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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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4160 results:


Massachusetts H1728: To implement the recommendations of the special commission on facial recognition technology

Description: For legislation to implement the recommendations of the special commission on facial recognition technology. The Judiciary.
Collection: Legislation
Status date: Feb. 16, 2023
Status: Introduced
Primary sponsor: Orlando Ramos (40 total sponsors)
Last action: Accompanied a new draft, see H4359 (Feb. 12, 2024)

Category:
Societal Impact
System Integrity (see reasoning)

The text discusses legislation focused on facial recognition technology, categorizing it as a form of biometric surveillance technology. This directly engages with societal concerns, particularly regarding how such technologies could impact privacy, civil rights, and potential misuse by law enforcement. The mention of regulations preventing unlawful biometric surveillance and requirements for accountability suggests a significant intersection with social impact. The aspect of holding law enforcement agencies accountable and ensuring transparency around facial recognition searches, including the implications of data use, is integral for evaluating the social ramifications of AI technologies. Therefore, Social Impact is rated very relevant. For Data Governance, while there are suggestions for documentation and reporting of facial recognition searches, the text focuses more on usage and accountability rather than specific data management policies, making it slightly relevant. System Integrity is pertinent due to the mentions of human intervention and regulatory requirements that enhance security and transparency in the usage of the technology. Robustness is less relevant as the text focuses more on legislative measures than on performance benchmarks or compliance audits for AI systems, so it is rated not relevant.


Sector:
Judicial system (see reasoning)

The text is primarily focused on the use of facial recognition technology, which is closely associated with the Judicial System due to its implications in law enforcement, investigations, and the legal consequences that arise from the use of such technology. It articulates how law enforcement can use facial recognition and sets rules for its application in judicial proceedings, highlighting its relevance to the sector. The discussion does not specifically engage with Politics and Elections or Government Agencies beyond their regulatory roles, as it primarily focuses on law enforcement agencies. It also does not touch upon Healthcare, Private Enterprises, Academic Institutions, International Cooperation, Nonprofits, or Emerging Sectors. Therefore, Judicial System is rated very relevant while the other sectors are rated not relevant as they are not addressed in the context of this legislation.


Keywords (occurrence): automated (5) algorithm (1) show keywords in context

United States SB4932: Department of Energy Quantum Leadership Act of 2024

Description: A bill to amend the National Quantum Initiative Act to provide for a research, development, and demonstration program, and for other purposes.
Collection: Legislation
Status date: Aug. 1, 2024
Status: Introduced
Primary sponsor: Richard Durbin (5 total sponsors)
Last action: Placed on Senate Legislative Calendar under General Orders. Calendar No. 633. (Nov. 21, 2024)

Category:
Data Governance
Data Robustness (see reasoning)

The 'Department of Energy Quantum Leadership Act of 2024' has substantial implications for AI, particularly through its explicit mention of machine learning within the context of quantum computing and advanced computational systems. It recognizes the intersection of quantum technologies with AI and machine learning applications, which suggests a direct impact on data processing and decision-making models. The initiative's purpose of advancing quantum science can have clear societal implications in terms of ethical uses and the governance of AI technologies as they converge with quantum capabilities. However, it does not directly address issues related to AI’s social impact, data governance, system integrity, or robustness without exploring their ramifications. Thus, it aligns partially with these categories of legislation but not predominantly in any single focus.


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

This legislation primarily pertains to the academic and research sectors through its focus on developing quantum information science and associated technologies. However, it also impacts governmental and enterprise sectors as it addresses workforce development, commercialization, and public institution collaboration in advancing quantum technology applications, which can indirectly influence AI sectors. The mention of AI and machine learning accelerators suggests a potential overlap with industrial applications but is not limited strictly to corporate practices. Thus, while the primary emphasis is academic, there are moderately relevant lines pertaining to government and private enterprise applications.


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

United States SB4664: Department of Energy AI Act

Description: A bill to require the Secretary of Energy to establish a program to promote the use of artificial intelligence to support the missions of the Department of Energy, and for other purposes.
Collection: Legislation
Status date: July 10, 2024
Status: Introduced
Primary sponsor: Joe Manchin (2 total sponsors)
Last action: Placed on Senate Legislative Calendar under General Orders. Calendar No. 631. (Nov. 21, 2024)

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

Given that there is no text available, it is impossible to determine explicit references to AI within the categories defined. However, since the bill involves promoting AI use within the Department of Energy, it can be interpreted as having implications for data governance (e.g., AI data management), system integrity (e.g., security and reliability of AI systems), and robustness (ensuring that AI used is effective and meets performance standards). The Social Impact category might have relevance depending on how the AI is applied in terms of public consequences, but this is less clear without additional context.


Sector:
Government Agencies and Public Services (see reasoning)

Without any specific elaboration available in the text, the relevance of sectors ties to the overarching theme of integrating AI in government operations, particularly concentrating on the Department of Energy. Since the bill directly addresses the establishment of a program within a governmental business frame, it can be slightly relevant to Government Agencies and Public Services, but other sectors like Private Enterprises might also connect if the AI solutions are considered for commercial applications. The lack of explicit references limits the strength of the links.


Keywords (occurrence): artificial intelligence (25) machine learning (2) automated (2) foundation model (1) show keywords in context

Illinois HB5918: AI USE IN HEALTH INSURANCE ACT

Description: Creates the Artificial Intelligence Systems Use in Health Insurance Act. Provides that the Department of Insurance's regulatory oversight of insurers includes oversight of an insurer's use of AI systems to make or support adverse determinations that affect consumers. Provides that any insurer authorized to operate in the State is subject to review by the Department in an investigation or market conduct action regarding the development, implementation, and use of AI systems or predictive model...
Collection: Legislation
Status date: Nov. 25, 2024
Status: Introduced
Primary sponsor: Bob Morgan (sole sponsor)
Last action: Filed with the Clerk by Rep. Bob Morgan (Nov. 25, 2024)

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

The text explicitly pertains to the use of AI systems within health insurance, directly addressing consumer impacts, oversight by regulatory bodies, and the need for accountability in decision-making processes involving AI. This clearly relates to the Social Impact category, as it addresses consumer protections against adverse outcomes based solely on AI determinations. Data Governance is highly relevant due to its focus on ensuring the accuracy and accountability of data used by insurers in AI systems, emphasizing the need for oversight of predictive models and algorithms. There is also a strong connection to System Integrity, as the legislation mandates human review of AI-driven decisions, ensuring transparency and control. Robustness is less relevant, as the text does not focus significantly on benchmarking AI performance or regulatory compliance assessments for AI outcomes.


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

The legislation specifically addresses the use of AI within the insurance sector, primarily focusing on health insurance practices. It establishes regulatory oversight for insurers' use of AI systems and predictive models, ensuring these practices adhere to fair standards impacting consumers. This makes it highly relevant to the healthcare sector, as it aims to protect patients and policyholders from adverse decisions made by AI systems. It is less relevant to sectors like Politics and Elections or International Cooperation and Standards, as there's no focus on political activities or global standards in AI regulation presented within the text.


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

California SB892: Public contracts: automated decision systems: procurement standards.

Description: An act to add Section 12100.1 to the Public Contract Code, relating to public contracts.
Collection: Legislation
Status date: Aug. 31, 2024
Status: Enrolled
Primary sponsor: Steve Padilla (3 total sponsors)
Last action: Enrolled and presented to the Governor at 3 p.m. (Sept. 11, 2024)

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

The text revolves around the procurement and risk management standards for automated decision systems (ADS) or automated decision tools (ADT) used by state agencies in California. It explicitly mentions the development of regulations concerning artificial intelligence (AI) and details about the risk management for AI systems in public contracts. This directly taps into issues relating to social impacts of AI systems on various critical sectors, making it very relevant to the category of Social Impact. Furthermore, there are clear processes described for data governance through requirements for risk assessment, security controls, and compliance with privacy laws, thus making it similarly relevant for Data Governance. The inclusion of clauses mandating risk assessments and monitoring for system integrity outlines the need for control over these AI systems, which positions this text strongly in the System Integrity category. The legislation also discusses ensuring that AI systems are effective and compliant with established standards, thus making it pertinent to the Robustness category as well. All these reasons lead us to conclude that the text warrants high relevance across all categories mentioned.


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

The text refers to the implications of automated decision systems in various social domains, including access to employment, education, and even housing. This indicates a substantial relevance to sectors such as Government Agencies and Public Services, where AI may be utilized in delivering public services and managing government operations. The clear delineation of AI roles in areas such as health care, criminal justice, and higher education also suggests relevance to those sectors, particularly as the implications of AI in these areas can be critical. However, the text does not explicitly touch on all sectors, leaving Healthcare, Private Enterprises, and International Cooperation as less relevant. Judicial System relevance is also moderate but based on its focus on how decisions derived from AI affect legal outcomes and due process. Overall, it’s fair to assign high relevance to Government Agencies and Public Services, and moderately high to Judicial System and Healthcare due to the broader implications.


Keywords (occurrence): artificial intelligence (5) machine learning (1) automated (5) show keywords in context

United States HB8447: American Agricultural Security Act of 2024

Description: To direct the Secretary of Agriculture to establish centers of excellence for agricultural security research, extension, and education, and for other purposes.
Collection: Legislation
Status date: May 17, 2024
Status: Introduced
Primary sponsor: Don Bacon (3 total sponsors)
Last action: Referred to the House Committee on Agriculture. (May 17, 2024)

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

The text highlights the establishment of centers of excellence for research, extension, and education in agricultural security, with a specific inclusion of 'artificial intelligence' in the realm of 'digital agriculture.' This signals the recognition of AI's role in enhancing agricultural practices. Consequently, the relevance of Social Impact stems from potential societal benefits tied to AI in agriculture, including workforce development and community engagement. For Data Governance, while the text does not explicitly address data management or privacy associated with AI, the application of AI in agriculture would require careful data policies and governance. System Integrity is moderately relevant due to the emphasis on cybersecurity, which intersects with AI's capabilities in safeguarding agricultural data and processes. Robustness is less relevant as the text does not focus on performance benchmarks for AI systems directly. Overall, Social Impact and Data Governance receive higher relevance scores, whereas System Integrity is acknowledged as relevant due to the cybersecurity emphasis.


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

The mention of 'artificial intelligence' in the context of digital agriculture makes it relevant to the sector of Private Enterprises, Labor, and Employment, as AI technologies are poised to influence agricultural labor practices and industry standards. Government Agencies and Public Services see relevance through the involvement of governmental departments and educational institutions in establishing excellence centers. Additionally, there might be connections to Academic and Research Institutions due to the emphasis on research and education activities. However, the text does not delve deeply into political implications, the judicial framework around AI, or specific healthcare applications, resulting in lower scores for those sectors. Overall, Private Enterprises, Labor, and Employment has significant applicability, supported by Government Agencies and Public Services and Academic and Research Institutions receiving moderate scores.


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

Tennessee HB2325: AN ACT to amend Tennessee Code Annotated, Title 4, relative to the artificial intelligence advisory council.

Description: As enacted, enacts the "Tennessee Artificial Intelligence Advisory Council Act." - Amends TCA Title 4.
Collection: Legislation
Status date: May 29, 2024
Status: Passed
Primary sponsor: Patsy Hazlewood (3 total sponsors)
Last action: Effective date(s) 05/21/2024 (May 29, 2024)

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

The text discusses the creation of the Tennessee Artificial Intelligence Advisory Council, which focuses on guiding the state's use of artificial intelligence to improve government services and leverage AI for economic benefits. The emphasis on ethical use, economic implications, and transparency aligns closely with the impact of AI on society and individuals (Social Impact), as well as the governance and accuracy in the handling of AI and its data (Data Governance). Furthermore, there are references to expectations of governance frameworks and evaluation of AI risks, which speak to systemic integrity. The document does not delve deeply into benchmarking performance or compliance standards, thus Robustness is less relevant in comparison to the other categories.


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

The bill is highly relevant to several sectors, particularly the Government Agencies and Public Services as it directly pertains to the use of AI in government. The focus is on how AI can improve the efficiencies of state and local government services and goes deeper into workforce development and economic implications of AI, suggesting a somewhat relevant connection to Private Enterprises, Labor, and Employment. There are also touchpoints on education and research related to AI, which lend some relevance to Academic and Research Institutions. However, other sectors like Politics and Elections, Healthcare, and Judicial System do not apply directly to the text’s content, thus receiving a lower score.


Keywords (occurrence): artificial intelligence (22) show keywords in context

California AB3061: Vehicles: autonomous vehicle incident reporting.

Description: An act to add Section 38760 to the Vehicle Code, relating to vehicles.
Collection: Legislation
Status date: Aug. 28, 2024
Status: Enrolled
Primary sponsor: Matt Haney (2 total sponsors)
Last action: Senate amendments concurred in. To Engrossing and Enrolling. (Ayes 65. Noes 4.). (Aug. 28, 2024)

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

This text focuses on autonomous vehicles and their regulation, particularly in the context of incident reporting. Key terms related to AI, such as 'autonomous mode', indicate relevance to AI's social impact due to the implications on safety, liability, and discrimination, particularly against vulnerable road users. The reporting and oversight requirements suggest a framework for accountability and safety in AI operations, affecting individuals and society as a whole. Understanding how AI technologies can cause potential harm or benefit to users aligns with the Social Impact category, thereby indicating a strong relevance. The Data Governance category is also relevant, as it discusses the collection and management of data related to incidents, including mandates for transparent reporting. System Integrity is considered relevant because the provisions describe specifications for operational performance and the requirement for manual override in problematic situations. However, the focus is primarily anecdotal and regulatory, without delving into internal security measures for the AI systems themselves, which limits its relevance in this category. The Robustness category is less applicable here since the text does not specifically address performance benchmarks for AI systems, and instead focuses on reporting mechanisms, thus limiting its relevance in this category as well.


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

The text primarily addresses legislation concerning autonomous vehicles, directly relevant to several sectors. In the Politics and Elections sector, there is limited relevance, as the text does not discuss AI's role in elections or political campaigns. However, Government Agencies and Public Services is highly relevant as it speaks to how the DMV and other agencies must manage reports and data for the incident reporting of autonomous vehicles. The Judicial System is slightly relevant as it touches on accountability, though it primarily focuses on vehicle regulation rather than judicial applications. The Healthcare sector is not applicable, as there is no mention of healthcare applications. Within the Private Enterprises, Labor, and Employment sector, it reflects the implications for manufacturers and their operational obligations, but does not strongly address employment or corporate governance perspectives. Academic and Research Institutions have minor relevance as the legislation does not engage educational contexts specifically, even though innovations may come from research. International Cooperation and Standards does not receive an ample mention in this text, thus scoring low. Nonprofits and NGOs have little relevance unless involved in advocacy or disability issues related to the legislation, while Hybrid, Emerging, and Unclassified could apply given the innovative nature of autonomous vehicles, yet again lacks a strong basis here.


Keywords (occurrence): automated (2) autonomous vehicle (41) show keywords in context

New Hampshire HB1500: Relative to prohibiting the unlawful distribution of misleading synthetic media.

Description: Relative to prohibiting the unlawful distribution of misleading synthetic media.
Collection: Legislation
Status date: Dec. 11, 2023
Status: Introduced
Primary sponsor: Linda Massimilla (11 total sponsors)
Last action: Refer for Interim Study: Motion Adopted Voice Vote 03/14/2024 House Journal 8 P. 5 (March 14, 2024)

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

The legislation centers on the unlawful distribution of misleading synthetic media and explicitly links the definition of synthetic media to artificial intelligence algorithms. This directly relates to the 'Social Impact' category as it addresses potential harm from misleading AI-generated content and its implications for public trust and election integrity. It also connects to 'Data Governance' since unauthorized usage of AI to create misleading content can involve management of data rights and personal consent. The aspect of accountability and penalties in the bill aligns with 'System Integrity,' as it seeks to establish clear rules for AI systems that could mislead individuals in significant ways, which involves transparency and control. The robustness of these measures signifies a compliance effort with standards in AI content distribution. Overall, this legislation addresses both the societal consequences of AI media and accountability within AI governance.


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

The text is closely related to the sector of politics and elections, as it explicitly speaks about misleading synthetic media that can influence election outcomes. It addresses the deployment of AI in creating media that could harm electoral integrity, reflecting legislative intent in regulating AI's role in politics. Furthermore, it implicates government agencies and public services as the enforcement and compliance measures would likely involve public bodies. However, less direct relevance to other sectors such as healthcare or private enterprises suggests that while the bill intersects with several sectors, its core focus remains on political implications and public governance.


Keywords (occurrence): artificial intelligence (1) synthetic media (22) show keywords in context

United States SB4178: Future of Artificial Intelligence Innovation Act of 2024

Description: A bill to establish artificial intelligence standards, metrics, and evaluation tools, to support artificial intelligence research, development, and capacity building activities, to promote innovation in the artificial intelligence industry by ensuring companies of all sizes can succeed and thrive, and for other purposes.
Collection: Legislation
Status date: April 18, 2024
Status: Introduced
Primary sponsor: Maria Cantwell (7 total sponsors)
Last action: Committee on Commerce, Science, and Transportation. Ordered to be reported with an amendment in the nature of a substitute favorably. (July 31, 2024)

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

The text discusses the establishment of artificial intelligence standards, evaluation tools, and a safety institute, emphasizing the relevance to Social Impact through its focus on enhancing AI standards for public benefit. It also fits under System Integrity as it addresses measures for ensuring the reliability and security of AI systems through the collaboration of various federal agencies and development of best practices. Data Governance is relevant as the bill includes mandates for developing guidelines related to the secure and ethical use of AI, thus ensuring data practices are considered. Robustness is also pertinent as the text aims to create metrics and benchmarks for evaluating AI performance, including compliance with international standards. Overall, the text aims to enhance the safety, governance, and utility of AI technology, making all categories interconnected and significantly relevant to the legislation.


Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Academic and Research Institutions
International Cooperation and Standards
Nonprofits and NGOs (see reasoning)

This legislation is relevant across multiple sectors but most prominently in Government Agencies and Public Services as it discusses the application of AI standards and evaluation tools for improving governmental AI service delivery. International Cooperation and Standards also holds relevance due to the mention of partnerships and collaborations with international entities to align AI standards. Academic and Research Institutions are included as the text refers to partnerships with universities for research purposes. The text does not specifically target any sectors such as Politics and Elections or Healthcare, resulting in lower scores for those areas. Overall, it addresses the intersection between AI innovation, government efficiency, and international collaboration.


Keywords (occurrence): artificial intelligence (95) machine learning (1) automated (1) algorithm (1) show keywords in context

Tennessee HB2163: AN ACT to amend Tennessee Code Annotated, Title 39 and Title 40, relative to the sexual exploitation of children.

Description: As enacted, specifies that for the purposes of sexual exploitation of children offenses, the term "material" includes computer-generated images created, adapted, or modified by artificial intelligence; defines "artificial intelligence." - Amends TCA Title 39 and Title 40.
Collection: Legislation
Status date: May 13, 2024
Status: Passed
Primary sponsor: Mary Littleton (3 total sponsors)
Last action: Effective date(s) 07/01/2024 (May 13, 2024)

Category:
Societal Impact (see reasoning)

The text discusses legislation that involves AI in the context of preventing sexual exploitation of children. It emphasizes the creation and modification of computer-generated images using AI, linking AI to potential harmful content. This directly impacts societal values, norms, and safety, reflecting strong relevance to the Social Impact category. It does not focus on data governance, system integrity, or robustness, as it does not discuss data management, system security, or performance benchmarks in the AI context. Thus, Social Impact is rated highly, while the other categories score low.


Sector: None (see reasoning)

The text primarily addresses the legal implications of AI in relation to child exploitation, emphasizing the role of AI in generating harmful content. This has a direct implication for laws concerning societal norms and values, but it does not specifically pertain to any of the defined sectors like politics, public service, healthcare, or others. Therefore, the score for the sectors remains low, as it does not directly address those areas, with the exception of implications for potential impacts on children in both the Public Service and Nonprofits sectors being slightly relevant due to its protective nature.


Keywords (occurrence): artificial intelligence (5) automated (1) show keywords in context

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

Description: A bill to provide a framework for artificial intelligence innovation and accountability, and for other purposes.
Collection: Legislation
Status date: Nov. 15, 2023
Status: Introduced
Primary sponsor: John Thune (8 total sponsors)
Last action: Committee on Commerce, Science, and Transportation. Ordered to be reported with an amendment in the nature of a substitute favorably. (July 31, 2024)

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

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


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

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


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

District of Columbia B25-0930: Consumer Health Information Privacy Protection Act (CHIPPA) of 2024

Description: As introduced Bill 25-930 would require regulated entities to establish and make publicly available, a consumer health data privacy policy governing the collection, use, sharing, and sale of consumer health data with the consumer’s consent. It would establish additional protections and consumer authorizations for the sale of personal health data. It also establishes that regulated entities can only collect health data that is necessary for the purposes disclosed to the consumers and makes vio...
Collection: Legislation
Status date: July 12, 2024
Status: Introduced
Primary sponsor: Phil Mendelson (sole sponsor)
Last action: Referred to Committee on Health (Sept. 17, 2024)

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

The Consumer Health Information Privacy Protection Act (CHIPPA) clearly addresses the secure and responsible collection, use, and sharing of consumer health data, which naturally intersects with data governance. The legislation focuses on ensuring consent, data privacy, and transparency when it comes to managing health data, which is crucial in the context of AI collecting and processing personal health information. Furthermore, while the text contains some principles related to system integrity regarding ensuring consent and transparency, it does not explicitly mandate security protocols or oversight measures applicable to AI systems, leading to a lower relevance score for this category. The robustness category is less applicable as it does not address the performance benchmarks or auditing processes of AI systems directly, making it less relevant. The social impact category is more pertinent since the legislation seeks to protect consumers from potential harm from AI practices related to health data misuse and assures the ethical handling of personal information, which can influence societal trust in digital health platforms.


Sector:
Healthcare (see reasoning)

The CHIPPA Act specifically addresses consumer health data, which is inherently tied to the healthcare sector. The legislation outlines critical protections for consumer health data, requiring organizations to establish privacy policies and ensure informed consent. Its implications are significant for healthcare institutions and related entities that utilize AI technologies for processing health data. While it touches on aspects relevant to government agencies through the regulatory framework it sets, the primary focus remains on healthcare, thus making it most pertinent to that sector. Other sectors such as politics and elections or academic institutions are not directly addressed, and while the implications of data governance can influence various sectors, the clear focus of the legislation confines its primary relevance to healthcare.


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

United States SB4596: Artificial Intelligence Public Awareness and Education Campaign Act

Description: A bill to require the Secretary of Commerce to conduct a public awareness and education campaign to provide information regarding the benefits of, risks relating to, and the prevalence of artificial intelligence in the daily lives of individuals in the United States, and for other purposes.
Collection: Legislation
Status date: June 20, 2024
Status: Introduced
Primary sponsor: Todd Young (2 total sponsors)
Last action: Committee on Commerce, Science, and Transportation. Ordered to be reported without amendment favorably. (July 31, 2024)

Category:
Societal Impact (see reasoning)

Given that the text discusses a bill aiming to promote public awareness and education regarding artificial intelligence, it directly relates to the societal impact of AI. The reference to benefits and risks indicates a concern for the implications that AI has on individuals and society as a whole, touching upon issues of consumer protection and awareness, which aligns well with the 'Social Impact' category. However, the bill does not delve into specific regulations or laws that address the governance of data, the integrity of AI systems, or the robustness of AI benchmarks. Therefore, while there is a clear relevance to the 'Social Impact' category, the others have no content to connect them meaningfully to AI aspects discussed in this context.


Sector: None (see reasoning)

The bill's focus is on public awareness and does not delineate the usage of AI in specific sectors like politics, healthcare, or private enterprises. Its primary intention is to educate the general public about AI, which doesn't fit neatly into any specific sector. Therefore, while it mentions AI's prevalence in daily lives, it lacks ties to formal sectors or their respective regulations.


Keywords (occurrence): artificial intelligence (13) automated (1) show keywords in context

United States HB7533: Modernizing Retrospective Regulatory Review

Description: To improve retrospective reviews of Federal regulations, and for other purposes.
Collection: Legislation
Status date: March 5, 2024
Status: Introduced
Primary sponsor: Andy Biggs (3 total sponsors)
Last action: Ordered to be Reported in the Nature of a Substitute (Amended) by the Yeas and Nays: 21 - 19. (March 7, 2024)

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

The text primarily focuses on the retrospective review of Federal regulations and mentions the use of technology, including algorithmic tools and artificial intelligence, for enhancing the efficiency and accuracy of these reviews. It emphasizes the importance of using such technologies for identifying regulations that may need revision or elimination, which ties into social accountability and the need for guidelines governing AI's role in regulatory processes. Given this explicit mention of AI and its implications for regulation, the relevance across categories is assessed as follows: - Social Impact pertains due to the use of AI in reviewing regulations that could influence fairness and accountability in governance. - Data Governance is relevant since it touches on managing and processing regulatory data in a machine-readable format, but lacks a strong focus on bias or privacy. - System Integrity is relevant because of the mention of algorithmic tools and the need for oversight in their use, though it is not profoundly detailed in terms of security measures. - Robustness, while somewhat relevant because of the focus on improved processes using AI, does not address benchmarks or performance standards explicitly. Therefore, Social Impact, Data Governance, and System Integrity are assigned higher relevance scores while Robustness is lower.


Sector:
Government Agencies and Public Services (see reasoning)

In examining the sectors, there are strong connections to government functions and operations due to the proposed use of AI within federal regulatory frameworks: - Politics and Elections is not directly touched upon as the bill does not specify AI's usage in electoral processes. - Government Agencies and Public Services is very relevant since the bill targets improvements in how federal agencies conduct regulatory reviews with the help of AI. - The Judicial System is not addressed since AI's role in legal frameworks is not mentioned. - Healthcare is unrelated given no connection to health regulations. - Private Enterprises, Labor, and Employment is also unrelated, as discussions around business environments are absent. - Academic and Research Institutions are not applicable here as there's no focus on educational criteria. - International Cooperation and Standards do not play a role in this legislation either. - Nonprofits and NGOs are not mentioned, hence they are irrelevant here. - Hybrid, Emerging, and Unclassified could apply to some extent, but not strongly enough to warrant a significant score. Hence, the strongest relevance is to Government Agencies and Public Services.


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

Tennessee HB1731: AN ACT to amend Tennessee Code Annotated, Title 4; Title 5; Title 6; Title 7; Title 39; Title 47; Title 48; Title 55; Title 56; Title 62; Title 66 and Title 67, relative to parking.

Description: As enacted, enacts the "Modernization of Towing, Immobilization, and Oversight Normalization (MOTION) Act." - Amends TCA Title 4; Title 5; Title 6; Title 7; Title 39; Title 47; Title 48; Title 55; Title 56; Title 62; Title 66 and Title 67.
Collection: Legislation
Status date: May 31, 2024
Status: Passed
Primary sponsor: Jake McCalmon (22 total sponsors)
Last action: Comp. became Pub. Ch. 1017 (May 31, 2024)

Category: None (see reasoning)

The text primarily addresses revisions to parking regulations in Tennessee and does not explicitly mention AI, algorithms, or any related technology associated with the categories of Social Impact, Data Governance, System Integrity, or Robustness. The single mention of an 'automatic license plate reader' describes a tool that utilizes an algorithm but does not engage with any concepts directly related to AI ethics or governance as outlined in the categories. Overall, the core content of the act focuses on parking enforcement rather than the implications of AI technology.


Sector: None (see reasoning)

The text does not address specific sectors such as Politics and Elections, Government Agencies and Public Services, or any others that involve the use or regulation of AI technology. Instead, it proposes amendments relevant to parking enforcement and vehicle management, which do not inherently involve AI applications in any sector. The mention of an 'automatic license plate reader' does not align with the broader discussions typically associated with the defined sectors.


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

United States HB8665: Supercritical Geothermal Research and Development Act

Description: To amend the Energy Independence and Security Act of 2007 to direct research, development, demonstration, and commercial application activities in support of supercritical geothermal and closed-loop geothermal systems in supercritical various conditions, and for other purposes.
Collection: Legislation
Status date: June 7, 2024
Status: Introduced
Primary sponsor: Frank Lucas (2 total sponsors)
Last action: Subcommittee Hearings Held (July 23, 2024)

Category:
Data Governance
System Integrity (see reasoning)

The text does include references to AI through terms such as 'machine learning algorithms,' showing a connection to the use of AI in optimizing and enhancing geothermal research and applications. However, the primary focus of the legislation appears to be on geothermal energy rather than extensive AI-related social impacts or regulatory frameworks. The mention of machine learning suggests some relevance to the Data Governance and System Integrity categories, but it is not the primary thrust of the bill. Furthermore, without broader implications on data governance or system integrity, the scoring for Social Impact and Robustness may remain lower.


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

The focus of this legislation is primarily on geothermal energy research and development, with only tangential mentions of AI. The references to AI are included within the context of enhancing geothermal technology rather than addressing specific sectors significantly. Therefore, while there is a slight connection to the Government Agencies and Public Services sector due to its regulatory nature, the overall impact on sectors like Healthcare or Private Enterprises does not seem relevant. The understanding is limited to applications within the energy sector, and its broader impact does not clearly translate to other sectors.


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

New York S08305: Enacts into law major components of legislation necessary to implement the state public protection and general government budget for the 2024-2025 state fiscal year; establishes the crime of assault on a retail worker (Part A); establishes the crime of fostering the sale of stolen goods as a clas...

Description: Enacts into law major components of legislation necessary to implement the state public protection and general government budget for the 2024-2025 state fiscal year; establishes the crime of assault on a retail worker (Part A); establishes the crime of fostering the sale of stolen goods as a class A misdemeanor (Part B); adds to the list of specified offenses that constitutes a hate crime (Part C); authorizes the governor to close correctional facilities upon notice to the legislature (Part D...
Collection: Legislation
Status date: Jan. 17, 2024
Status: Introduced
Primary sponsor: Budget (sole sponsor)
Last action: SUBSTITUTED BY A8805C (April 18, 2024)

Category: None (see reasoning)

The provided text primarily focuses on implementing state legislation aimed at public protection and adjustments to the penal code. The text does not engage with AI systems, their impacts on society, or legislation directly related to AI governance or integrity. As such, it appears to be completely unrelated to AI-specific issues, making it irrelevant for all categories concerning AI.


Sector: None (see reasoning)

The text outlines various legal amendments and public protection measures but lacks any discussion or reference to AI-related use cases or regulations within specific sectors. This absence of AI content likewise renders the text non-relevant to the identified sectors, leading to a score of 1 across all sectors.


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

United States HB7532: Federal AI Governance and Transparency Act

Description: To amend chapter 35 of title 44, United States Code, to establish Federal AI system governance requirements, and for other purposes.
Collection: Legislation
Status date: March 5, 2024
Status: Introduced
Primary sponsor: James Comer (8 total sponsors)
Last action: Ordered to be Reported in the Nature of a Substitute (Amended) by the Yeas and Nays: 36 - 3. (March 7, 2024)

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

The Federal AI Governance and Transparency Act is directly focused on establishing governance for AI systems within the federal government. It explicitly addresses social impacts, such as civil rights, civil liberties, and fairness, by ensuring that AI applications do not unfairly harm or benefit certain groups. It also outlines requirements for transparency and accountability, which directly relate to the Social Impact category. The emphasis on responsible management, oversight, and adherence to laws reflects aspects covered by the System Integrity category while also tying into Data Governance under the data protection and privacy measures described. There is some relevance to robustness as well, due to the mention of testing AI systems against defined benchmarks and performance standards. However, the primary focus remains on governance and accountability in the context of social impact, data governance, and system integrity related to AI implementation and utilization.


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

The legislation is highly relevant to the Government Agencies and Public Services sector as it specifically pertains to the use and governance of AI within federal agencies, outlining their responsibilities and procedures in utilizing AI. There is a moderate relevance to the Judicial System because of implications that AI governance affects legal rights and individual determinations, such as appeals processes. Additionally, this legislation may touch upon the implications for Private Enterprises, Labor, and Employment due to its governance impact on contracts and procurement processes. However, it does not primarily address issues specifically related to sectors like Healthcare, Academic Institutions, or others listed.


Keywords (occurrence): artificial intelligence (57) machine learning (1) show keywords in context

California SB11: Artificial intelligence technology.

Description: An act to add Chapter 22.7 (commencing with Section 22650) to Division 8 of the Business and Professions Code, to amend Section 3344 of the Civil Code, to add Article 2.5 (commencing with Section 1425) to Chapter 1 of Division 11 of the Evidence Code, and to add Chapter 9 (commencing with Section 540) to Title 13 of Part 1 of the Penal Code, relating to artificial intelligence technology.
Collection: Legislation
Status date: Dec. 2, 2024
Status: Introduced
Primary sponsor: Angelique Ashby (sole sponsor)
Last action: From printer. May be acted upon on or after January 2. (Dec. 3, 2024)

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

The text explicitly discusses various legal frameworks concerning artificial intelligence (AI) technology, particularly focusing on accountability, consumer protection regarding synthetic content, and implications for legal proceedings. This aligns well with the Social Impact category, as it addresses accountability and harm related to the misuse of AI technology. The Data Governance category is relevant due to mentions of consumer warnings and the handling of AI-generated synthetic content which connects to data management and consent. System Integrity is also relevant since it highlights the necessity of judicial assessments of AI evidence, indicating concerns over security and control of AI systems. Robustness is less central as the text does not primarily address benchmarks for AI performance but rather legal definitions and implications. Overall, the relevance of the Social Impact is strong due to provisions on misuse and consumer rights, while Data Governance and System Integrity are moderately relevant as they touch upon data management and legal standards for evidence respectively.


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

The text pertains primarily to the sectors of Government Agencies and Public Services, as it discusses legislation that directs state regulatory bodies on AI-related consumer rights and judicial practices. It indirectly touches on the Judicial System due to its focus on evidence and verification processes concerning AI. The discussion about consumer warnings and liabilities is particularly relevant to Private Enterprises, Labor, and Employment, as it relates to businesses dealing with AI technology. While there are implications for healthcare and academic institutions, these are much less pronounced, thus scoring lower. The legislation primarily focuses on governmental and consumer implications arising from AI technology, giving it a distinct connection to governmental functions and legal statutes.


Keywords (occurrence): artificial intelligence (14) show keywords in context
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