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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:


SENATE COMMITTEE MEETINGS

Summary: This bill establishes a computerized scheduling system for Senate committee meetings, requiring formal notification of meeting details and updates to enhance transparency and organization in legislative proceedings.
Collection: Congressional Record
Status date: June 12, 2023
Status: Issued
Source: Congress

Category: None (see reasoning)

The text discusses Senate committee meetings and scheduling but does not explicitly reference AI, algorithms, or any related technology. There is a mention of a Senate bill (S. 1865) that relates to automated systems interacting with the public, which could loosely fit into several categories. However, the focus is more on procedural governance than on the societal impact or regulatory needs concerning AI. There is insufficient substantive detail to warrant strong relevance to any of the categories provided. Therefore, all scores will be low, indicating a lack of clear focus on AI legislation even if the topic is touched upon.


Sector: None (see reasoning)

The text outlines agenda for various Senate committee meetings but does not address the use or regulation of AI specifically in the described sectors. Even in terms of governmental use of AI, which might be pertinent under the 'Government Agencies and Public Services' category due to a very indirect reference to automation, the connection is too weak to merit higher relevance. As such, all sector scores will be low.


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

Pennsylvania HB1663: Providing for disclosure by health insurers of the use of artificial intelligence-based algorithms in the utilization review process.

Description: An Act providing for disclosure by health insurers of the use of artificial intelligence-based algorithms in the utilization review process.
Summary: The AURA Act mandates Pennsylvania health insurers to disclose the use of artificial intelligence algorithms in their utilization review process, ensuring transparency and mitigating bias in healthcare decisions.
Collection: Legislation
Status date: Sept. 7, 2023
Status: Introduced
Primary sponsor: Arvind Venkat (30 total sponsors)
Last action: Referred to INSURANCE (Sept. 7, 2023)

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

The text contains specific provisions regarding health insurers' use of artificial intelligence-based algorithms, particularly addressing disclosure, transparency, and minimizing bias in utilization review. This directly concerns societal impacts, such as consumer protections and the ethical use of AI in healthcare settings, pointing to relevant issues of bias and accountability. Therefore, it holds significant relevance in the Social Impact category. The Data Governance category is also highly relevant as it relates to the secure management and accuracy of data sets used in AI algorithms, with clear mandates to ensure that data is bias-free, contributing to data governance. The System Integrity category is somewhat relevant because the text requires transparency and oversight of the algorithms to ensure they operate fairly and correctly, which relates to security and control of AI systems. However, the focus primarily lies within the parameters established in the first two categories, indicating these are the most pertinent with regards to AI applications in this context. Lastly, the Robustness category is not addressed, as there's no mention of performance benchmarks or regulatory compliance requirements for the algorithms. Hence, it was assessed as irrelevant.


Sector:
Healthcare (see reasoning)

The text primarily pertains to the healthcare sector, emphasizing health insurers' duties concerning AI in their utilization review processes. This aligns it deeply with the Healthcare sector, given that the act specifically focuses on disclosures meant to protect covered persons and providers in their dealings with insurers. It does not address other sectors such as Politics and Elections or Government Agencies and Public Services as the focus remains strictly on healthcare insurer practices. Therefore, the relevance score for Healthcare is extremely high. Other sectors are considered not applicable or unrelated, as the legislation does not intersect with those defined categories.


Keywords (occurrence): artificial intelligence (6) show keywords in context

Quality Assurance Procedures

Summary: The bill establishes quality assurance and control procedures for Continuous Emission Monitoring Systems (CEMS) to ensure accurate air quality data for compliance with environmental regulations.
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 mainly consists of procedural and technical instructions for Quality Assurance (QA) and Quality Control (QC) procedures related to gas continuous emissions monitoring systems (CEMS). There are no explicit references to AI technologies or their impacts on society, data governance, system integrity, or performance benchmarks associated with AI systems. Therefore, it is not relevant to the Social Impact, Data Governance, System Integrity, or Robustness categories.


Sector: None (see reasoning)

The text discusses quality assurance procedures related to emissions monitoring, which fall under environmental regulations but do not specifically address AI applications or regulations in political, healthcare, or employment contexts. Thus, it does not fit well with any of the predefined sectors. It mainly pertains to the environmental sector without mentioning AI, making it irrelevant to the specified sectors.


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

Commentary on Selected Sections of the Regulations on Criminal History Record Information Systems

Summary: The bill outlines regulations for the management, access, and dissemination of criminal history record information systems. It aims to enhance compliance and protect individual privacy while ensuring timely submission of arrest data by law enforcement agencies.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

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

The text primarily focuses on the regulations surrounding criminal history record information systems, their management, and the obligations of criminal justice agencies regarding data accuracy and dissemination. It discusses concepts such as automation in maintaining criminal history records and the importance of data privacy and security. However, it does not specifically delve into AI systems or technologies that utilize AI for these purposes, such as algorithms or automated decision-making processes. Consequently, it has moderate relevance to the categories associated with AI. Social Impact is somewhat relevant due to its emphasis on privacy and legal rights, while Data Governance is more applicable as the text discusses how data should be managed and protected. System Integrity is relevant in terms of ensuring that access to records is controlled and transparent. Robustness is less relevant as it doesn’t specifically address performance metrics or benchmarks for AI. Hence, while there are connections to AI concepts, the focus remains largely on legal and procedural aspects of criminal justice data without direct reference to AI technology or its implications.


Sector:
Government Agencies and Public Services
Judicial system (see reasoning)

The text is primarily concerned with aspects of the criminal justice system, detailing the management and dissemination of criminal history record information. It outlines the roles played by various agencies, particularly in legal contexts. Given that it addresses regulation and procedural compliance within criminal justice, it has strong relevance to the Judicial System and also extends to Government Agencies and Public Services due to the administrative nature of the discussed regulations. However, it does not touch upon other sectors such as Healthcare or Academic Institutions, making it less relevant in those domains. Similarly, while it has potential implications for data privacy and regulatory compliance, it does not directly address sectors such as Private Enterprises or International Standards. Overall, the text is most pertinent to the Judicial System, but also captures aspects relevant to Government Operations.


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

Automated slide stainer.

Summary: The bill regulates automated slide stainers and tissue processors, classifying them under Class I exemptions for premarket notification. It emphasizes performance validation and analytical testing to ensure diagnostic accuracy.
Collection: Code of Federal Regulations
Status date: April 1, 2023
Status: Issued
Source: Office of the Federal Register

Category:
Data Governance
System Integrity (see reasoning)

The text discusses automated devices used in medical diagnostic processes, specifically an automated slide stainer and tissue processor, as well as the regulatory requirements surrounding their validation and classification. In this context, the legislation indirectly touches upon the implications of automation in healthcare practices. While it emphasizes accuracy, clarity, and the specifications of automated devices, it lacks a direct focus on broader social impacts, data governance, system integrity related to AI, or specific benchmarks for robustness. However, there's a significant connection to healthcare processes, which is indicative of system integrity and data governance relating to the efficacy and ethical application of these automated devices in clinical environments.


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

The legislation clearly pertains to the healthcare sector as it addresses automated devices used for diagnostics in pathology. It defines the operational standards and classifications of devices that directly influence clinical practices. As such, it is relevant to both the healthcare sector and touches on standards expected from technologies employed in these settings. However, the text does not specify issues related to political processes, judicial concerns, public service regulations, private enterprise impacts, academic guidelines, international cooperation, or non-profit applications, limiting its scope to healthcare-specific considerations.


Keywords (occurrence): automated (5) show keywords in context

United States HB6791: Artificial Intelligence Literacy Act of 2023

Description: To amend the Digital Equity Act of 2021 to facilitate artificial intelligence literacy opportunities, and for other purposes.
Summary: The Artificial Intelligence Literacy Act of 2023 aims to enhance AI literacy by amending the Digital Equity Act, promoting educational opportunities and resources to prepare Americans for the AI-driven economy.
Collection: Legislation
Status date: Dec. 14, 2023
Status: Introduced
Primary sponsor: Lisa Rochester (4 total sponsors)
Last action: Referred to the Subcommittee on Communications and Technology. (Dec. 15, 2023)

Category:
Societal Impact (see reasoning)

The text explicitly discusses AI literacy, which implies a significant focus on the societal implications of AI and the need for educational frameworks to foster understanding among various communities. This directly aligns with the 'Social Impact' category due to its focus on equitable access to AI knowledge and the importance of literacy to mitigate bias and inform consumers. There are clear educational initiatives intended to prepare diverse populations for the integration of AI into society. The text does not mention specifics about data management or security directly, making 'Data Governance' less relevant. 'System Integrity' and 'Robustness' are also not directly addressed, as the focus is more on education rather than the technical aspects of AI systems themselves. Overall, the legislation emphasizes the social ramifications of AI, particularly for underserved communities, suggesting a very relevant connection to 'Social Impact.'


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

The text predominantly centers on the landscape of education influenced by AI, which pertains particularly to 'Academic and Research Institutions' due to its focus on improving AI literacy in these settings, including K-12 and community colleges. There are mentions of grants and partnerships that involve educational entities, supporting this classification. The 'Government Agencies and Public Services' sector could be considered slightly relevant given the mention of government support through grant programs, but it is not the core focus. The remaining sectors do not find significant alignment as they do not directly address AI transformation in political, legal, or commercial frameworks. Overall, 'Academic and Research Institutions' emerges as the most relevant sector.


Keywords (occurrence): artificial intelligence (17) show keywords in context

System performance requirements.

Summary: The bill establishes performance requirements and operational standards for electronic data filing with Customs, ensuring accuracy and confidentiality while outlining procedures for addressing non-compliance, including probation and suspension.
Collection: Code of Federal Regulations
Status date: April 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily revolves around system performance requirements and quality standards for electronic data filing within a government context, particularly related to Customs. While it mentions maintaining accuracy and operational standards, it does not explicitly address AI-related topics such as fairness, transparency, or algorithmic accountability, which would fall under the categories of Social Impact, Data Governance, System Integrity, or Robustness. Therefore, the relevance to these categories is minimal, as much of the focus is on procedural performance requirements rather than AI-specific concerns.


Sector:
Government Agencies and Public Services (see reasoning)

The text is relevant to Government Agencies and Public Services since it discusses the regulations around electronic data filing procedures that likely involve the use of technology in government operations. However, it does not directly engage with the specific use or regulatory frameworks for AI technologies within those contexts, leading to a low score in this sector. The other sectors such as Politics and Elections, 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 directly apply to the content of the text, as they focus on areas not discussed within the text.


Keywords (occurrence): automated (1)

Man and Machine: Artificial Intelligence on the Battlefield

Summary: The bill discusses the role of artificial intelligence (AI) in modern warfare, emphasizing the need for the U.S. to maintain technological leadership over adversaries like China to ensure national security and operational efficiency.
Collection: Congressional Hearings
Status date: July 18, 2023
Status: Issued
Source: House of Representatives

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

The document discusses the potential implications of artificial intelligence on military operations, highlighting both the benefits and risks associated with its use. It emphasizes topics like AI's influence on warfare, military strategies, and national security. These elements speak directly to the social impact of AI on military personnel and the ethical considerations surrounding its use in combat. It raises ethical questions about the use of AI in warfare, potential biases in AI systems, and accountability for AI-driven decisions, fitting well within the social impact category. Furthermore, it addresses AI's operational integrity and the necessity for secure, accountable deployment of AI technologies in the armed forces, which ties into system integrity and robustness as well. However, the focus is primarily on the societal and ethical impacts of AI in military contexts, particularly in how they affect individuals involved and the broader implications for democratic values and governance. Therefore, the relevance to each category is weighted accordingly, with social impact being most significant, followed by system integrity, robustness, and data governance in the context of military applications.


Sector:
Government Agencies and Public Services
International Cooperation and Standards
Hybrid, Emerging, and Unclassified (see reasoning)

The text primarily addresses the use of AI within the context of the military and national security, relating to governmental operations and public services at a strategic level. It highlights the significance of AI technologies such as algorithmic warfare and intelligence systems in enhancing military capability and ensuring national safety, making it very relevant to the Government Agencies and Public Services sector. Although it appears to touch on the use of AI in general societal contexts that could broadly impact various sectors, its focus on military applications is more pronounced. The references to economic implications and the necessity for clear policies regarding the deployment of AI further illustrate its relevance to governmental frameworks, while discussions about accountability and potential biases hint at broader regulatory concerns that affect multiple sectors, though mainly positioned within the military context.


Keywords (occurrence): artificial intelligence (29) machine learning (4) synthetic media (1) large language model (2) foundation model (1) algorithm (1) autonomous vehicle (1) show keywords in context

United States SB2222: Digital Defense Content Provenance Act of 2023

Description: A bill to require the Director of the Defense Media Activity to establish a course of education on digital content provenance and to carry out a pilot program on implementing digital content provenance standards, and for other purposes.
Summary: The Digital Defense Content Provenance Act of 2023 mandates the Defense Media Activity to create an educational program on digital content provenance and pilot programs to implement related standards, addressing digital content forgery challenges.
Collection: Legislation
Status date: July 10, 2023
Status: Introduced
Primary sponsor: Gary Peters (sole sponsor)
Last action: Read twice and referred to the Committee on Armed Services. (July 10, 2023)

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

The text explicitly addresses the use of artificial intelligence and machine learning techniques in the context of digital content forgery, highlighting the implications for securing and authenticating digital content. This connection is crucial to understanding the societal impact of AI technologies, especially regarding their potential for misuse. Furthermore, by laying out a course of education related to these technologies, the bill emphasizes creating standards that will influence how AI impacts security measures and information integrity. Therefore, the Social Impact category receives a high relevance score. Other categories related to governance of data, system integrity, and robustness are relevant to a lesser extent because the focus here is primarily on education and standards rather than detailed regulatory requirements or technical benchmarks.


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

Given the focus on the Defense Media Activity, the text has significant relevance to the Government Agencies and Public Services sector, as it pertains directly to government-sponsored educational programs and initiatives aimed at managing digital content. It also touches on the use of emerging technologies such as AI in the context of defense, implicating both the Judicial System and National Security sectors indirectly through its implications for misinformation. However, it does not have explicit relevance to the other sectors like Healthcare or Education. Thus, the Government Agencies and Public Services category scores the highest, reflecting its core focus.


Keywords (occurrence): machine learning (1) show keywords in context

Standard No. 202a; Head restraints; Mandatory applicability begins on September 1, 2009.

Summary: The bill mandates requirements for head restraints in vehicles to minimize neck injuries during collisions, applicable to various passenger vehicles manufactured after September 1, 2009.
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 safety standards related to head restraints in vehicles and does not include explicit mentions of AI-related technologies, systems, or methodologies. Consequently, the categories of Social Impact, Data Governance, System Integrity, and Robustness are not applicable. There are no references to the ethical implications of AI, data management practices, the security of AI systems, or the performance benchmarks for AI technologies, resulting in very low relevance for all categories.


Sector: None (see reasoning)

The text is highly focused on vehicle safety regulations and compliance options for head restraints, which does not fall into the predefined 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, or Hybrid, Emerging, and Unclassified. There is no mention or implication of AI application in any of these sectors, leading to a score of 1 for each.


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

United States HR649: Calling on the United States to champion a regional artificial intelligence strategy in the Americas to foster inclusive artificial intelligence systems that combat biases within marginalized groups and promote social justice, economic well-being, and democratic values.

Description: Calling on the United States to champion a regional artificial intelligence strategy in the Americas to foster inclusive artificial intelligence systems that combat biases within marginalized groups and promote social justice, economic well-being, and democratic values.
Summary: The bill calls for the U.S. to lead a regional AI strategy in the Americas that promotes inclusive systems, addressing biases against marginalized groups, and supporting social justice and democratic values.
Collection: Legislation
Status date: Aug. 8, 2023
Status: Introduced
Primary sponsor: Adriano Espaillat (sole sponsor)
Last action: Referred to the Committee on Foreign Affairs, and in addition to the Committee on Science, Space, and Technology, 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. (Aug. 8, 2023)

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

This resolution focuses heavily on the societal impact of artificial intelligence (AI), particularly in terms of promoting inclusive systems, combating biases, and supporting marginalized groups. The emphasis on social justice, economic well-being, and democratic values directly aligns with the parameters outlined for the Social Impact category. The resolution discusses the amplification of existing biases through AI and the necessity for diverse representation in AI systems which indicates a clear connection to fairness and bias metrics, enhancing the validity of its relevance. While it touches upon accountability and risks posed by AI, the primary focus is directed towards societal ramifications, thus making it highly relevant to the Social Impact category. The Data Governance category is less relevant as there are no specific mentions of data management practices, although the concern for bias could relate tangentially to data equity. System Integrity and Robustness show some relevance due to mentions of accountability and the importance of transparent and fair AI practices, but they are not the focal point of the text, making them less relevant than the Social Impact category.


Sector:
Politics and Elections
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
International Cooperation and Standards (see reasoning)

The resolution has strong implications for various sectors. In the context of Politics and Elections, it urges the U.S. to lead in the ethical governance of AI technologies, impacting electoral processes and public trust. The Government Agencies and Public Services category is also highly relevant due to its focus on the role of government in shaping AI policy and practice for the public good. The intersection of AI with social justice initiatives aligns with the discussion on the need for fairness in Private Enterprises, Labor, and Employment, albeit with slightly less emphasis. The text also acknowledges the role of international cooperation in governance and development, impacting the International Cooperation and Standards sector. However, since it doesn't directly focus on healthcare, judicial systems, academic institutions, or specific actions by nonprofits, those sectors remain less relevant. The content is particularly significant to the Politics and Elections and Government Agencies and Public Services sectors.


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

Oversight of Federal Agencies' Post-Pandemic Telework Policies Part II

Summary: The bill conducts oversight of federal agencies' telework policies post-pandemic, assessing their effectiveness in mission accomplishment and ensuring transparency in employee productivity and agency responses.
Collection: Congressional Hearings
Status date: Nov. 29, 2023
Status: Issued
Source: House of Representatives

Category: None (see reasoning)

The text revolves around the oversight of federal agencies' telework policies and their effectiveness. Although it lacks explicit context regarding AI technologies, it indirectly relates to the impact that automation and data-driven decision making prevalent in AI can have on telework and workforce management. Given that the document centers around governmental operations, it does not primarily address AI's societal impact, data governance, system integrity, or robustness directly. The references to data collection and agency performance may tangentially connect with AI-related systems, but they do not delve deeply into AI mechanisms or frameworks. Thus, the relevance of the categories remains on the lower side of the scale.


Sector:
Government Agencies and Public Services (see reasoning)

The text primarily discusses the functioning of federal agencies after the pandemic, with a focus on telework policies. There is no specific mention or discussion of AI in any of the agency operations or workforce management issues. Therefore, while the document may speak to broader topics related to government services and operations, it does not pertain directly to any Regulation or legislations about AI in the specific sectors identified. The discussions of effective and efficient workforce policies, while important, don't directly indicate relevance to the sectors described, like politics, healthcare, or the judicial system, among others. Thus, all sector scores reflect negligible direct relevance.


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

United States HB2670: Military Construction Authorization Act for Fiscal Year 2024 Black Sea Security Act of 2023 Preventing Child Sex Abuse Act of 2023 Department of Veterans Affairs Minor Construction Threshold Adjustment Act of 2023 Ensuring Interagency Cooperation to Support Veterans Act of 2023 Nuclear Fuel Secur...

Description: To authorize appropriations for fiscal year 2024 for military activities of the Department of Defense and for military construction, and for defense activities of the Department of Energy, to prescribe military personnel strengths for such fiscal year, and for other purposes.
Summary: The bill authorizes funding and outlines military activities for the Department of Defense and the Department of Energy for fiscal year 2024, including construction and personnel matters.
Collection: Legislation
Status date: Dec. 22, 2023
Status: Passed
Primary sponsor: Mike D. Rogers (2 total sponsors)
Last action: Became Public Law No: 118-31. (Dec. 22, 2023)

Category: None (see reasoning)

The text primarily focuses on military appropriations and authorization for various defense-related activities. Although it mentions artificial intelligence in some contexts related to military optimization, these mentions are minimal and geared toward specific applications, rather than a broader exploration of AI's societal implications, data governance, integrity, or robustness. Therefore, the overall relevance to the categories is low.


Sector:
Government Agencies and Public Services (see reasoning)

The text is mostly focused on military and defense operations, with some references to artificial intelligence. However, the legislation does not delve into significant implications for political processes, healthcare, judicial systems, or other sectors as defined. The mentions are largely operational rather than impacting or regulating specific sectors significantly, leading to a low relevance across sectors.


Keywords (occurrence): artificial intelligence (154) machine learning (19) automated (26) algorithm (1) show keywords in context

Federal Implementation Plan for the Billings/Laurel Area.

Summary: The bill establishes a Federal Implementation Plan for air quality control in the Billings/Laurel area, addressing sulfur dioxide emissions from specific petroleum refineries, ensuring compliance with the Clean Air Act.
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 mention or reference any aspect of artificial intelligence, algorithms, or automated systems. The focus is strictly on environmental regulations, emission monitoring, and compliance related to air quality standards, which makes it irrelevant to AI-related categories. It discusses laws regarding environmental protection but does not touch upon social aspects impacted by AI, data governance in AI systems, integrity of AI systems, or the robustness of AI benchmarks. There is no mention of accountability issues or frameworks governing AI systems within the content provided.


Sector: None (see reasoning)

Similar to the category assessment, the text does not pertain to any specific sector related to AI. Instead, it addresses environmental agencies' regulatory compliance and emission reporting for petrochemical facilities. There is no reference to AI applications in politics, government, public services, healthcare, or any relevant sector that would require categorization under the specified sectors. Therefore, it can be assessed as not relevant to these sectors.


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

Daily Digest/Final Resume of Congressional Activity

Summary: The bill summarizes legislative activity and executive nominations during the second session of the 117th Congress, detailing session duration, bills passed, and nominations confirmed. It serves to provide transparency regarding congressional workings.
Collection: Congressional Record
Status date: May 23, 2023
Status: Issued
Source: Congress

Category: None (see reasoning)

The text does not explicitly mention any keywords associated with AI such as Artificial Intelligence, Machine Learning, or Algorithm. It primarily describes legislative activities and statistics from Congress without providing any content that relates to the social, economic, or governance impacts of AI. Hence, all categories score low as there are no relevant mentions of AI-related policy or implications.


Sector: None (see reasoning)

Similar to the category reasoning, the text lacks any reference to AI applications or regulation across various sectors such as Politics, Government Services, Healthcare, and others. The content strictly focuses on legislative summaries without dealing specifically with AI's role in these sectors or related issues. Thus, each sector also receives the lowest score.


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

Waste, Fraud, and Abuse Go Viral: Inspectors General on Curing the Disease

Summary: The hearing addresses waste, fraud, and abuse in COVID relief programs, emphasizing the need for improved oversight and legislative measures to recover improper payments and protect taxpayer funds.
Collection: Congressional Hearings
Status date: March 9, 2023
Status: Issued
Source: House of Representatives

Category:
Data Governance (see reasoning)

The text primarily discusses the challenges of waste, fraud, and abuse in federal programs, particularly in the context of the COVID-19 pandemic. While it does not specifically mention AI technologies, the examination of improper payments and fraud may tangentially relate to automated systems and algorithms. Given that the use of data sharing and analytics was highlighted, there is a potential relevance to AI in the context of enhancing fraud detection and prevention mechanisms. However, due to the absence of direct references to AI or related technologies, the relevance remains limited.


Sector:
Government Agencies and Public Services (see reasoning)

The text mainly focuses on the operations of government agencies in addressing fraud related to pandemic relief programs. There are mentions of the roles of various inspectors general within federal agencies, and discussions of implementing better practices to ensure proper oversight and accountability. While the document references federal governance and oversight, its specific connection to any direct AI application within government services is underdeveloped. As such, the relevance to government agencies and public services resides primarily in the context of improving anti-fraud efforts rather than explicitly addressing AI integration within those processes.


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

United States SB688: DATA Act Data and Algorithm Transparency Agreement Act

Description: A bill to impose notice and consent requirements on internet platforms that use algorithms to manipulate the availability of content on the platform.
Summary: The DATA Act mandates that internet platforms using algorithms for content manipulation must obtain user consent for data collection and provide clear notifications about data use to enhance transparency and user rights.
Collection: Legislation
Status date: March 7, 2023
Status: Introduced
Primary sponsor: Rick Scott (sole sponsor)
Last action: Read twice and referred to the Committee on Commerce, Science, and Transportation. (March 7, 2023)

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

The text pertains to a legislative bill that targets the use of algorithms on internet platforms, focusing on notice and consent requirements for data collection. The use of the term 'algorithm' is directly tied to its implications for data governance, social impact, and system integrity through its manipulation of content availability and personal data use. However, it does not explicitly focus on AI systems nor does it touch on AI performance benchmarks, making relevance to robustness lower. Given that this bill seems primarily aimed at consumer protections, transparency, and fair practices regarding the use of personal data and algorithms, its strongest relevance is seen in data governance and social impact. System integrity is also significant due to the security and oversight it proposes for data handling.


Sector:
Government Agencies and Public Services (see reasoning)

This bill specifically addresses the implications of algorithm use on public platforms and its relationship with data privacy and fairness. While it inherently touches upon the areas of government in terms of regulation and enforcement mechanisms, its primary focus remains on the general digital landscape rather than on specific sectors like healthcare or politics, for instance. Therefore, while it does fit somewhat into the realm of government agencies, its broader applicability makes it more relevant to the digital and consumer sectors where AI and algorithms play a critical role.


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

TEXT OF AMENDMENTS

Summary: The bill amends aviation laws to enhance FAA programs, and includes provisions for transportation funding and restrictions on mask mandates during public health emergencies.
Collection: Congressional Record
Status date: Sept. 29, 2023
Status: Issued
Source: Congress

Category: None (see reasoning)

The amendments do not reference or address any AI-related terms or issues. They primarily focus on funding allocations and procedural amendments related to the Federal Aviation Administration, Customs and Border Protection, immigration enforcement, and health mandates concerning mask usage in various contexts. Therefore, none of the categories for Social Impact, Data Governance, System Integrity, or Robustness has any relevance to the text. This leads to a score of 1 across all categories.


Sector: None (see reasoning)

The text does not discuss or pertain to any AI-specific sector such as 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 any hybrid, emerging, or unclassified sector. It deals with amendments regarding federal funding and regulatory measures rather than AI applications or implications. Therefore, all sectors score 1 as well.


Keywords (occurrence): automated (2)

Michigan HB5143: Campaign finance: other; artificial intelligence; define. Amends sec. 2 of 1976 PA 388 (MCL 169.202). TIE BAR WITH: HB 5141'23

Description: Campaign finance: other; artificial intelligence; define. Amends sec. 2 of 1976 PA 388 (MCL 169.202). TIE BAR WITH: HB 5141'23
Summary: The bill amends Michigan's campaign finance laws by defining "artificial intelligence" and regulating its use in political activities, aiming for transparency and accountability in campaign financing.
Collection: Legislation
Status date: Dec. 31, 2023
Status: Passed
Primary sponsor: Matthew Bierlein (30 total sponsors)
Last action: Assigned Pa 264'23 (Dec. 31, 2023)

Category:
Societal Impact (see reasoning)

The text primarily focuses on defining artificial intelligence within the context of campaign finance, thus connecting it directly to issues related to regulation and accountability in political processes. It describes AI's capabilities which could affect decision-making and influence within this field, hinting at potential societal impacts, such as misinformation or bias in campaign activities. However, the text does not address data governance, system integrity, or robustness in depth, as it is mainly concerned with the legal definition and implications of AI in a specific area of legislation. Therefore, the most relevant category here is Social Impact, while the others receive lower relevance scores.


Sector:
Politics and Elections (see reasoning)

This legislation explicitly mentions AI in the context of campaign finance, thereby directly impacting Politics and Elections. Its focus on defining AI's role within political activity suggests significant implications on how political campaigns may employ or be influenced by AI, making it extremely pertinent to this sector. The other sectors do not have recognized relevance in this legislation as it does not address other areas such as healthcare, government services, or academic institutions directly.


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

Business Before the Senate (Executive Session)

Summary: The bill outlines the Senate's priorities as it reconvenes, emphasizing bipartisan cooperation to keep the government open, address pressing issues like AI regulation, and improve Americans' lives through various legislative efforts.
Collection: Congressional Record
Status date: Sept. 5, 2023
Status: Issued
Source: Congress

Category:
Societal Impact
Data Governance (see reasoning)

The text addresses multiple aspects of legislation and discussions regarding AI, indicating a focus on both the implications for society and the governance of data related to AI in the context of congressional action. The emphasis on constructing safe AI innovation, addressing various issues, and considering civil liberties suggests a high relevance to the Social Impact category. The mention of promoting innovation and discussing privacy and security in the context of AI points to strong relevance in Data Governance. The text doesn't delve deeply into system integrity or robustness, thus scoring lower in those areas. Overall, the discussions about AI's societal implications and the need for responsible governance indicate very high relevance to Social Impact and moderate relevance to Data Governance.


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

The text features discussions on AI in a governmental context, including the Senate's plans to host AI Insight Forums and engage with experts and stakeholders, indicating relevance primarily to the Government Agencies and Public Services sector. It does not specifically address AI in a legal or judicial context, nor does it focus on healthcare, political campaigns specifically, or private enterprise aspects in relation to AI, indicating lower relevance in those sectors. The conversations focus on utilizing AI for public benefit and addressing challenges, making it pertinent for Government Agencies and Public Services without extensive coverage of other sectors.


Keywords (occurrence): artificial intelligence (1)
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