All Items
Legislation Only
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:


White House Policy on AI

Summary: The bill addresses the White House's AI policy aimed at promoting responsible AI development while mitigating risks. It emphasizes collaboration among government, industry, and academia to enhance AI safety and innovation.
Collection: Congressional Hearings
Status date: Dec. 6, 2023
Status: Issued
Source: House of Representatives

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

The text discusses the implications of artificial intelligence, particularly focusing on legislative frameworks that address its potential social impacts, such as algorithmic bias and data privacy concerns. It emphasizes accountability regarding AI's effects on individuals and the economy, particularly the potential harm from misinformation and cyber-attacks facilitated by AI, aligning strongly with the Social Impact category. The text also addresses data governance through the need for security measures in data management related to AI, directly tying AI's risks to this category. System integrity is referenced through mentions of oversight, transparency, and federal agency guidelines for AI deployment but is less explicitly emphasized compared to the other categories. Robustness is mentioned regarding AI performance benchmarks but is not a central focus, suggesting limited relevance. There is a need for robust AI regulatory frameworks, directly tying back to robustness but again is not the central theme. Therefore, the Social Impact and Data Governance categories receive the highest relevance scores, while System Integrity and Robustness score lower due to less emphasis in the text.


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

The text highlights the applications of AI across various sectors like healthcare, national security, and governmental efficiency, emphasizing AI's potential disruptions in these areas. It discusses government actions, leading to its relevance in the realm of Government Agencies and Public Services due to the focus on federal AI applications. Additionally, there is a mention of medical advances attributed to AI, aligning with the Healthcare sector’s focus, but the specifics needed for a strong alignment are weaker. The emphasis on legislation that guides AI's use in various sectors aligns less with specific sectors like Politics and Elections or Judicial System despite mentions of the political implications of AI, leading to lower scores for those categories. Academic and Research Institutions is mentioned in the context of investment in AI research but similarly does not receive a high score due to a broader focus on governmental action. There's less relevance for Nonprofits and the Hybrid category based on the provided information.


Keywords (occurrence): artificial intelligence (6) machine learning (1) deepfake (1) algorithm (2) show keywords in context

Diethylene glycol butyl ether and diethylene glycol butyl ether acetate.

Summary: The bill mandates health effects testing for diethylene glycol butyl ether and diethylene glycol butyl ether acetate, requiring manufacturers to submit testing plans and reports to the EPA on oncogenicity, toxicity, and neurotoxicity.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text provided is primarily focused on the regulation and testing requirements of specific chemical substances, namely diethylene glycol butyl ether (DGBE) and diethylene glycol butyl ether acetate (DGBA). While it includes extensive references to testing and reporting requirements for health effects, toxicity, and pharmacokinetics, there is no mention or direct relevance to AI-related topics like algorithms, machine learning, or automated decision-making systems. Thus, this legislation does not address social impacts, data governance, system integrity, or robustness in relation to AI technologies.


Sector: None (see reasoning)

The legislation is focused on environmental regulations about chemical testing rather than specific sectors such as politics, healthcare, or employment impacted by AI technologies. There is no mention of AI applications or regulations affecting any of the defined sectors such as the public service, academic institutions, or nonprofits. The text does not intersect with established frameworks for AI use and regulation in any recognized sector, rendering it irrelevant to these classifications.


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

United States SB2597: Digital Consumer Protection Commission Act of 2023

Description: A bill to amend the Clayton Act to establish a new Federal commission to regulate digital platforms, including with respect to competition, transparency, privacy, and national security.
Summary: The Digital Consumer Protection Commission Act of 2023 aims to establish a federal commission to oversee digital platforms, focusing on competition, transparency, privacy, and national security regulations.
Collection: Legislation
Status date: July 27, 2023
Status: Introduced
Primary sponsor: Elizabeth Warren (2 total sponsors)
Last action: Read twice and referred to the Committee on the Judiciary. (July 27, 2023)

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

The text primarily concerns the establishment of a Federal commission to regulate digital platforms, which includes provisions that directly involve the governance of algorithms and automated decision-making processes. The mention of algorithms, especially the description of how they process data for decision-making purposes, connects the text to AI technologies. This legislation aims at digital consumer protection, which addresses implications stemming from algorithms' effects on transparency, privacy, and national security. Therefore, it shows a significant relevance to Social Impact and Data Governance, while still relating moderately to System Integrity and Robustness through its provisions for transparency and compliance. Overall, it is not merely a peripheral mention but integrated into the central aims of the legislation.


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

The text provides a framework for regulating digital platforms, which falls within the realms of Government Agencies and Public Services as it includes oversight powers and duties related to algorithm governance and consumer protection. The legislation does not specifically address political campaigns, judicial applications, healthcare systems, or other sectors like employment or academia. However, it indirectly impacts all sectors through its implications for how digital platforms operate and protect consumers. It has moderate relevance to the Government Agencies and Public Services sector given its intent to fortify regulatory oversight mechanisms.


Keywords (occurrence): artificial intelligence (4) machine learning (1) automated (1) algorithm (3) show keywords in context

From Bait to Plate: How Forced Labor in China Taints America's Seafood Supply Chain

Summary: The bill addresses the impact of forced labor in China on America's seafood supply chain, revealing human rights abuses and urging government action to ensure accountability and improve labor conditions.
Collection: Congressional Hearings
Status date: Oct. 24, 2023
Status: Issued
Source: Congress

Category:
Societal Impact (see reasoning)

The text concerns forced labor practices within the seafood supply chain, particularly those linked to human rights violations related to Chinese labor practices. The majority of issues discussed are centered around enforcement of laws and regulations to prevent exploitation, though there is no direct reference to AI technologies or its applications. Therefore, Social Impact is relevant as it deals with the implications of forced labor and human rights on society, and some acts may involve AI for monitoring purposes. Data Governance receives a lower score as the text does not emphasize the management of data in AI but does imply some governance issues regarding sourcing practices and ethical considerations. System Integrity does not directly apply as there are no mentions of security or transparency of AI systems, and Robustness is also not applicable as no performance benchmarks for AI are discussed, underlining that AI does not play a central role in the text's content.


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

The document discusses forced labor within the seafood supply chain, primarily addressing the implications for labor rights, human rights, and national security, while referring to actions by government and industry to combat these issues. Politics and Elections could be tangentially related due to mentions of legislation affecting trade and procurement; however, AI application is not discussed directly within the text’s context. The Government Agencies and Public Services category is applicable since there are mentions of government enforcement actions related to labor rights violations, while the Labor and Employment category is extremely relevant due to the focus on labor exploitation in the seafood industry. Healthcare and Judicial System don't apply as there's no healthcare context or legal use of AI mentioned. Similarly, Academic and Research Institutions don't apply without mention of educational or research implications. International Cooperation and Standards can be included due to the international dimensions of seafood supply chains, but its relevance is not strong. Nonprofits and NGOs are relevant as they often address the issues of labor rights, while Hybrid Emerging and Unclassified are not applicable here.


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

United States HB5077: Creating Resources for Every American To Experiment with Artificial Intelligence Act of 2023 CREATE AI Act of 2023

Description: To establish the National Artificial Intelligence Research Resource, and for other purposes.
Summary: The CREATE AI Act of 2023 aims to establish the National Artificial Intelligence Research Resource (NAIRR) to enhance access to AI resources for diverse researchers and spur innovation in AI development.
Collection: Legislation
Status date: July 28, 2023
Status: Introduced
Primary sponsor: Anna Eshoo (62 total sponsors)
Last action: Referred to the House Committee on Science, Space, and Technology. (July 28, 2023)

Category:
Societal Impact
Data Governance (see reasoning)

The Creating Resources for Every American To Experiment with Artificial Intelligence Act of 2023 addresses multiple aspects related to the social impact of artificial intelligence. This includes increasing access to AI resources for researchers and historically underrepresented groups, indicating a commitment to equity and diversity in AI innovation. Furthermore, the act emphasizes enhancing capabilities in AI research, which relates to the social benefits of driving progress in technology for broader societal use. On the other hand, the Data Governance category is also relevant because the act provides for access and management of datasets and computational resources which involves considerations around the ethics, privacy, civil rights, and the fact that it mentions establishing standards for data management, which implies the need for secure and responsible data handling. However, System Integrity and Robustness focus more on technical and operational safety and performance standards than on accessibility and inclusion, thus their relevance to this specific act is lower. The final assessment concludes that the categories of Social Impact and Data Governance are most strongly aligned with the themes present within this legislative text.


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

The mentioned act emphasizes the importance of artificial intelligence in educational contexts, particularly through the establishment of educational tools and services, which makes it relevant to Academic and Research Institutions. It explicitly discusses improving access to AI resources for researchers and students; hence, this relates to educational opportunities and the advancement of AI knowledge in academic settings. Government Agencies and Public Services is also relevant as it establishes a national resource under the governance of federal entities like the National Science Foundation and emphasizes interagency coordination for AI research. While the act indirectly touches on STEM, employment and labor dynamics, and more general technology use across sectors, those connections are less explicit in the text provided. Overall, the final scoring reflects that the act strongly supports Academic and Research Institutions and Government Agencies and Public Services while being moderately relevant to other sectors.


Keywords (occurrence): artificial intelligence (31) show keywords in context

United States SB2346: Strategy for Public Health Preparedness and Response to Artificial Intelligence Threats

Description: A bill to require the Secretary of Health and Human Services to develop a strategy for public health preparedness and response to artificial intelligence threats, and for other purposes.
Summary: The bill mandates the Secretary of Health and Human Services to create a strategy for public health preparedness against artificial intelligence threats, aiming to enhance national health security.
Collection: Legislation
Status date: July 18, 2023
Status: Introduced
Primary sponsor: Ted Budd (2 total sponsors)
Last action: Read twice and referred to the Committee on Health, Education, Labor, and Pensions. (July 18, 2023)

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

The text clearly addresses the threats posed by Artificial Intelligence, which falls directly under the purview of the categories provided. The focus on public health preparedness and response in relation to AI indicates a significant social impact, as it deals with the consequences and risks to individual and community health. It establishes an accountability framework for the Secretary of Health and Human Services and a strategic approach to mitigate the misuse of AI technologies. Data governance is relevant because the effective management of AI data will likely be critical to combating health threats. System integrity is important here due to the need for secure and transparent AI systems in public health discussions. Robustness may be slightly relevant but is less emphasized given the broader focus on public health preparedness rather than specific AI performance benchmarks.


Sector:
Government Agencies and Public Services
Healthcare
Academic and Research Institutions
Hybrid, Emerging, and Unclassified (see reasoning)

The bill specifically targets the healthcare sector by focusing on public health preparedness in relation to AI threats. It includes provisions relevant to public health agencies and emphasizes the importance of a strategic response that considers AI's potential misuse. While it ranks highly for healthcare, its relevance to politics and elections, the judicial system, and other sectors is lower as the primary focus remains on public health responses rather than broad sector impacts or regulatory frameworks across multiple sectors.


Keywords (occurrence): artificial intelligence (10) show keywords in context

Implementation plan for regional haze.

Summary: The bill outlines emission standards for various pollutants in Wyoming, enforcing limits on particulate matter, nitrogen oxides, and sulfur dioxide. It aims to address regional haze and improve air quality through regulatory compliance.
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 discusses the implementation plan for regional haze, focusing on emission standards and compliance requirements for various pollutants. The text does not mention Artificial Intelligence (AI) or any related concepts or technologies. As such, it holds no relevance to the categories of Social Impact, Data Governance, System Integrity, or Robustness concerning AI systems and their impacts. Legislation related to the environmental impact does not directly connect with AI legislation, as environmental regulations do not encompass any considerations of AI's impact or data handling, nor oversight requirements specific to AI systems. Therefore, all categories are scored as not relevant.


Sector: None (see reasoning)

The text relates solely to environmental regulations and emissions standards, with no reference to the sectors defined. None of the sectors – Politics and Elections, Government Agencies and Public Services, Judicial System, Healthcare, Private Enterprises, Labor and Employment, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, or Hybrid, Emerging and Unclassified – fit the subject matter of emission standards or regional haze. The legislation does not discuss the use of AI in any of these sectors or any other topics related to them. Thus, all sectors are rated as not relevant.


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

New York A00539: Provides that a person may operate a fully autonomous vehicle on the public roads of this state without a human driver provided that the automated driving system is engaged and the vehicle meets certain conditions; defines terms; requires insurance and that such vehicle is registered as a fully a...

Description: Provides that a person may operate a fully autonomous vehicle on the public roads of this state without a human driver provided that the automated driving system is engaged and the vehicle meets certain conditions; defines terms; requires insurance and that such vehicle is registered as a fully autonomous vehicle; makes related provisions.
Summary: The bill allows the operation of fully autonomous vehicles on New York public roads without a human driver, establishes conditions for their use, and requires proper registration and insurance.
Collection: Legislation
Status date: Jan. 9, 2023
Status: Introduced
Primary sponsor: Kenneth Burgos (5 total sponsors)
Last action: enacting clause stricken (July 22, 2024)

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

The text is primarily focused on the regulation and operation of autonomous vehicles, which directly pertains to AI through the mention of automated driving systems. The relevance to the categories is assessed as follows: For Social Impact, the legislation addresses the implications of autonomous vehicles on safety, public use, and potential societal changes related to transport, thus scoring a 4 (Very relevant). In terms of Data Governance, while there are mentions of conditions and requirements, the emphasis lies more on operation than data management, placing it at a 2 (Slightly relevant). System Integrity is significant since the text establishes regulations around the operation of these systems, including safety and response procedures, earning a score of 4 (Very relevant). Similarly, robustness is implicated through the demand for performance standards and safety checks for autonomous systems, leading to a score of 4 (Very relevant). Overall, the key focus areas of the text indicate it concerns itself with how AI in vehicles impacts society, system safety, and operational performance.


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

The legislation strongly addresses how AI operates within the transportation sector, particularly focusing on autonomous vehicles. In the context of Politics and Elections, there's no direct applicability, which earns a 1 (Not relevant). Government Agencies and Public Services receive a score of 5 (Extremely relevant) as the legislation will directly affect how local and state agencies manage and regulate public road usage. For the Judicial System, while there may be indirect implications regarding liability and accountability, the text does not focus on judicial applications, leading to a score of 2 (Slightly relevant). In Healthcare, there are no connections, scoring a 1 (Not relevant). Private Enterprises, Labor, and Employment scores a 3 (Moderately relevant) since the operations could affect businesses offering transportation services. Academic and Research Institutions receive a score of 2 (Slightly relevant) at best, given implications for research into autonomous vehicle systems. International Cooperation and Standards is not addressed which results in a score of 1 (Not relevant). Nonprofits and NGOs have no mention in this context earning a score of 1 (Not relevant), while Hybrid, Emerging, and Unclassified sectors might consider autonomous driving technology as emerging, so it scores a 3 (Moderately relevant).


Keywords (occurrence): automated (24) autonomous vehicle (23) show keywords in context

Drug use review program.

Summary: The bill establishes a Drug Use Review (DUR) program aimed at ensuring appropriate drug therapy through prospective and retrospective reviews, educational initiatives, and standards to minimize misuse and enhance patient safety.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text discusses a Drug Use Review (DUR) program, which primarily focuses on ensuring appropriate therapy and adherence to clinical guidelines. While it mentions criteria for evaluating drug therapy, it doesn't explicitly relate to broad AI concepts such as machine learning algorithms or AI decision-making systems. It emphasizes predetermined standards, which may be assessed through potential automated systems, but the connection to the systematic governance or operational integrity of AI systems is tenuous. Thus, while there are implications that can be related to AI, the relevance is not strong enough to assign high scores in any category.


Sector:
Healthcare (see reasoning)

The legislation primarily pertains to healthcare practices, specifically the drug review processes ensuring safety and appropriate therapeutics. It does not directly engage with aspects of political regulation, AI in public services beyond healthcare, judicial review, private sector implications, or academic research. Thus, although relevant to the healthcare sector, its relevance does not extend significantly beyond that, leading to the conclusion that while connected, it's only slightly relevant to the other sectors.


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

Movement of passenger equipment with power brake defects.

Summary: The bill outlines regulations for the movement of passenger rail equipment with power brake defects, allowing limited, penalty-free transport for repair or scrapping while ensuring safety and compliance with federal standards.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text provided discusses regulations concerning the movement of passenger equipment with power brake defects, focusing primarily on safety conditions and operational guidelines for railroads. There are no explicit mentions or implications regarding AI technologies or methods. Since AI is not related to the principles of transportation equipment maintenance or safety protocols as covered in this text, it will not be impactful on issues such as the ethical implications of AI, data governance, system integrity, or robustness as these categories pertain to AI systems. Therefore, all categories will receive a score of 1 since they are not relevant to the content of the text.


Sector: None (see reasoning)

The text relates directly to rules and regulations governing passenger rail operations but does not touch on the use of AI technologies within government services or regulations specifically. There is a lack of references to any political system, public service dependency on AI, usage in the judicial system, healthcare technology, employment practices, or the role of academic institutions. Since the text is strictly about equipment related to rail transport, it will score a 1 across all sectors as they are not relevant to this legislative document regarding AI applications or implications.


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

Table of Frequency Allocations.

Summary: The bill outlines the Table of Frequency Allocations, detailing the allocation of radio frequencies in the U.S. and internationally, ensuring organized use and minimizing interference.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The provided text primarily discusses frequency allocations as outlined in regulatory documentation. It does not mention or reference anything explicitly related to Artificial Intelligence (AI), algorithms, or any AI-related technology. Thus, the four categories are not applicable as they don’t address the content within the text, which is focused solely on telecommunications regulations without intersecting with AI-related considerations.


Sector: None (see reasoning)

The text does not address the sectors specified, as it is entirely focused on frequency allocations in telecommunications. There are no references to Politics and Elections, Government Services, Healthcare, or any other sectors defined in the context of AI. The content is strictly regulatory and technical in nature without any implications or discussions about the use of AI in any given sector.


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

New York A03308: Enacts the "digital fairness act"; requires any entity that conducts business in New York and maintains the personal information of 500 or more individuals to provide meaningful notice about their use of personal information; establishes unlawful discriminatory practices relating to targeted adve...

Description: Enacts the "digital fairness act"; requires any entity that conducts business in New York and maintains the personal information of 500 or more individuals to provide meaningful notice about their use of personal information; establishes unlawful discriminatory practices relating to targeted advertising.
Summary: The "Digital Fairness Act" mandates businesses in New York handling personal data for 500+ individuals to provide clear notice about data usage and obtain opt-in consent, aiming to protect user privacy and prevent discrimination.
Collection: Legislation
Status date: Feb. 2, 2023
Status: Introduced
Primary sponsor: Catalina Cruz (2 total sponsors)
Last action: referred to consumer affairs and protection (Jan. 3, 2024)

Category:
Societal Impact
Data Governance (see reasoning)

The text of the Digital Fairness Act addresses several aspects related to social impact, particularly concerning the misuse of personal information and the potential harms such as discrimination and erosion of trust in digital interactions. It highlights the need for transparency, accountability, and fairness in how personal information is processed. This suggests a focus on the societal implications of AI systems, especially how algorithms can disproportionately affect historically disadvantaged groups. Therefore, social impact is rated highly. For data governance, the text explicitly discusses the management of personal information, consent requirements, and the need for accurate data practices, which aligns strongly with governance concerns in AI. System integrity is tangentially relevant since it deals with the manipulation and security of personal data through algorithms but is not the primary focus of the text. Robustness, on the other hand, is less applicable as the text does not primarily focus on performance benchmarks or auditing, which are core to this category. Therefore, it scores low. Overall, social impact and data governance emerge as the most relevant categories.


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

The text relates closely to multiple sectors. The Government Agencies and Public Services sector is relevant since the act discusses the use of automated decision systems by governmental entities, focusing on ensuring they operate fairly and transparently. The Private Enterprises, Labor, and Employment sector is also significantly applicable as it addresses businesses' responsibilities in using personal data ethically, especially in the digital advertising sphere. The lack of explicit references to AI applications in the Judicial System, Healthcare, or the remaining sectors leads to lower relevance for them. Academic and Research Institutions and Nonprofits and NGOs are also less relevant as the legislation primarily targets businesses doing commerce in New York. Therefore, Government Agencies and Public Services and Private Enterprises, Labor, and Employment are the most fitting sectors.


Keywords (occurrence): automated (97) algorithm (1) show keywords in context

Performance Specifications

Summary: The bill details performance specifications and testing procedures for continuous emission monitoring systems (CEMS) related to mercury and opacity in stationary sources, ensuring accurate measurements and regulatory compliance.
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 addresses performance specifications and analytical methods relevant to mercury emissions monitoring, rather than AI-related aspects. As such, it does not sufficiently engage with the broader implications of AI technologies, their societal impacts, data management, system integrity, or robustness. Each of the four categories focuses on specific aspects of AI legislation that deal with either the implications of AI technologies or their performance standards, none of which is addressed explicitly in the text.


Sector: None (see reasoning)

The text focuses specifically on performance specifications for continuous opacity monitoring systems and related analytical methods for measuring pollutants rather than any sector-specific applications of AI. Although it details the methodology and standards for measuring emissions, it does not engage with AI applications in governance or other sectors. As a result, the relevance to the sectors defined is minimal; it does not apply to politics, government services, healthcare, etc.


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

Nomination of Monica Bertagnolli to Be Director of the National Institutes of Health

Summary: The bill pertains to the nomination of Dr. Monica Bertagnolli as the Director of the National Institutes of Health, focusing on addressing healthcare challenges and pharmaceutical pricing issues.
Collection: Congressional Hearings
Status date: Oct. 18, 2023
Status: Issued
Source: Senate

Category: None (see reasoning)

The text primarily revolves around the nomination of Monica Bertagnolli as the Director of the National Institutes of Health (NIH) and the surrounding health care issues, notably the high costs of prescription drugs. Although there might be discussions related to the use of AI in healthcare, the specific text does not mention explicit AI-related terms such as 'Artificial Intelligence', 'Machine Learning', or similar keywords. Hence, its relevance to AI categories is minimal. The legislation regarding the health sector may involve implications for AI in medical research indirectly, but these connections are not made explicit enough to warrant high relevance for the categories defined.


Sector:
Government Agencies and Public Services
Healthcare
Academic and Research Institutions (see reasoning)

The text mainly discusses health care policies and the nomination of a significant figure in this field, rather than offering specific legislation or regulation regarding the sectors it describes. It touches upon topics relevant to the healthcare sector, especially in relation to drug pricing and healthcare system issues. Thus, while there is some indirect relevance considering the potential use of AI in healthcare research at NIH, the specific use or regulation of AI is not addressed. Therefore, its direct relevance to the sectors defined is low.


Keywords (occurrence): artificial intelligence (3) machine learning (4) show keywords in context

Rules and notices.

Summary: The bill outlines regulations for publishing service contract rules and notices by federal maritime carriers, ensuring clarity and compliance while listing exemptions for certain cargo types.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily discusses the rules and notices pertaining to service contracts in the maritime context. It does not address AI-related concepts or implications, such as social impact, data governance, system integrity, or robustness. The content is focused on regulatory frameworks and specific exclusions for transportation contracts. Keywords related to AI (Artificial Intelligence, Algorithm, etc.) are absent, indicating that no relevant connections exist to any of the defined categories.


Sector: None (see reasoning)

The text revolves around maritime regulations and the publishing of rules related to service contracts. While it might intersect with the government sector broadly due to its regulatory nature, there is no mention or implication of AI's use in political processes, governmental operations, or services directly. Therefore, it remains irrelevant to each sector category described.


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

Conversion Procedures

Summary: The bill establishes quality assurance and control measures for monitoring NOx, SO2, and CO2 emissions from gas and oil-fired peaking units, ensuring 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 focuses on emission monitoring and pollution control within the framework of environmental protection. It does not contain specific references to artificial intelligence (AI) or related technologies that would fall under the category definitions. The content is more technical regarding statistical procedures for determining emissions rather than discussing impacts related to AI, data governance, system integrity, or robustness in the context of AI systems. Therefore, all categories will yield low relevance scores as the text lacks direct engagement with AI concepts or concerns.


Sector: None (see reasoning)

The sectors being evaluated pertain mostly to the intersection of AI technology with various domains, including politics, government, and healthcare. The text, however, is strictly focused on emissions monitoring criteria and procedures governed by environmental legislation, with no mention of AI applications or implications in any sector, including politics, government services, healthcare, or otherwise. Consequently, all sector scores are expected to be very low due to the lack of AI context.


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

China (Executive Calendar)

Summary: The bill emphasizes the need for dialogue between the U.S. and China to address tensions, promote peace, and encourage China to act responsibly in global affairs.
Collection: Congressional Record
Status date: June 7, 2023
Status: Issued
Source: Congress

Category:
Societal Impact (see reasoning)

The text discusses the United States' approach to China, particularly in the context of international relations, including technological advancements. The mention of 'advancements in technology, like artificial intelligence, like quantum computing' indicates a recognition of the important role that these technologies play in global diplomacy and security. This directly aligns with the aspect of Social Impact as it hints at the impact (positive or negative) of AI on society and international relations. However, there is no explicit discussion of accountability, ethical implications, or specific social consequences tied to AI use, so the relevance is strong but not exhaustive. In terms of Data Governance, the text lacks detailed mention of data-related policies, secure collection, management or bias rectification in the context of AI. For System Integrity, while international relations are touched upon, there is insufficient emphasis on security, transparency or control measures concerning AI systems. Lastly, while there is a nod to technology standards, there are no specific benchmarks or performance measures discussed, so Robustness is not strongly relevant either.


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

The text predominantly addresses relations between the United States and China, with a focus on international diplomacy and military concerns rather than any specific sector. The mention of technology advancements implies relevance to sectors like Government Agencies and Public Services as well as International Cooperation and Standards, but it does not delve into specific applications in those sectors. It does not touch upon the regulation of AI in the context of Politics and Elections, Healthcare, or other sectors explicitly. Thus, the strongest relevance is to International Cooperation and Standards due to the diplomatic context and the mention of technological discussions, while others are less applicable.


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

Illinois HB0364: EMPLOYMENT-TECH

Description: Amends the Artificial Intelligence Video Interview Act. Makes a technical change in a Section concerning the short title.
Summary: The bill amends the Artificial Intelligence Video Interview Act in Illinois, facilitating clearer legal citation by updating a technical section of the Act.
Collection: Legislation
Status date: Jan. 12, 2023
Status: Introduced
Primary sponsor: Emanuel Welch (sole sponsor)
Last action: Rule 19(a) / Re-referred to Rules Committee (March 27, 2023)

Category:
Societal Impact (see reasoning)

The text primarily revolves around a technical amendment to the Artificial Intelligence Video Interview Act. It directly references 'Artificial Intelligence' in relation to video interviewing processes in the realm of employment. Therefore, the relevance of this text within the category of 'Social Impact' can be considered significant since it touches on employment practices affected by AI. However, because the text does not delve into broader implications such as consumer protections or societal issues, it is not rated at the highest level. For 'Data Governance', 'System Integrity', and 'Robustness', the text does not provide any clarity or specifications regarding data management or AI performance standards, which leads to lower relevance in those areas.


Sector:
Private Enterprises, Labor, and Employment (see reasoning)

The text explicitly addresses legislation concerning employment and specifically the use of AI in video interviews, making it directly relevant to the sector of employment and labor. It does not reference other specific sectors such as healthcare, government agencies, or the judicial system, nor does it explore broader international implications. Therefore, it is rated as highly relevant in terms of Private Enterprises, Labor, and Employment while being completely not relevant for other sectors.


Keywords (occurrence): artificial intelligence (2)

SENATE COMMITTEE MEETINGS

Summary: The bill outlines a system for scheduling and notifying Senate committee meetings and hearings, ensuring transparency and timely communication of legislative activities.
Collection: Congressional Record
Status date: June 7, 2023
Status: Issued
Source: Congress

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

The text discusses various Senate committee meetings and their agendas, including a specific meeting on artificial intelligence (AI) and human rights. Therefore, the relevance of the categories is evaluated based on the mention of AI and its implications. The discussion around AI in the context of human rights amplifies the social impact as it potentially addresses ethical concerns, implications of AI technologies, and their societal effects. Although specific data governance measures are not explicitly detailed, the mention of AI brings the issues of data accuracy and management into consideration, making it moderately relevant. System integrity is identified as relevant to ensure transparency and oversight in AI applications, particularly in sensitive areas such as human rights. Robustness is less relevant here as no specific benchmarks or performance standards for AI are mentioned in the text.


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

The mention of committee meetings related to AI points to the integration of AI in discussions within government frameworks, especially with regard to human rights, making it critically relevant to areas such as political oversight and public concern. However, the text does not provide substantial detail on how AI directly relates to sectors like healthcare or international standards, and thus those categories receive lower scores. The relevance to sectors such as Government Agencies and Public Services is pertinent since the legislative discussions might shape how government interacts with AI technologies, whereas Political and Elections reflects the concerns of technology in governance processes. Other sectors are less directly addressed, resulting in lower scores.


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

Enlistment waivers.

Summary: The bill establishes guidelines for enlistment waivers, detailing requirements for medical, dependent, conduct, and drug-related disqualifications, allowing case-by-case approvals by military authorities.
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 discusses the requirements and procedures for obtaining enlistment waivers in the military. It focuses on criteria related to medical conditions, conduct, and drug use without reference to AI technologies or concepts. Therefore, the categories concerning social impact, data governance, system integrity, and robustness do not apply as there is no mention of AI's societal effects, data management issues, system security, or performance benchmarks.


Sector: None (see reasoning)

The text does not address any sector related to politics, government, healthcare, or any other specified sectors as it strictly pertains to military enlistment waivers. Consequently, there are no mentions of AI applications or regulations within these sectors either. Therefore, all sectors receive a score of 1 due to this lack of relevance.


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