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Legislation Only
Regulations and Documents
Legislation
About these categories

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

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

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

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

About these sectors

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

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

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

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

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

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

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

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

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

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4828 results:


Minnesota HF2500: Algorithm and AI use prohibited during health insurance prior authorization request review.

Description: Algorithm and AI use prohibited during health insurance prior authorization request review.
Summary: The bill prohibits health insurance carriers from using algorithms or artificial intelligence when reviewing prior authorization requests, aiming to ensure human oversight in these decisions starting January 1, 2026.
Collection: Legislation
Status date: March 17, 2025
Status: Introduced
Primary sponsor: Alex Falconer (4 total sponsors)
Last action: Author added Rehrauer (March 24, 2025)

Category:
Societal Impact
Data Governance (see reasoning)

The text pertains to legislation that directly addresses the prohibition of using algorithms and artificial intelligence in health insurance prior authorization decision-making. This has significant implications for social impact as it aims to ensure fairness and accountability in health insurance processes. Given that the legislation directly mentions the prohibition of AI and algorithms, it is extremely relevant to the societal impacts that AI systems can have on healthcare and individual rights. Data governance is also relevant as it pertains to how data for these algorithms may have been collected or used, but not as directly as social impact since the bill focuses specifically on prohibiting use rather than regulating data integrity. System integrity and robustness are less relevant because the bill does not focus on the technical standards or performance metrics of AI but rather restricts its use altogether in a specific context.


Sector:
Healthcare (see reasoning)

The bill is highly relevant to the Healthcare sector, as it specifically addresses the use of AI within health insurance contexts, particularly in the prior authorization process. It restricts the application of AI and algorithms directly related to patient care decisions, impacting how health insurers operate. The relevance to other sectors, like Politics and Elections or Government Agencies and Public Services, is minimal since the bill does not address political processes, governmental functions, or other sectors that do not involve healthcare decision-making. No relevance is found regarding the Judicial System, Private Enterprises, Labor, and Employment, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, or Hybrid, Emerging, and Unclassified sectors as the focus remains strictly within healthcare legislation.


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

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Category: None (see reasoning)


Sector: None (see reasoning)


Keywords (occurrence): artificial intelligence () machine learning () neural network () deep learning () automated () deepfake () synthetic media () large language model () foundation model () chatbot () recommendation system () algorithm () autonomous vehicle ()

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Keywords (occurrence): artificial intelligence () machine learning () neural network () deep learning () automated () deepfake () synthetic media () large language model () foundation model () chatbot () recommendation system () algorithm () autonomous vehicle ()

Florida S1424: K-12 School Transportation

Description: Requiring school districts to provide transportation to students in kindergarten through grade 12 under certain circumstances; requiring district school boards to provide transportation to students in kindergarten through grade 12 who live more than 1 mile from the nearest appropriate school; requiring the use of artificial intelligence programs for specified purposes within a certain timeframe of such programs being made available; revising the criteria for walkways parallel and perpendicula...
Summary: The bill mandates Florida school districts to provide transportation for K-12 students living over one mile from school, requires parental consent, and enforces safety standards, including using AI for route optimization.
Collection: Legislation
Status date: Feb. 26, 2025
Status: Introduced
Primary sponsor: Jay Collins (sole sponsor)
Last action: Introduced (March 10, 2025)

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

The text explicitly requires the use of artificial intelligence programs in transportation for K-12 students under defined circumstances. This inclusion makes it relevant to the categories, particularly 'Data Governance' for the management of AI systems used for transportation, and 'System Integrity' as it addresses the need for oversight of AI applications in ensuring safe transportation routes. The emphasis on AI's role indicates significant implications for social impact, as it directly affects the wellbeing of students by making transportation safer and more efficient. Therefore, the scores will reflect the intersection of AI and its broader societal implications.


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

The legislation primarily pertains to K-12 school transportation, which aligns closely with the 'Government Agencies and Public Services' sector as it involves state mandates concerning public education. The legislation also touches on aspects relevant to the 'Academic and Research Institutions' sector, particularly in how AI might optimize operational efficiencies in educational settings. However, the main focus remains on government regulations regarding how school districts provide transportation services, suggesting a stronger relevance to the government sector.


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

United States SB2770: Protect Elections from Deceptive AI Act

Description: A bill to prohibit the distribution of materially deceptive AI-generated audio or visual media relating to candidates for Federal office, and for other purposes.
Summary: The "Protect Elections from Deceptive AI Act" prohibits disseminating misleading AI-generated media related to federal candidates to safeguard election integrity and enables civil actions for violations.
Collection: Legislation
Status date: Sept. 12, 2023
Status: Introduced
Primary sponsor: Amy Klobuchar (6 total sponsors)
Last action: Placed on Senate Legislative Calendar under General Orders. Calendar No. 388. (May 15, 2024)

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

The legislation explicitly addresses the impact of AI-generated media on elections, referring directly to the potential psychological and material harm that could arise from deceptive AI-generated content. It emphasizes accountability by prohibiting misleading AI-generated media related to candidates, indicating a legislative attempt to protect the integrity of the electoral process. This aligns closely with Social Impact, justifying a high relevance score. Data Governance has moderate relevance as well, since ensuring the integrity of data in political contexts can relate to AI outputs, though the focus on deception slightly shifts it away from core data governance concerns. System Integrity evaluates how AI-generated content must undergo scrutiny and potential oversight, reflecting the nature of AI's role in maintaining a fair election process, thereby presenting moderate relevance. Robustness is less relevant, as no specific performance benchmarks or standards for AI systems are outlined in the text, indicating that it is insufficiently emphasized within the proposed regulation.


Sector:
Politics and Elections (see reasoning)

This text directly pertains to the regulation of AI in the political realm, given its focus on preventing the spread of deceptive AI-generated content regarding federal electoral candidates. By explicitly dealing with AI technology's implications in politics and elections, the legislation shows a clear intent to protect voters and candidates from misinformation, thus scoring highly in this sector. Other sectors do not receive the same level of focus, as the legislation primarily centers around electoral processes and does not significantly address the roles of other sectors like healthcare, private enterprises, or government agencies.


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

North Carolina H375: AI/Ban Deceptive Ads

Description: AI/Ban Deceptive Ads
Summary: House Bill 375 seeks to regulate the use of AI-generated deepfakes in political advertisements, aiming to prevent deceptive practices that mislead voters and protect minors from harmful content.
Collection: Legislation
Status date: March 11, 2025
Status: Introduced
Primary sponsor: Harry Warren (22 total sponsors)
Last action: Ref to the Com on Commerce and Economic Development, if favorable, Election Law, if favorable, Judiciary 2, if favorable, Rules, Calendar, and Operations of the House (March 13, 2025)

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

This legislation explicitly addresses the social impact of AI by regulating the use of deepfakes and deceptive advertisements in political campaigns, which can significantly affect public perception and the integrity of electoral processes. The bill aims to protect the public from misleading content resulting from AI-generated media, which relates directly to issues of misinformation and accountability. It also acknowledges the potential harms AI can cause, particularly to minors, reinforcing its relevance to social impact. Therefore, it can be rated as 'extremely relevant'. The aspect of governing data within AI systems is also touched upon, particularly in relation to the authenticity and provenance of AI-generated content. However, the focus remains on the societal implications of using such AI technologies, making this category a priority. Thus, it receives a score of 5. The Data Governance category, while relevant due to its discussion on digital content provenance and the accuracy of AI-generated media, is more of a secondary concern compared to the primary focus on the societal effects of AI misinformation, thus it rates lower at 3. The System Integrity category is relevant through mentions of ensuring transparency in AI-generated content and requiring disclosures, hence a score of 4 is warranted. The Robustness category's emphasis on performance benchmarks does not directly relate to the main concerns of the bill; hence a score of 2 reflects its limited relevance.


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

This legislation clearly pertains to the Politics and Elections sector, as it directly addresses the regulation of AI use in political campaigns and the dissemination of potentially deceptive advertisements during elections. The act's focus on preventing misinformation through AI-generated deepfakes makes it a key component of election integrity and voter protection. Thus, it rates as 'extremely relevant' with a score of 5. The Government Agencies and Public Services sector is somewhat relevant given that it discusses the responsibilities of content creators and potential governmental oversight, warranting a score of 3. The Judicial System is also relevant, considering the act outlines remedies in case of violations, thus receiving a score of 4. However, other sectors like Healthcare, Private Enterprises, Labor and Employment, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, and Hybrid, Emerging, and Unclassified have little to no explicit relevance to the text; consequently, they receive a score of 1.


Keywords (occurrence): artificial intelligence (22) machine learning (1) automated (2) deepfake (8) synthetic media (12) show keywords in context

North Carolina S287: Safeguard Health Ins. Utilization Reviews

Description: Safeguard Health Ins. Utilization Reviews
Summary: The bill ensures that healthcare service determinations for necessity are made by qualified providers, prohibiting solely AI-based decisions, to safeguard patient care in North Carolina.
Collection: Legislation
Status date: March 13, 2025
Status: Introduced
Primary sponsor: Gale Adcock (sole sponsor)
Last action: Ref To Com On Rules and Operations of the Senate (March 17, 2025)

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

The text explicitly mentions the use of artificial intelligence in utilization reviews, focusing on ensuring that AI-based algorithms are not the sole determinants in healthcare decisions relating to medical necessity. This indicates a direct relevance to the social impact of AI, as it addresses the accountability and standards surrounding AI's role in sensitive healthcare decisions. The category of Data Governance may also pertain to the management of data accuracy within AI systems, particularly in verifying contracts with third parties in healthcare settings. System Integrity is relevant as well since there is a clear interest in maintaining human oversight in AI functions concerning medical evaluations, reinforcing the importance of security and transparency in those decisions. The category of Robustness can be considered as it indicates a focus on ensuring the reliability of AI systems but is less directly addressed compared to the others. Hence, the scores reflect the mandatory inclusion of human oversight in AI processes, the significant implications for fairness and accountability, and the need for accurate data governance.


Sector:
Healthcare (see reasoning)

The legislation directly relates to Healthcare by outlining how AI will be governed within the context of utilization reviews. It stipulates how healthcare providers are expected to operate in relation to AI, making this sector highly relevant. Therefore, the primary scores come from the direct association of AI's regulatory presence within healthcare utilization processes, ensuring that these technologies do not operate independently of qualified human oversight.


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

Rhode Island H5857: Creates the reproductive freedom and gender affirming care health data privacy act.

Description: HEALTH AND SAFETY -- REPRODUCTIVE FREEDOM AND GENDER AFFIRMING CARE HEALTH DATA PRIVACY ACT - Creates the reproductive freedom and gender affirming care health data privacy act.
Summary: The bill establishes the Reproductive Freedom and Gender Affirming Care Health Data Privacy Act in Rhode Island, safeguarding consumer health data related to reproductive and gender-affirming care, and ensuring informed consent for data collection and sharing.
Collection: Legislation
Status date: Feb. 28, 2025
Status: Introduced
Primary sponsor: Jason Knight (10 total sponsors)
Last action: Introduced, referred to House Health & Human Services (Feb. 28, 2025)

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

The text primarily addresses issues related to health data privacy, specifically regarding reproductive freedom and gender-affirming care. The references to algorithms and machine learning highlight concerns about how these technologies are utilized to process consumer health data, suggesting implications for biases, transparency, and system integrity within the health data framework. The legislation indirectly relates to social impact by informing stakeholders of rights and safeguards, potentially applying AI/data governance considerations. The focus on privacy and security resonates with Data Governance, while the examination of algorithmic data reinforces themes of System Integrity. However, the text lacks substantial emphasis on benchmarks and performance metrics related to AI, suggesting less relevance to Robustness.


Sector:
Healthcare (see reasoning)

This act is specifically focused on health data privacy in the context of reproductive and gender-affirming care. It is directly applicable to the Healthcare sector due to its emphasis on consumer health data, rights to privacy, and the potential influence of technology on these areas. The act does not directly discuss political campaign impacts or government agency use of AI, making it less relevant to Politics and Elections or Government Agencies and Public Services. It is not specifically tailored to Judicial systems, Private Enterprises, Labor, Academic Institutions, International Cooperation, Nonprofits, or emerging sectors. Thus, its primary relevance lies in Healthcare, with secondary considerations in areas linked to data processing methodologies.


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

Massachusetts S2539: Relative to cybersecurity and artificial intelligence

Description: For legislationfor legislationfor legislationfor legislationfor legislationfor legislationfor legislationfor legislationfor legislation to protect residents of the Commonwealth from the threat posed by certain foreign adversaries using current or potential future social media companies; and of Marcus S. Vaughn relative to electronic security for certain procurements involving electronic or cyber security equipment components, report the accompanying bill (Senate, No. 2539).
Summary: The bill establishes a comprehensive framework for cybersecurity and artificial intelligence regulation in Massachusetts, including statewide training, a Cybersecurity Control Board, and standards for protecting sensitive information and critical infrastructure.
Collection: Legislation
Status date: Dec. 28, 2023
Status: Introduced
Primary sponsor: Advanced Information Technology, the Internet and Cybersecurity (22 total sponsors)
Last action: Bill reported favorably by committee and referred to the committee on Senate Ways and Means (Dec. 28, 2023)

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

The text explicitly discusses the regulation of artificial intelligence in the context of cybersecurity. It highlights the establishment of standards and regulations governing AI use, particularly in how AI interacts with cybersecurity measures, thus affecting the overall integrity and security of systems. Therefore, the legislation is very relevant to social impact as it addresses potential risks and impacts of AI on societal safety, including the potential for misuse by foreign adversaries through cybersecurity channels. The detailed provisions regarding training and compliance within the realm of AI further support its relevance to data governance. The text discusses general cybersecurity measures and the creation of a Cybersecurity Control Board, linking tightly to system integrity and the need for compliance with standards that could also encompass robustness. Overall, the text’s focus on regulation, standards, and impact directly correlates with the central themes of social impact, data governance, system integrity, and robustness.


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

The legislation's focus on AI and cybersecurity has implications across several sectors. In the 'Politics and Elections' sector, while it does not directly address political campaigning or electoral processes, it indirectly touches on securing critical infrastructure, which could include election systems, thereby granting it some relevance (score of 2). The 'Government Agencies and Public Services' sector is highly relevant as it outlines measures for governmental entities, compliance, and training regarding AI and cybersecurity, hence a score of 5. The 'Judicial System' is not explicitly mentioned, although elements such as data privacy and cybersecurity can have indirect implications; thus a rating of 2. The 'Healthcare' sector does not specifically apply here but could be impacted due to cybersecurity measures related to personal data (score of 2). The 'Private Enterprises, Labor, and Employment' section is indirectly affected through regulations impacting businesses that handle sensitive information (score of 3). 'Academic and Research Institutions' may find relevance through training and standards set by the board, giving it a score of 2. The 'International Cooperation and Standards' may have some implications as the board will look toward federal guidelines, which can relate to consistency and standards in AI; thus, a 3. Nonprofits and NGOs could see impacts related to data protection, scoring a 2. Lastly, the legislation also slightly pertains to the 'Hybrid, Emerging, and Unclassified' sector given its broad scope regarding emerging technologies, thus a score of 3.


Keywords (occurrence): artificial intelligence (15) machine learning (3) automated (33) algorithm (1) show keywords in context

West Virginia HCR94: Requesting a study regarding the creating of an artificial intelligence elective course to be offered in high schools

Description: Requesting a study regarding the creating of an artificial intelligence elective course to be offered in high schools
Summary: The bill requests a study to establish an Artificial Intelligence Education Program as an elective in West Virginia high schools, focusing on curriculum development and funding to prepare students for future careers.
Collection: Legislation
Status date: March 18, 2025
Status: Introduced
Primary sponsor: Jarred Cannon (11 total sponsors)
Last action: To House Rules (March 18, 2025)

Category:
Societal Impact
Data Governance (see reasoning)

The text involves the establishment of an Artificial Intelligence Education Program, focusing on the educational impacts of AI in high schools. This directly pertains to the Social Impact category because it discusses the implications of AI education on youth and society in general. It addresses the need for training in AI to prepare students for a technology-driven future and the ethical considerations surrounding AI, which are societal concerns. The Data Governance category is also relevant as it could encompass how educational institutions manage data regarding AI programs. The System Integrity category is slightly relevant due to the need for oversight in implementing educational standards, but does not focus heavily on security or transparency issues related to AI systems. The Robustness category might not be directly relevant, as the text largely focuses on educational aspects rather than performance benchmarks or compliance measures for AI. Overall, the Social Impact category is the most pertinent, while Data Governance shows moderate relevance due to implications for data in education.


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

The text is highly relevant to the Academic and Research Institutions sector because it relates to the introduction of AI education within high schools, an educational context. It directly addresses the need for teaching AI concepts and principles to students, thus fitting squarely within academic sectors. The Government Agencies and Public Services sector is moderately relevant due to the legislative nature of the request, which involves government action to establish educational programs. However, it does not directly involve service delivery. The Private Enterprises, Labor, and Employment sector may have a slight connection, as education in AI can impact future employment opportunities, but this is less direct. The other sectors such as Politics and Elections, Judicial System, Healthcare, International Cooperation and Standards, Nonprofits and NGOs, and Hybrid, Emerging, and Unclassified do not have significant relevance to this text. Therefore, the final scoring represents a focus on educational implications.


Keywords (occurrence): artificial intelligence (16) machine learning (2) show keywords in context

California SB53: CalCompute: foundation models: whistleblowers.

Description: An act to add Section 11547.6.1 to the Government Code, and to add Chapter 5.1 (commencing with Section 1107) to Part 3 of Division 2 of the Labor Code, relating to artificial intelligence.
Summary: Senate Bill No. 53 establishes a consortium to create “CalCompute,” a public AI cloud computing framework promoting safe and ethical AI. It also enhances whistleblower protections for employees reporting critical risks from AI models.
Collection: Legislation
Status date: Jan. 7, 2025
Status: Introduced
Primary sponsor: Scott Wiener (sole sponsor)
Last action: Re-referred to Coms. on G.O. and JUD. (March 12, 2025)

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

The text discusses legislation focused on the development and oversight of artificial intelligence, specifically frontier models. This includes the establishment of safeguards, risk analysis related to generative AI, and the coordination of multiple governmental bodies. This directly relates to social impacts, as the text addresses the high-risk automated decision systems and their implications for individuals. Data governance is relevant here as well since the act mentions the need for inventory and risk analysis of AI systems, implying a structured approach to data management. System integrity is highlighted through the reference to oversight and safeguards against potential threats, emphasizing security and transparency in AI applications. Robustness is connected to the mention of standards and the intention to ensure the integrity of AI frontier models. Overall, the text is highly relevant to all four categories due to its comprehensive approach to regulating AI systems.


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

The text is primarily focused on the regulatory framework surrounding artificial intelligence, particularly in the context of state governance. The discussions about the Department of Technology, risk assessments by the Office of Emergency Services, and coordination with various governmental entities suggest relevance to the Government Agencies and Public Services sector. However, there are implications for multiple sectors as it relates to the application of AI across public infrastructure and decision-making processes, but the strongest relevance is to government operations. The impact on voters and electoral integrity aligns with the Politics and Elections sector, but it is less central to the text.


Keywords (occurrence): artificial intelligence (13) machine learning (1) automated (3) foundation model (6) show keywords in context

Massachusetts H3669: Relative to the safety of autonomous vehicles

Description: For legislation to further regulate the operation of autonomous vehicles. Transportation.
Summary: This bill mandates that autonomous vehicles in Massachusetts must have a human safety operator present during operation to ensure safety compliance with federal standards.
Collection: Legislation
Status date: Feb. 27, 2025
Status: Introduced
Primary sponsor: Jessica Giannino (sole sponsor)
Last action: Senate concurred (Feb. 27, 2025)

Category:
Societal Impact (see reasoning)

The text specifically addresses regulation regarding the operation of autonomous vehicles, which inherently involves AI technologies necessary for vehicle automation. The legislation concerns public safety and the operational guidelines around AI-driven systems (autonomous vehicles), making it pertinent to considerations of Social Impact, particularly regarding human safety and oversight. However, the text does not delve into data privacy aspects, algorithmic transparency, or the robustness of AI systems, which limits its relevance to Data Governance, System Integrity, and Robustness. Hence, it primarily impacts the Social Impact category, but with less direct relevance to the other categories.


Sector:
Government Agencies and Public Services (see reasoning)

The legislation discusses the operation of autonomous vehicles, which falls under the category of Government Agencies and Public Services due to state regulation of transportation. It ensures the safe and responsible deployment of AI technology in the public sector. However, it does not directly pertain to political regulations, healthcare applications, judicial system regulations, the role of private enterprises, academic contexts, international cooperation, or nonprofit activities. Thus, it is most relevant to Government Agencies and Public Services.


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

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Category: None (see reasoning)


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Keywords (occurrence): artificial intelligence () machine learning () neural network () deep learning () automated () deepfake () synthetic media () large language model () foundation model () chatbot () recommendation system () algorithm () autonomous vehicle ()

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Keywords (occurrence): artificial intelligence () machine learning () neural network () deep learning () automated () deepfake () synthetic media () large language model () foundation model () chatbot () recommendation system () algorithm () autonomous vehicle ()

North Dakota HB1448: The advanced technology review committee, advanced technology grant program, and advanced technology grant fund.

Description: A BILL for an Act to create and enact a new chapter to title 54 of the North Dakota Century Code, relating to the advanced technology review committee, advanced technology grant program, and advanced technology grant fund.
Summary: The bill establishes an Advanced Technology Review Committee and an Advanced Technology Grant Program in North Dakota to support early-stage research and development in advanced technologies, promoting economic growth and innovation.
Collection: Legislation
Status date: Feb. 25, 2025
Status: Engrossed
Primary sponsor: Josh Christy (12 total sponsors)
Last action: Received from House (Feb. 25, 2025)

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

The text contains provisions related to the establishment of an advanced technology grant program, specifically highlighting the emphasis on artificial intelligence, machine learning, and similar technologies. This indicates a direct focus on the social implications and development aspects of AI, thus it has strong relevance to the categories. The text does not deal with data governance practices, systemic integrity concerns, or robustness measures explicitly but does indicate oversight and compliance considerations somewhat indirectly through the review process, making those categories less relevant.


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

The text mentions advanced technology in contexts that broadly touch the private sector but does not specifically outline provisions for particular sectors like healthcare or government agencies. Its focus on entrepreneurship and small business innovation may tie into the private enterprises sector but it is more overarching. Therefore, while relevant, the specific legislative considerations for sectors aren't the primary focus here.


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

TEXT OF AMENDMENTS

Summary: The bill H.R. 5009 aims to reauthorize wildlife habitat and conservation programs, while additional amendments propose various effective dates for its implementation and address anti-human trafficking initiatives domestically and internationally.
Collection: Congressional Record
Status date: Dec. 12, 2024
Status: Issued
Source: Congress

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

Colorado SB280: Data Center Development and Grid Modernization Act

Description: Concerning benefits to facilitate data center development while supporting electric grid infrastructure, and, in connection therewith, creating the "Colorado Data Center Development and Grid Modernization Act".
Summary: The bill establishes the Colorado Data Center Development and Grid Modernization Act, providing tax incentives for data center projects that meet specific investment, job creation, and sustainability criteria to enhance digital infrastructure and modernize the electric grid.
Collection: Legislation
Status date: April 4, 2025
Status: Introduced
Primary sponsor: Nick Hinrichsen (6 total sponsors)
Last action: Introduced In Senate - Assigned to Transportation & Energy (April 4, 2025)

Keywords (occurrence): artificial intelligence (1) machine learning (1)

Florida S0794: Mandatory Human Reviews of Insurance Claim Denials

Description: Requiring that insurers' decisions to deny claims or any portion of a claim be made by qualified human professionals; prohibiting using algorithms, artificial intelligence, or machine learning systems as the sole basis for determining whether to adjust or deny a claim; requiring insurers to include certain information in denial communications to claimants, etc.
Summary: The bill mandates human reviews of insurance claim denials in Florida, prohibiting sole reliance on algorithms or AI for decisions, ensuring qualified professionals assess claims, and requiring detailed record-keeping and communication.
Collection: Legislation
Status date: Feb. 18, 2025
Status: Introduced
Primary sponsor: Banking and Insurance (2 total sponsors)
Last action: CS by Banking and Insurance read 1st time (March 26, 2025)

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

The text explicitly addresses the regulation of AI in the context of insurance claim denials. It mandates that decisions based on denying claims cannot rely on AI or machine learning systems, indicating clear legislative intent to protect consumers and ensure human oversight, which relates strongly to social impact. It also enforces requirements for documentation and reporting for human review processes, touching on aspects of governance and integrity, although the emphasis leans primarily toward social implications. The system integrity aspect pertains to mandates on human oversight and transparency in decision-making processes, further supporting the relevance of this category. However, the legislation does not explicitly address benchmarking or auditing for AI performance, which is relevant to robustness but not applicable here.


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

The text deals with the role of artificial intelligence in the insurance sector, specifically relating to claims processes. This has clear implications for Consumer Protection, as it ensures that decisions affecting individuals are made by qualified professionals rather than automated systems. It also pertains to the Government Agencies and Public Services sector through the enforcement of audits and regulatory oversight of claims processing by agencies. It doesn't fit neatly into sectors like Healthcare or Politics, as it deals specifically with the insurance industry and its ethical implications. While related to the private enterprise sector, the focus remains primarily on consumer oversight and accountability, which aligns more with public interest.


Keywords (occurrence): artificial intelligence (5) machine learning (4) algorithm (7) show keywords in context

Florida H1289: Verification of Reemployment Assistance Benefit Eligibility

Description: Revises circumstances under which Department of Commerce disqualifies claimants from benefits; requires department to verify claimants' identities before paying benefits; requires department to cross-check information; requires department to maintain web page & e-mail address for specified purpose & to notify employers each year of web page & e-mail address; requires department's job-matching information system to contain certain elements.
Summary: The "Promoting Work, Deterring Fraud Act of 2024" mandates verification of reemployment assistance claimants' identities to prevent fraud, requiring comprehensive cross-checks of their information before benefits are paid.
Collection: Legislation
Status date: Jan. 5, 2024
Status: Introduced
Primary sponsor: Commerce Committee (3 total sponsors)
Last action: Died on Second Reading Calendar (March 8, 2024)

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

Hawaii SB2879: Relating To Technology.

Description: Establishes and appropriates funds for an artificial intelligence government services pilot program to provide certain government services to the public through an internet portal that uses artificial intelligence technologies.
Summary: The bill establishes an artificial intelligence pilot program in Hawaii to enhance state and county government services through an internet portal, with an appropriation for its development.
Collection: Legislation
Status date: Jan. 19, 2024
Status: Introduced
Primary sponsor: Glenn Wakai (7 total sponsors)
Last action: The committee on LBT deferred the measure. (Feb. 5, 2024)

Keywords (occurrence): artificial intelligence (7) show keywords in context
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