial practices (Judicial System). The emphasis is primarily on government and military regulations, which pertain to Government Agencies and Public Services. Therefore, this sector receives a high relevance score as it relates to the oversight of AI applications in defense. Other sectors like Healthcare, Private Enterprises, Labor, and Employment, Academic and Research Institutions, International Cooperation and Standards, or Nonprofits and NGOs do not find significant mention within the text, showing minimal to no relevance. Hence, only Government Agencies and Public Services receives a higher score.


Keywords (occurrence): artificial intelligence (3) show keywords in context

United States SB3312: Artificial Intelligence Research, Innovation, and Accountability Act of 2023

Description: A bill to provide a framework for artificial intelligence innovation and accountability, and for other purposes.
Summary: The Artificial Intelligence Research, Innovation, and Accountability Act of 2023 establishes a framework for AI innovation and accountability, focusing on transparency, standards, and risk management in AI systems.
Collection: Legislation
Status date: Nov. 15, 2023
Status: Introduced
Primary sponsor: John Thune (8 total sponsors)
Last action: Committee on Commerce, Science, and Transportation. Ordered to be reported with an amendment in the nature of a substitute favorably. (July 31, 2024)

Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)

This text directly addresses various aspects of artificial intelligence, including its development, application, and accountability. The mention of terms related to AI such as 'artificial intelligence systems', 'generative artificial intelligence', and specific provisions aimed at governing these technologies reveals the intention to create a comprehensive legal framework for AI that includes innovation, risk assessment, and consumer protection. The text covers both technical and ethical considerations of AI deployment, greatly contributing to societal implications and legal governance of AI technologies.


Sector:
Politics and Elections
Government Agencies and Public Services
Judicial system
Healthcare
Academic and Research Institutions
International Cooperation and Standards
Nonprofits and NGOs
Hybrid, Emerging, and Unclassified (see reasoning)

The text addresses several different sectors where AI is employed. It is relevant to the Government Agencies and Public Services sector as it outlines standards, practices, and recommendations for the federal government on the use of AI systems. There are clear implications for accountability in potential legal and ethical frameworks that relate to the Judicial System, as well as elements that could impact Political and Elections through proposed consumer education. Healthcare implications may also arise through the use of AI systems for decision making. The text does not specifically pertain to Private Enterprises since the focus is more on governmental and regulatory frameworks, therefore receiving lower relevance in that sector.


Keywords (occurrence): artificial intelligence (110) foundation model (1) show keywords in context

Addressing America's Data Privacy Shortfalls: How a National Standard Fills Gaps to Protect Americans' Personal Information

Summary: This bill aims to establish a national standard for data privacy to address gaps in protection for Americans' personal information, enhancing security and clarity in regulations across various sectors.
Collection: Congressional Hearings
Status date: April 27, 2023
Status: Issued
Source: House of Representatives

Category:
Data Governance (see reasoning)

The text discusses the importance of data privacy and the need for a comprehensive, national standard to protect consumers' personal information. Although there are several references to privacy standards and sector-specific regulations, there is no direct mention of AI technologies or systems that require regulation or oversight. The primary focus is on data privacy legislation in general rather than AI-specific impacts. As such, while the relevance to categories can be inferred indirectly due to AI often operating on data, the explicit references needed to strongly associate this document with AI are absent, leading to lower scores across categories.


Sector:
Healthcare (see reasoning)

The text mainly addresses data privacy regulations and their impact on consumers, particularly regarding sectors like healthcare and education. While it touches on issues that could potentially affect various sectors employing AI technologies (data management, privacy), it doesn't specifically discuss the application or regulation of AI in these sectors. Therefore, while it has some relevance to data governance as it concerns managing personal data, it lacks sufficient direct references to AI to garner higher scores across the sectors.


Keywords (occurrence): automated (2) algorithm (1) show keywords in context

Departments of Labor, Health and Human Services, and Education, and Related Agencies Appropriations for Fiscal Year 2024

Summary: The bill allocates funding for the Departments of Labor, Health and Human Services, and Education for fiscal year 2024, emphasizing investments in healthcare, child services, and public health initiatives to enhance American well-being.
Collection: Congressional Hearings
Status date: March 22, 2023
Status: Issued
Source: Senate

Category: None (see reasoning)

The text primarily discusses the appropriations for various departments, with a focus on addressing health and human services, including mental health and behavioral healthcare. While there are mentions of substance use treatment and biomedical research, there are no explicit references to AI-related keywords such as Artificial Intelligence, Machine Learning, or Automated Decision systems. Thus, while the implications of technology in healthcare could indirectly relate to AI, the document does not directly address AI systems or legislation regarding their social impact, data governance, system integrity, or robustness.


Sector: None (see reasoning)

The text focuses heavily on the budget appropriations for various HHS initiatives without any specific mention of AI applications within any of the sectors described. While healthcare and mental health are significant topics covered, they do not explicitly connect to AI regulations or applications in the healthcare setting, nor do they provide insight into how AI relates to political or public services. Therefore, all sectors receive a score indicating no relevance.


Keywords (occurrence): artificial intelligence (2) automated (1) show keywords in context

United States SB2293: AI LEAD Act AI Leadership To Enable Accountable Deployment Act

Description: A bill to establish the Chief Artificial Intelligence Officers Council, Chief Artificial Intelligence Officers, and Artificial Intelligence Governance Boards, and for other purposes.
Summary: The AI LEAD Act establishes a Chief Artificial Intelligence Officers Council and governance boards to enhance responsible AI deployment, ensuring accountability, coordination, and adherence to democratic values across federal agencies.
Collection: Legislation
Status date: July 13, 2023
Status: Introduced
Primary sponsor: Gary Peters (2 total sponsors)
Last action: Placed on Senate Legislative Calendar under General Orders. Calendar No. 495. (Sept. 10, 2024)

Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)

The AI LEAD Act establishes governance structures for artificial intelligence (AI) within federal agencies, which directly correlates with issues of accountability, transparency, and ethical deployment of AI systems. The emphasis on the responsibilities of Chief Artificial Intelligence Officers and Governance Boards suggests that social implications, data governance concerns, system integrity, and robustness metrics are critical to this legislation, ensuring AI adoption is responsible and aligned with democratic values. The act advocates for risk management and oversight of AI technologies, clearly supporting implications relevant to social impact and system integrity. It also touches on robustness through mandates for compliance with standards and improvement of government operations using AI.


Sector:
Government Agencies and Public Services
Academic and Research Institutions
International Cooperation and Standards (see reasoning)

The AI LEAD Act is highly relevant to both Government Agencies and Public Services and the emerging regulatory framework surrounding AI usage in those sectors. By creating specific roles for Chief Artificial Intelligence Officers and Governance Boards, it aims at enhancing how federal agencies deploy AI technologies in a manner that is efficient, accountable, and protective of civil rights. It further addresses the integration of AI practices in governmental decision-making processes and operations, demonstrating interdependence on public trust and engagement with both federal and external stakeholders, including industry, academia, and other levels of government.


Keywords (occurrence): artificial intelligence (96) show keywords in context
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