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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.

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4840 results:


United States HB5576: Protect Working Musicians Act of 2023

Description: To empower independent music creator owners to collectively negotiate with dominant online platforms regarding the terms on which their music may be distributed.
Summary: The Protect Working Musicians Act of 2023 allows independent music creators to collectively negotiate licensing terms with major online platforms, addressing power imbalances and protecting their rights in music distribution.
Collection: Legislation
Status date: Sept. 19, 2023
Status: Introduced
Primary sponsor: Deborah Ross (4 total sponsors)
Last action: Referred to the House Committee on the Judiciary. (Sept. 19, 2023)

Category:
Societal Impact (see reasoning)

In this text, the contributions of AI are specifically highlighted in Section 2(3), where it mentions 'companies engaged in the development or deployment of generative artificial intelligence.' This indicates a legal premise for how AI can influence licensing and distribution in the music industry. The emphasis on collective negotiation against dominant platforms suggests a need for regulations around fairness and transparency as related to AI-generated content. Issues related to social impact arise from potential exploitation due to unequal bargaining power, particularly how AI systems might affect music creators' livelihoods and market structure. However, the legislation does not elaborate deeply on broader implications for AI itself but rather focuses on specific interactions between music creators and AI-using companies. Therefore, it shows relevance in Social Impact due to these implications but is less relevant in the other categories. Overall, the references to AI-related issues lean towards social impact without delving into measures of data governance, system integrity, or robustness.


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

The legislation directly impacts the music sector by addressing how independent music creators can collectively negotiate licensing terms with platforms, some of which deploy generative AI technologies. The mention of AI specifically highlights the intersection of music and technology. While it is clear that AI plays a role in the distribution landscape, the legislation's broader implications may reflect concerns in artistic industries. However, it does not adequately cover other sectors distinctly such as politics, government services, or healthcare, since its focus is uniquely on the music industry. The specific relevance to music creators gives it a higher score in this sector whereas it bears little relevance to the others identified.


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

PUBLIC BILLS AND RESOLUTIONS

Summary: Several public bills were introduced, addressing various issues such as banking regulations, executive compensation, environmental safety, and healthcare, aiming to improve financial governance and public welfare.
Collection: Congressional Record
Status date: June 20, 2023
Status: Issued
Source: Congress

Category:
Societal Impact
Data Governance (see reasoning)

The text contains multiple legislative bills and resolutions, with several of them specifically addressing issues related to artificial intelligence (AI). The mention of H.R. 4223, which proposes the establishment of an artificial intelligence commission, is a direct and explicit reference to AI. This makes the categories of Social Impact and Data Governance particularly relevant, as they can encompass issues such as ethical considerations, accountability, and oversight related to AI systems. Although there may be implications for System Integrity and Robustness due to the proposed oversight framework, they are not as explicitly relevant in this specific text as the former two categories. The other texts listed do not address AI at all, so they are irrelevant for scoring in the context of AI legislation. Therefore, we score Social Impact and Data Governance higher while rating the others lower.


Sector:
Government Agencies and Public Services (see reasoning)

The text outlines various bills and resolutions, with particular focus on legislation that can impact multiple sectors. H.R. 4223, regarding the establishment of an AI commission, is particularly relevant to the Government Agencies and Public Services sector as it relates to the regulation and oversight of AI utilization by government entities. Other bills mentioned primarily relate to financial services, agriculture, or general governance, which hold little relevance to any AI sector. Thus, the Government Agencies and Public Services sector is rated higher due to its clear connection to the proposed AI commission, while other sectors receive lower marks as they do not directly pertain to the content discussed.


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

How will we determine if a Tribe fails to meet the minimum work participation rate(s)?

Summary: The bill outlines penalties for Tribes that fail to meet federal requirements under the Tribal Family Assistance Grant program, focusing on work participation rates and proper use of funds.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text does not explicitly mention AI technologies or concepts, such as Artificial Intelligence, Algorithms, or any related terms like Machine Learning or Neural Networks. It focuses primarily on the assessment of Tribal Family Assistance Grant funds and compliance regulations. Therefore, it does not provide sufficient relevance to the categories of Social Impact, Data Governance, System Integrity, or Robustness related to AI. Considering the nature of the content, the categories do not align with its focus on administrative processes and compliance rather than AI-related implications or governance.


Sector: None (see reasoning)

The text mainly relates to standards and regulations within the context of Tribal Family Assistance Programs. It does not involve the sectors related to AI applications like Politics and Elections, Government Services, Healthcare, or any others listed. While there is a mention of data accuracy, it does not connect to any evocative AI-related frameworks or systems within these sectors, leading to minimal relevance to the sectors considered.


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

Form SDR

Summary: The bill establishes Form SDR, an application for registration as a swap data repository, detailing the required information, amendments, and instructions for compliance with the Commodity Futures Trading Commission regulations.
Collection: Code of Federal Regulations
Status date: April 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text pertains to the registration application for swap data repositories under the Commodity Futures Trading Commission. It primarily focuses on the administrative and operational requirements for such applications without addressing AI, its impacts, governance, or related system integrity. Terms related to AI such as 'Artificial Intelligence', 'Algorithm', or 'Automated Decision' do not appear in the document. Thus, it falls outside the scope of the categories identified.


Sector: None (see reasoning)

This text deals explicitly with the operational aspects and documentation needed for a swap data repository's application to the Commodity Futures Trading Commission. It does not discuss the role of AI in any sector such as politics, healthcare, or public services. There's a lack of direct or indirect references to AI utilization in public services, judicial systems, or private enterprises, making it infeasible to categorize under the specified sectors. Thus, relevance to the sectors is absent.


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

Request for designation.

Summary: The bill outlines procedures for sponsors to request designation of the appropriate FDA agency component for premarket review of combination products, particularly when jurisdiction is unclear.
Collection: Code of Federal Regulations
Status date: April 1, 2021
Status: Issued
Source: Office of the Federal Register

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

Daily Digest/CONGRESSIONAL PROGRAM AHEAD

Summary: The bill outlines the upcoming congressional activities for the week of September 12-15, 2023, detailing Senate confirmations, committee hearings, and legislative discussions focused on various national issues.
Collection: Congressional Record
Status date: Sept. 11, 2023
Status: Issued
Source: Congress

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

The text includes multiple references to AI, indicating the Senate's active engagement with AI-related legislation. The mention of hearings aimed at examining the need for transparency in Artificial Intelligence directly touches on social implications such as accountability and the potential impact of AI on society. Additionally, discussions about governing AI through acquisition and procurement hint at complexities of data governance and system integrity. The focus on AI in various Senate committees suggests significant legislative consideration for its societal impact, data management, and system reliability, qualifying the text for relevance across several categories while solidifying its basis in social impact, data governance, and system integrity.


Sector:
Government Agencies and Public Services
Judicial system
Hybrid, Emerging, and Unclassified (see reasoning)

The text details congressional activities that include hearings on AI in various contexts, such as transparency and governance. This implicates sectors like government agencies, public services, and the judicial system, as discussions around AI regulation could influence these spaces significantly. However, the text does not focus on specific sectors like healthcare or judicial decision-making and discusses broader implications instead. Due to its broad coverages of legislative processes rather than sector-specific implications, most categories will rate lower than significantly specialized sectors but still highlight relevant considerations for government and public services.


Keywords (occurrence): artificial intelligence (3) automated (1) show keywords in context

Tennessee SB1299: AN ACT to amend Tennessee Code Annotated, Title 4; Title 47 and Title 65, relative to social media.

Description: As introduced, requires a social media platform to provide certain information about its content and data management, business practices, and acceptable use policy; prohibits a social media platform from censoring the expression of a user who resides in this state based on viewpoint or geographic location; imposes other related requirements and prohibitions. - Amends TCA Title 4; Title 47 and Title 65.
Summary: The bill amends Tennessee law to regulate social media platforms, requiring them to disclose content management practices, maintain user rights, and provide complaint systems while prohibiting viewpoint discrimination.
Collection: Legislation
Status date: Jan. 31, 2023
Status: Introduced
Primary sponsor: Paul Bailey (sole sponsor)
Last action: Assigned to General Subcommittee of Senate Commerce and Labor Committee (March 20, 2023)

Category:
Societal Impact
Data Governance (see reasoning)

The text primarily concerns regulations surrounding social media platforms, including definitions and requirements related to algorithms used for content management. The term 'algorithm' is specifically mentioned in relation to how social media platforms rank and curate content. This is relevant to data governance as it addresses the operational aspects of data management within AI systems used by social media. Additionally, it addresses social impact through content moderation and censorship practices, impacting users' rights to expression and access. However, no sections explicitly focus on the robustness or integrity of the algorithms themselves. Hence, social impact and data governance categories are the most relevant.


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

This piece of legislation particularly impacts social media platforms, which are vital components of the digital landscape, affecting public discourse, user rights, and data management. It doesn't specifically address AI use in other sectors like healthcare or government agencies, nor does it indicate implications for the judicial system or international cooperation. However, it closely pertains to communication and information technology sectors due to its regulation of algorithms on platforms. Thus, 'Hybrid, Emerging, and Unclassified' would apply.


Keywords (occurrence): automated (2) algorithm (3) show keywords in context

How do I demonstrate initial compliance with the emissions limitations that apply to me?

Summary: The bill outlines procedures for demonstrating compliance with emissions limitations for iron and steel foundries, specifying monitoring requirements, operating limits, and the use of performance tests to ensure regulatory adherence.
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 compliance requirements for emissions limitations related to iron and steel foundries. There is no explicit mention of AI or related technologies like algorithms or automated systems in the provided text. The focus of the document is strictly on monitoring emissions and compliance with environmental regulations, without delving into the implications of AI's role in environmental monitoring or decision-making.


Sector: None (see reasoning)

The text is concentrated on environmental regulations for iron and steel foundries, detailing compliance processes necessary for emissions limits. There are no references to the application of AI technologies, political regulations regarding AI in industry, or AI's application in public sector environments. This text does not fit into any of the nine predefined sectors due to its highly specific focus on emissions compliance for industrial processes.


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

Disclosure of requested records to individuals.

Summary: The bill outlines procedures for individuals to access their records at the USPTO. It emphasizes timely responses, the right to assistance, and does not require justifications for access.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

This text primarily relates to the procedures for disclosing records to individuals, focusing on privacy rights and access to information. It does not contain explicit references to AI-related technologies such as Artificial Intelligence, algorithms, or automated decision-making processes. Therefore, it does not directly align with the definitions provided in the categories regarding AI's social impact, data governance, system integrity, or robustness. Any potential connections are very indirect and do not warrant categorization. Overall, the text focuses on individual access rights rather than the implications or governance of AI-related systems.


Sector: None (see reasoning)

The text addresses the procedures for individual requests concerning personal records but does not specify the use of AI in any sector. It does not detail how AI impacts government agencies or public services, nor does it provide insight into how AI is utilized or regulated within the context of privacy and access to information. As such, it does not fit any specific sector related to AI.


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

U.S. Department of Veterans Affairs Budget Request for Fiscal Years 2024 and 2025

Summary: The bill outlines the U.S. Department of Veterans Affairs budget request for fiscal years 2024 and 2025, emphasizing funding for healthcare, mental health, infrastructure improvements, and support services for veterans.
Collection: Congressional Hearings
Status date: March 23, 2023
Status: Issued
Source: House of Representatives

Category: None (see reasoning)

The text does not explicitly reference artificial intelligence (AI) or related concepts directly, such as algorithms, machine learning, or automated decision-making systems. It primarily focuses on budgetary allocations, healthcare services, and the operational needs of the Department of Veterans Affairs. Therefore, it does not address social implications of AI, nor does it highlight data governance, system integrity, or robustness specifically within AI contexts. Consequently, the relevance to the categories is minimal.


Sector: None (see reasoning)

The text discusses the budget requests for the Department of Veterans Affairs and its implications for veterans' services. While it may indirectly relate to government agency operations, there are no specific mentions or discussions about AI applications or regulations within those agencies. The focus is mainly on funding for veterans’ healthcare and related infrastructure rather than the detailed roles of AI in these contexts. Therefore, any relevance to specific sectors like Government Agencies and Public Services is weak.


Keywords (occurrence): automated (1)

TEXT OF AMENDMENTS

Summary: This bill aims to authorize appropriations for fiscal year 2024 for defense activities, while also proposing amendments to oppose financial assistance to China from development banks and redefine its status as a developing nation.
Collection: Congressional Record
Status date: July 12, 2023
Status: Issued
Source: Congress

Category: None (see reasoning)

The text provided is primarily focused on legislative amendments regarding economic assistance policies and international relations with the People's Republic of China. There are no explicit mentions or relevant discussions about AI, its technologies, impacts, or governance. Consequently, all categories regarding the social impact, data governance, system integrity, and robustness directly related to AI are irrelevant. Thus, the scores assigned to each category reflect this lack of relevance.


Sector: None (see reasoning)

Similar to the reasoning for the categories, the text does not pertain to AI applications within any of the specified sectors. The content involves legislative amendments related to fiscal policies and international economic relations, but it lacks any connection to political processes involving AI, government service enhancements through AI, AI in the judiciary, healthcare applications of AI, or any other identified sector. Hence, all assigned scores reflect this complete absence of relevance to the sectors.


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

Method modifications and analytical requirements.

Summary: The bill outlines procedures for requesting approval of alternative test methods for pollutant analysis under the Clean Water Act, ensuring modifications meet equivalency and quality control 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 addresses alternate test procedures for measuring pollutants and does not directly connect to the broader societal impacts or ethical considerations related to AI technologies. Therefore, it does not cover the nuances of AI's social impact on fairness, bias, or accountability, which would be essential for a high relevance score in this category. There are mentions of methods and procedures but no evidence of moral or ethical implications resulting from AI implementations Data governance is concerned with the accurate and secure management of data in AI systems; however, the text discusses analytical procedures without explicitly referencing data governance principles like accuracy, biases, or privacy issues related to AI data sets. Overall, while the text includes essential regulatory measures, they are not directly applicable to the data governance surrounding AI, warranting low relevance here. System integrity focuses on security, transparency, and control in AI systems. The detailed discussions about method modifications might tangentially infer a certain standard of integrity in analytical processes, but the core subject remains environmental testing rather than the integrity of AI systems themselves. Therefore, its relevance to this category remains low. In terms of robustness, which involves ensuring performance benchmarks for AI, there are mentions of equivalent performance and quality control measures related to analytical methods. However, these standards do not necessarily pertain to AI itself, but rather to environmental sampling methods, leading to a low relevance score for this category. Overall, no substantive references to AI technologies can be derived from this text.


Sector: None (see reasoning)

The text primarily discusses methodology related to environmental protection and analytical chemistry pertaining to pollutant testing. It does not mention or discuss AI within the political, legal, healthcare, or other sectors that involve the use or regulation of AI. Specifically, there’s no reference to AI applications, regulatory frameworks concerning AI deployment, or impacts on labor or public services that would associate it with meaningful relevance to any of the specified sectors. Therefore, each sector score is low due to the absence of AI-related content or implications.


Keywords (occurrence): automated (4) show keywords in context

MATH ALWAYS WINS

Summary: The "MATH ALWAYS WINS" bill emphasizes the urgent need to address the looming financial crises in Social Security and Medicare due to demographic shifts, warning that without action, future generations will face severe economic burdens.
Collection: Congressional Record
Status date: Feb. 28, 2023
Status: Issued
Source: Congress

Category: None (see reasoning)

This text primarily discusses economic issues and the mathematical implications of demographics on Social Security and Medicare. It touches on societal challenges related to workforce participation but does not delve into issues that pertain intricately to AI systems or their impact on social structures. While it does point to the need for talent and skills in the future, which can tangentially relate to AI developments, the core focus is not on AI itself nor does it suggest the introduction of AI solutions or safeguards. Consequently, it falls short of addressing the specific implications related to societal impact, data governance, system integrity, or robustness of AI systems.


Sector: None (see reasoning)

The text does not address any sector related to AI regulation or application. While it references economic issues and the importance of demographics in the workforce, it does not connect these elements to AI or related sectors such as government services, healthcare, or education. Thus, the lack of direct relevance to the predefined sectors leads to an overall score of 1 across all categories.


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

Allowable fees and charges; manufactured home unit.

Summary: This bill outlines the fees and charges associated with VA guaranteed loans for manufactured homes, ensuring veterans have clear warranties and protections while regulating allowable costs in the loan process.
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 primarily focuses on regulations regarding fees, charges, and warranty information for manufactured home loans under the Department of Veterans Affairs. It lacks any explicit references to AI technologies or their impacts. Therefore, while some general aspects surrounding financial transactions and legal compliance may have indirect implications for data governance or consumer protection in digital contexts, the absence of direct AI references means the relevance scores for the categories must be low. Each category does not mention or imply the use of AI systems, their safety, data management, or societal impacts distinctly enough to score higher than a 1.


Sector: None (see reasoning)

The text discusses the financing and management of manufactured home loans but does not focus on AI applications within any sector such as politics, government services, healthcare, or non-profit organizations. There is no mention of AI applications that would relate this text to any of the specified sectors. Thus, the relevance of the legislation to all nine sectors is minimal, resulting in a score of 1 across the board.


Keywords (occurrence): automated (1)

FINANCIAL SERVICES AND GENERAL GOVERNMENT APPROPRIATIONS ACT, 2024

Summary: The Financial Services and General Government Appropriations Act, 2024, allocates $25.279 billion in nondefense discretionary spending, focusing on fiscal restraint, agency accountability, and reducing regulatory burdens while cutting funding for many oversight agencies.
Collection: Congressional Record
Status date: Nov. 8, 2023
Status: Issued
Source: Congress

Category: None (see reasoning)

The text does not contain explicit references to Artificial Intelligence (AI) or any related technologies and terminologies. It focuses primarily on appropriations and policy regarding financial services and government operations without addressing any specific impacts, regulations, or considerations related to AI technologies. Therefore, it lacks relevance to all defined categories as it does not address social impacts, data governance, system integrity, or robustness in the context of AI.


Sector: None (see reasoning)

Similarly, there are no references to AI applications or regulations related to any of the nine sectors defined, including their potential impacts on politics, public services, healthcare, or private enterprises. The discussion remains rooted in general appropriations without exploring the influence of AI in these contexts. Therefore, all sectors score a 1, indicating no relevance.


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

NATIONAL DEFENSE AUTHORIZATION ACT FOR FISCAL YEAR 2024

Summary: The National Defense Authorization Act for Fiscal Year 2024 authorizes budget allocations for defense procurement, research, and personnel policies, aiming to enhance military readiness and support innovative technology integration.
Collection: Congressional Record
Status date: Sept. 5, 2023
Status: Issued
Source: Congress

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

The National Defense Authorization Act for Fiscal Year 2024 contains explicit references to artificial intelligence and automation, particularly concerning defense applications. The sections that mention AI indicate a clear intent to shape legislation around the use and implications of AI technologies, directly impacting social parameters like military capabilities and strategic oversight. This relevance is particularly pronounced in terms of security, transparency, and the potential implications of using AI technologies in defense systems. Hence, this has strong relevance for the categories of Social Impact, Data Governance, System Integrity, and Robustness.


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

The text contains multiple sections dedicated to the use of AI within military contexts, including the automation of defense technologies and implications for military procurement strategies. It addresses how AI is integrated into military operations, signifying a significant impact on the Government Agencies and Public Services sector. However, it only indirectly references implications for other sectors such as Healthcare and Politics, thus being more relevant to Military Applications within government.


Keywords (occurrence): artificial intelligence (132) machine learning (15) neural network (1) deep learning (1) automated (21) algorithm (1) show keywords in context

United States SB2722: Investing in Tomorrow's Workforce Act of 2023

Description: A bill to address the needs of workers in industries likely to be impacted by rapidly evolving technologies.
Summary: The "Investing in Tomorrow's Workforce Act of 2023" aims to support training for workers likely impacted by automation, enhancing skills for in-demand jobs and addressing economic inequalities.
Collection: Legislation
Status date: Sept. 5, 2023
Status: Introduced
Primary sponsor: Richard Durbin (5 total sponsors)
Last action: Read twice and referred to the Committee on Health, Education, Labor, and Pensions. (Sept. 5, 2023)

Category:
Societal Impact (see reasoning)

The text explicitly deals with legislation aimed at addressing the workforce impacts of automation and evolving technologies, specifically targeting workers who may face job dislocation due to these changes. The references to automation directly tie into the Social Impact category, as this legislation is framed as a response to potential workforce displacement, which has significant societal consequences. There is an emphasis on training programs to help workers transition into new roles and industries impacted by technology, mitigating negative social effects. For Data Governance, while the text mentions training services and skills for workers, it doesn't focus on data management or secure data practices related to AI. In terms of System Integrity, the text does not speak directly to the cybersecurity or oversight needs of AI systems. Similarly, the Robustness category is less applicable since it does not concern itself with benchmarks or compliance checks for AI systems but focuses more on workforce training and adaptability. Thus, the most relevant category is Social Impact due to its emphasis on addressing the social consequences of automation and job availability.


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

The bill is primarily focused on the workforce and is directly relevant to the Private Enterprises, Labor, and Employment sector, as it addresses the implications of automation on job displacement and the need for responsive training programs. It seeks to support workers in sectors likely to be affected by emerging technologies, thus, it also indirectly touches on the Government Agencies and Public Services sector, as implementation would involve federal support and oversight. However, the text doesn't directly reference regulations or the application of AI within the Judicial System, Healthcare, or academic contexts, nor does it engage with politics or collaborations at an international level. Therefore, the highest scores are for Private Enterprises, Labor, and Employment while Government Agencies may receive a lower relevance score.


Keywords (occurrence): autonomous vehicle (1) show keywords in context

Procedure for requesting records.

Summary: The bill establishes procedures for requesting records from the Office of Science and Technology Policy (OSTP) to support scientific research, detailing request format, requirements, and response protocols.
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 procedures for requesting records from the Office of Science and Technology Policy (OSTP) without addressing any specific implications of AI or its applications. While it mentions the use of automated systems and electronic formats, it does not delve into the societal impacts, data governance, system integrity, or performance benchmarks directly associated with AI. Therefore, the relevance to the AI categories is minimal.


Sector: None (see reasoning)

The text does not address any specific sector or how AI pertains to political activities, public services, or any other sector outlined. The mentions of automated information systems are very generic and do not directly connect to the application of AI in any defined area of governance or service delivery. Hence, most sectors remain irrelevant.


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

Investigating Pandemic Fraud: Preventing History from Repeating Itself

Summary: The bill focuses on investigating pandemic-related fraud, aiming to prevent future occurrences by analyzing how significant funds were misappropriated during COVID-19 relief efforts and improving oversight mechanisms.
Collection: Congressional Hearings
Status date: Oct. 19, 2023
Status: Issued
Source: House of Representatives

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

The text addresses issues related to pandemic fraud and discusses the role of data and technology, including artificial intelligence, for fraud detection and prevention. It highlights the need for effective measures to ensure accurate usage of taxpayer funds and the importance of data analytics in combating fraud. However, the primary focus remains on accountability and regulation rather than the broader societal impacts or ethical considerations of AI systems themselves, thus limiting its full relevance to the categories. Nevertheless, references to how technology can help in fraud prevention can touch upon broader social impacts and data governance aspects. Hence, each category should be evaluated for its relevance based on this nuanced understanding.


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

The text primarily talks about the implications of fraud in government programs, touching on transparency and accountability in government spending and practices. The mention of the use of data analytics and AI aligns particularly well with government operations where the integrity of data and systems is crucial for effective functioning. Although some points related to the judicial system do emerge regarding prosecution and enforcement aspects, they do not dominate the discussion. Therefore, some sectors are more relevant than others. Data governance is highly relevant due to the emphasis on secure data handling for fraud prevention, while government-related sectors take priority over others. Thus, scoring reflects this context.


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

Requirements for third-party servicers and lenders contracting with third-party servicers.

Summary: The bill establishes requirements for third-party servicers and lenders in administering federal student loan programs, ensuring administrative and financial responsibility, as well as compliance with regulations. It aims to protect federal funds and promote accountability.
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 focuses on regulation and administrative responsibilities related to third-party servicers and lenders in the context of financial and operational standards. It does not explicitly discuss any AI-related topics or technologies such as algorithms, machine learning, or automated systems. Instead, it deals primarily with financial responsibility and compliance standards in educational and federal financial aid programs. Therefore, the categories related to Social Impact, Data Governance, System Integrity, and Robustness are not applicable as the text lacks relevance to AI systems or their implications.


Sector: None (see reasoning)

The text outlines regulations specific to educational financial aid programs and the roles of third-party servicers. While it does indicate compliance requirements for financial management, it does not delve into how AI technologies might be utilized or regulated within these sectors. Hence, the sectors of 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, and Hybrid, Emerging, and Unclassified do not find relevant application in this text. As such, all sectors are deemed not relevant.


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