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Regulations and Documents
Legislation
About these categories

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

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

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

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

About these sectors

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

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

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

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

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

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

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

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

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

Clear All

4633 results:


Kansas HB2183: Modifying elements in the crimes of sexual exploitation of a child, unlawful transmission of a visual depiction of a child and breach of privacy to prohibit certain acts related to visual depictions in which the person depicted is indistinguishable from a real child, morphed from a real child's i...

Description: Modifying elements in the crimes of sexual exploitation of a child, unlawful transmission of a visual depiction of a child and breach of privacy to prohibit certain acts related to visual depictions in which the person depicted is indistinguishable from a real child, morphed from a real child's image or generated without any actual child involvement, provide an exception for cable services in the crime of breach of privacy and prohibit dissemination of certain items that appear to depict or p...
Collection: Legislation
Status date: Feb. 25, 2025
Status: Engrossed
Primary sponsor: Judiciary (sole sponsor)
Last action: Senate Committee Report recommending bill be passed as amended by Committee on Judiciary (March 7, 2025)

Category:
Societal Impact
Data Governance (see reasoning)

The text specifically addresses the implications of artificial intelligence in the context of visual depictions, particularly concerning criminal offenses related to sexual exploitation. It discusses modifying definitions of crimes to include images altered or generated by AI and establishes nuanced legal ramifications for such depictions. This indicates a direct concern about the social impact of AI as it relates to crime, exploitation, and the protection of minors, thus linking strongly to the category of Social Impact. The inclusion of measures regarding privacy and ethics within the context of AI further aligns it with discussions on Data Governance, addressing how data (in this case, visual depictions) is managed and used in these new legal considerations. However, while the text touches upon issues related to system integrity and robustness in terms of preventing harm and outlining legal structures, it does not delve into technical specifics about system validation or integrity benchmarks, resulting in lower relevance scores for those categories.


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

The legislation's focus on criminal offenses that involve AI-generated content, specifically concerning the potential harm to minors, positions it strongly within the realm of government regulation as it pertains to public safety. It reflects societal concerns and legal responses to the risks posed by emerging technologies, which is indicative of the Government Agencies and Public Services sector. Given the nature of the offenses and the involvement of minors, there is a moderate connection to the Judicial System sector as well, though it focuses more on enforcement than on the legal framework surrounding AI application. It does not fit squarely into other sectors like Healthcare or Private Enterprises, as it is not addressing those specific domains. Thus, the scores reflect this concentrated focus.


Keywords (occurrence): artificial intelligence (5) automated (1) 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.
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)

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

The text discusses the Department of Commerce's role in verifying identities and managing claims related to reemployment assistance benefits. Although it primarily focuses on data verification and claim management, the mention of an 'automated job-matching information system' that uses 'artificial intelligence generation' implies some relevance to the mechanisms behind AI systems. There are considerations for fraud prevention which can tie into systemic integrity and robustness. However, the text doesn’t explicitly address the broader social implications or governance aspects of AI usage.


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

The text pertains to government processes and regulations surrounding reemployment assistance, which includes the usage of AI systems within job-matching contexts. It aligns closely with government initiatives and operations. Given that it directly involves the Department of Commerce's actions, data practices for claim verification, and the integrity of the reemployment assistance system, it's relevant to the 'Government Agencies and Public Services' sector. However, it doesn’t directly engage with judicial aspects, healthcare applications, or others mentioned, thus assigning lower relevance there.


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

Massachusetts H4722: Relative to strengthening Massachusetts' economic leadership

Description: Relative to strengthening Massachusetts' economic leadership
Collection: Legislation
Status date: June 5, 2024
Status: Introduced
Primary sponsor: Committee on Economic Development and Emerging Technologies (sole sponsor)
Last action: New draft substituted, see H4789 (June 27, 2024)

Category:
Societal Impact
Data Robustness (see reasoning)

The text provides funding to support the adoption and application of artificial intelligence across various sectors within Massachusetts. This indicates a strong relevance to the 'Social Impact' category, particularly regarding economic opportunities and the promotion of innovation. The text highlights the importance of leveraging AI to advance the commonwealth’s technological leadership, which aligns with social progress and technological accountability. Furthermore, it discusses job creation, which ties into both social equity and the economic benefits of adopting AI technologies. While there are mentions of funding allocations that could be relevant to data governance, system integrity, and robustness through grants aimed at technological improvement, the focus is heavily weighted towards social impacts and economic innovation. Overall, the legislation appears to address various impacts of AI on society, particularly regarding job creation and industry leadership rather than specific governance or technical integrity issues, leading to a higher score in 'Social Impact' and lower relevance in the other categories.


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

The text discusses several funding allocations for technology development with explicit mentions of artificial intelligence applications primarily in economic sectors. The references to leveraging AI technologies to advance growth in sectors such as life sciences, healthcare, and education indicate a direct connection to the 'Healthcare' and 'Government Agencies and Public Services' sectors, as these are areas that will likely adopt AI for improved service delivery and innovation. The legislation aims to enhance the commonwealth's infrastructure and stimulate economic development, which relates to 'Private Enterprises, Labor, and Employment' due to the promotion of job creation through technology advancement. There are mentions of support for agricultural biotechnology, which aligns partially with 'Private Enterprises, Labor, and Employment.' However, many sectors that don’t explicitly discuss the use of AI would score lower, reflecting a moderate relevance overall. Given the broad nature of the impacts considered, the legislation constitutes strong relevance to 'Government Agencies and Public Services', 'Healthcare', and 'Private Enterprises, Labor, and Employment' while scoring lower for 'Academic and Research Institutions' or 'International Cooperation and Standards' as those connections are not clear.


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

Washington HB1622: Allowing bargaining over matters related to the use of artificial intelligence.

Description: Allowing bargaining over matters related to the use of artificial intelligence.
Collection: Legislation
Status date: Jan. 27, 2025
Status: Introduced
Primary sponsor: Lisa Parshley (47 total sponsors)
Last action: Rules Committee relieved of further consideration. Placed on second reading. (March 4, 2025)

Category:
Societal Impact (see reasoning)

The provided text primarily focuses on legislation that pertains to the usage of artificial intelligence within the context of collective bargaining agreements. The terms and references to 'artificial intelligence' and related technologies are directly related to the legislation's aim of ensuring that the adoption and modification of AI technologies are subject to collective bargaining if they impact employee wages, hours, or working conditions. Therefore, the relevance of the categories can be evaluated based on the implications of AI on social impact, data governance, system integrity, and robustness in the context of labor relations. Overall, while there are mentions of technology, the act structurally aligns more with social implications rather than data governance, system integrity, or robustness. The legislation's relevance to societal aspects of AI usage, fairness, and employee rights can be considered very relevant.


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

The text explicitly addresses the role of artificial intelligence in the context of collective bargaining, which is primarily relevant to the workforce, labor relations, and government interactions with employees. The mentions of decisions about adopting AI affecting employee conditions directly tie to the implications and interactions within the Labor market. However, the broad aspects like healthcare and other specific sectors are not directly discussed, thus scoring lower in those respects. This text does suggest some level of engagement with public services through government agencies overseeing employment matters, which gives it slight relevance there. Ultimately, the legislation's core focus on the intersection between AI and labor relations is evident.


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

Illinois HB0299: EDUCATION-TECH

Description: Amends the Courses of Study Article of the School Code. In provisions concerning bullying and cyber-bullying, provides that bullying includes posting or distributing sexually explicit images. Provides that, beginning with the 2025-2026 school year, the term "cyber-bullying" includes the posting or distribution of a digital replica by electronic means. Defines "artificial intelligence", "digital replica", and "generative artificial intelligence". Effective July 1, 2025.
Collection: Legislation
Status date: May 22, 2024
Status: Engrossed
Primary sponsor: Janet Yang Rohr (15 total sponsors)
Last action: Referred to Assignments (May 22, 2024)

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

Virginia SB775: Political campaign advertisements; synthetic media, penalty.

Description: Elections; political campaign advertisements; synthetic media; penalty. Prohibits electioneering communications containing synthetic media, as those terms are defined in the bill, from being published or broadcast without containing the following conspicuously displayed statement: "This message contains synthetic media that has been altered from its original source or artificially generated and may present conduct or speech that did not occur." The bill creates a civil penalty not to exceed $...
Collection: Legislation
Status date: March 7, 2025
Status: Enrolled
Primary sponsor: Scott Surovell (2 total sponsors)
Last action: Bill text as passed Senate and House (SB775ER) (March 7, 2025)

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

The text explicitly addresses the dissemination of artificial audio and visual media in elections, indicating a significant social impact by trying to mitigate misinformation and deception in political campaigns. It discusses penalties for using synthetic media misleadingly, directly correlating with accountability measures and consumer protections, as it aims to protect voters from being misled by AI-generated content. As such, it is highly relevant to the Social Impact category. The Data Governance category is relevant as it also involves regulations on disclosure in the context of AI-generated media, ensuring that voters are provided with accurate information about the nature of the media they encounter. However, it does not delve deeply into data management aspects, which may limit its relevance. The System Integrity category pertain to the requirement of clear disclosures and the regulations for online platforms regarding synthetic media, focusing more on the integrity of the media being presented in political contexts than on inherent security or control issues. The Robustness category is less relevant here since there is little mention of benchmarks, auditing, or performance measures for AI systems in the text.


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

The text is highly relevant to the Politics and Elections sector as it specifically discusses regulations concerning the use of AI-generated content in electoral contexts. The legislation aims to combat misinformation and help maintain electoral integrity through the regulation of synthetic media, making it extremely relevant to this sector. The Government Agencies and Public Services sector could be moderately relevant, as it involves the regulation and enforcement of these new media guidelines by governmental bodies, but it primarily focuses on political campaign contexts. The Judicial System sector does not appear to directly relate here, as the text primarily addresses legislation rather than its application in legal proceedings. Healthcare, Private Enterprises, Labor, and Employment, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, and Hybrid, Emerging, and Unclassified sectors do not seem to relate to the text at all, as it doesn't address the use or regulation of AI outside of the electoral context.


Keywords (occurrence): synthetic media (5) show keywords in context

New York A00433: Relates to the disclosure of automated employment decision-making tools; requires the office of information technology services to maintain an artificial intelligence inventory; provides that the use of artificial intelligence systems shall not affect the existing rights of employees pursuant to ...

Description: Relates to the disclosure of automated employment decision-making tools; requires the office of information technology services to maintain an artificial intelligence inventory; provides that the use of artificial intelligence systems shall not affect the existing rights of employees pursuant to an existing collective bargaining agreement, or the existing representational relationships among employee organizations or the bargaining relationships between the employer and an employee organization.
Collection: Legislation
Status date: Jan. 8, 2025
Status: Introduced
Primary sponsor: Steven Otis (2 total sponsors)
Last action: substituted by s822 (Feb. 12, 2025)

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

The text focuses significantly on the disclosure and ethical use of automated employment decision-making tools and systems that utilize AI. It explicitly mentions 'artificial intelligence' multiple times and discusses the impact of these systems on employee rights, thus embedding the social dynamics of AI into its provisions. The legislation aims to protect the rights of workers against potential negative implications of AI usage in employment settings, addressing issues of accountability, transparency, and algorithmic decision-making fairness, which aligns well with concerns in the Social Impact category. Regarding Data Governance, the legislation mandates maintaining an AI inventory and disclosure of automated tools, which relates to data management and oversight in AI systems. System Integrity is relevant due to the focus on human oversight in these AI applications to ensure accountability. Robustness is less relevant since the text does not significantly address performance benchmarks or compliance standards for AI systems, but does mention the need for operational review processes, which aligns with some aspects of oversight and auditing. Overall, this text is extremely relevant to Social Impact and moderately relevant to Data Governance and System Integrity, with little relevance to Robustness.


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

This legislation is fundamentally connected to the sector of Private Enterprises, Labor, and Employment as it deals with how AI impacts employment practices and the rights of employees within the context of automated decision-making. It specifies caution against the displacement of jobs and assures that employee rights remain safeguarded, which is essential for existing workforce dynamics. While there are implications for Government Agencies and Public Services in terms of how automated systems may be employed within state agencies, the primary focus on labor rights and protections leverages stronger connections to employment frameworks. It does not explicitly address politics, the judicial system, healthcare, academic institutions, or international cooperation, making them less relevant. Therefore, the legislation is rated as extremely relevant to Private Enterprises, Labor, and Employment and moderately relevant to Government Agencies and Public Services.


Keywords (occurrence): artificial intelligence (11) machine learning (2) automated (30) large language model (1) show keywords in context

New York S02414: Enacts the "political artificial intelligence disclaimer (PAID) act"; requires political communications that use synthetic media to disclose that they were created with the assistance of artificial intelligence; requires committees that use synthetic media to maintain records of such usage.

Description: Enacts the "political artificial intelligence disclaimer (PAID) act"; requires political communications that use synthetic media to disclose that they were created with the assistance of artificial intelligence; requires committees that use synthetic media to maintain records of such usage.
Collection: Legislation
Status date: Jan. 17, 2025
Status: Introduced
Primary sponsor: Kevin Parker (sole sponsor)
Last action: REFERRED TO ELECTIONS (Jan. 17, 2025)

Category:
Societal Impact
Data Governance (see reasoning)

The text specifically addresses the impact of AI in the context of political communications, especially focusing on synthetic media and the necessity for disclosure regarding AI assistance. This touches on issues of accountability and transparency in AI use in political discourse, which are key elements of the Social Impact category. Given its focus on ensuring that political communications made with AI tools do not mislead voters, the relevance to Social Impact is extremely high. It also indirectly relates to Data Governance as it implies the management of records related to the use of AI in political contexts, but its primary emphasis is clearly on social implications. Although it discusses some aspects of oversight and record-keeping, it does not touch directly on system integrity or robustness in a significant way. Therefore, only Social Impact is rated as highly relevant, while Data Governance is considered moderately relevant due to its connection to record keeping but lacks a direct focus on data management issues.


Sector:
Politics and Elections (see reasoning)

The text deals specifically with the regulation of synthetic media in political communications, indicating a clear tie to the politics and elections sector. The need for disclosure about the use of artificial intelligence highlights the efforts to ensure transparency in political processes, making it extremely relevant to the political sector. It does not pertain to government agencies, the judicial system, healthcare, or other sectors because its primary focus lies within the political domain. Thus, it receives a high score in the Politics and Elections sector. Other sectors do not apply as they do not involve direct relevance to the AI's use in political contexts.


Keywords (occurrence): artificial intelligence (3) automated (1) synthetic media (5) show keywords in context

Florida S1680: Advanced Technology

Description: Creating the Government Technology Modernization Council within the Department of Management Services for a specified purpose; prohibiting a person from knowingly possessing or controlling or intentionally viewing photographs, motion pictures, representations, images, data files, computer depictions, or other presentations which the person knows to include generated child pornography; prohibiting a person from intentionally creating generated child pornography, etc.
Collection: Legislation
Status date: April 29, 2024
Status: Passed
Primary sponsor: Rules (3 total sponsors)
Last action: Chapter No. 2024-118 (April 29, 2024)

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

The text clearly outlines legislation focused on both the creation of the Government Technology Modernization Council and regulations surrounding generated child pornography. The references to artificial intelligence, especially in the establishment of the council, link it to the development and regulation of technology. The council is tasked with promoting AI systems, addressing ethical considerations, evaluating the impact of automated decision systems, and recommending policies to protect citizens from malicious uses of AI. Given this context, the legislation has strong implications for social impact, data governance, and system integrity if AI technologies are to be implemented responsibly. Furthermore, the text discusses AI's role in managing security and safety, reinforcing the relevance of the robustness category as it implies the establishment of benchmarks and regulations. Overall, the implications of AI for social accountability and ethical considerations make the social impact category especially relevant, while the regulation of AI systems points to the importance of data governance and system integrity.


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

This legislation pertains to several sectors through its provisions and objectives. The establishment of the Government Technology Modernization Council suggests a strong relevance to Government Agencies and Public Services, as it is designed to enhance the deployment and regulation of technology within the state. The mention of artificial intelligence and automated decision systems also implies considerations relevant to the Judicial System due to concerns about rights and biases arising from AI use. Additionally, as the legislation addresses responsibilities around the use of AI to combat issues such as generated child pornography, it touches on social justice impacts relevant to the broader community. It does not directly pertain to sectors like Healthcare or academics, nor does it address international cooperation specifically. However, its broad implications point to significant relevance for multiple sectors with an emphasis on governance and regulatory compliance.


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

Washington HB1616: Creating a charter of people's personal data rights.

Description: Creating a charter of people's personal data rights.
Collection: Legislation
Status date: Jan. 26, 2023
Status: Introduced
Primary sponsor: Shelley Kloba (4 total sponsors)
Last action: By resolution, reintroduced and retained in present status. (Jan. 8, 2024)

Category:
Societal Impact
Data Governance (see reasoning)

The text is primarily focused on personal data rights and privacy, particularly as they relate to the handling of personal information by entities within Washington state. It emphasizes the significance of protecting personal data that may be used in automated processes, and it addresses potential harms stemming from privacy violations, including discrimination driven by AI systems. The presence of terms such as 'algorithms' plainly relates to the Data Governance and Social Impact categories due to its emphasis on data security and the consequences of its misuse on marginalized communities. Thus, relevance to the discussed categories will vary. The System Integrity category could be only slightly relevant as it touches on oversight and obligations related to data collection and processing but doesn't explicitly outline measures for AI system integrity. The Robustness category is not explicitly relevant since benchmarks, compliance, and oversight for AI performance are not discussed.


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

The text details legislation related to data privacy and personal rights in the context of Washington state. While it does not specifically mention sectors such as Healthcare or Education, it addresses issues that can closely touch upon the sectors of Government Agencies and Public Services (as it regulates entities interacting with personal data) and Private Enterprises, Labor, and Employment (due to implications for businesses handling personal information). The primary sector connections here will thus be with Government Agencies and Private Enterprises, which focused on data handling standards.


Keywords (occurrence): artificial intelligence (3) automated (5) show keywords in context

New York S01962: Enacts the "New York artificial intelligence consumer protection act", in relation to preventing the use of artificial intelligence algorithms to discriminate against protected classes.

Description: Enacts the "New York artificial intelligence consumer protection act", in relation to preventing the use of artificial intelligence algorithms to discriminate against protected classes.
Collection: Legislation
Status date: Jan. 14, 2025
Status: Introduced
Primary sponsor: Kristen Gonzalez (sole sponsor)
Last action: REFERRED TO INTERNET AND TECHNOLOGY (Jan. 14, 2025)

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

The 'New York Artificial Intelligence Consumer Protection Act' explicitly addresses AI by preventing discrimination based on algorithmic outputs, which directly aligns with the Social Impact category due to its emphasis on ethical applications of AI that affect protected classes. It also touches on technical aspects of data management and bias auditing relevant to Data Governance. The requirement for risk management and oversight mechanisms indicates a consideration of System Integrity as it pertains to accountability and protection against misuse of AI. Although the text mentions measures for performance and evaluation, it does not focus on establishing new benchmarks or metrics for AI systems, making Robustness less relevant in this case.


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

The legislation is centered around consumer protection in the context of AI algorithms, which relates primarily to the private sector where businesses deploy AI systems. It has implications for various sectors, including Public Services (ensuring fair access to services and preventing discrimination) and perhaps contact with Government Agencies as it emphasizes compliance and audits, but these are not dominant themes. It does not directly address areas like Healthcare, Judicial System, or International Cooperation, which lessens their relevance significantly. Academic and research aspects are not highlighted either. The relevance to Nonprofits or NGOs appears minimal, though they may be involved in advocacy for ethical AI policies. Therefore, the most appropriate classification would be under Private Enterprises, related to labor and employment since the Act addresses the impact of AI on employment decisions.


Keywords (occurrence): artificial intelligence (96) show keywords in context

South Carolina H3102: Stop Social Media Censorship Act

Description: Amend The South Carolina Code Of Laws By Adding Article 6 To Chapter 5, Title 39 So As To Stop Certain Social Media Censorship, To Provide Penalties, And To Provide Exceptions.
Collection: Legislation
Status date: Jan. 10, 2023
Status: Introduced
Primary sponsor: James Burns (4 total sponsors)
Last action: Member(s) request name added as sponsor: Beach (Feb. 2, 2023)

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

The text discusses social media censorship and the use of algorithms, making it relevant to all four categories. In terms of 'Social Impact', it raises issues on the impact of censorship on political and religious speech, which directly aligns with societal impacts of AI-driven moderation. For 'Data Governance', while not explicitly focused on data management, the reference to algorithms and the requirement for fair practices in speech indirectly invokes considerations of how data-related practices affect users. 'System Integrity' is relevant due to the mention of algorithmic use and potential biases in social media platforms, seeking to ensure users have human-level oversight in case of disputes. 'Robustness' is relevant as the bill discusses maintaining standards for algorithms that govern speech, although the main focus is on censorship rather than performance metrics. Overall, there is a significant emphasis on the social implications and the governance of algorithms with respect to public discourse and trust, contributing to higher scores.


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

The legislation prominently addresses issues pertinent to the regulation of AI through algorithms on social media, especially in the context of political speech, making it highly relevant to 'Politics and Elections'. The potential penalties and standards for algorithmic moderation also lend relevance to 'Government Agencies and Public Services', as officials may need to enforce these regulations. 'Judicial System' relevance is evident through its implications for legal actions users can take against social media platforms. While healthcare and private enterprise sectors are not directly addressed, the principle of algorithm accountability may resonate in these areas as they intersect with operational practices of various entities. Overall, 'Politics and Elections' stands out as the most relevant sector closely tied to the legislative text's focus on censorship and algorithmic influence.


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

Texas HB4018: Relating to use of artificial intelligence in utilization review conducted for health benefit plans.

Description: Relating to use of artificial intelligence in utilization review conducted for health benefit plans.
Collection: Legislation
Status date: March 7, 2025
Status: Introduced
Primary sponsor: Suleman Lalani (sole sponsor)
Last action: Filed (March 7, 2025)

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

This text primarily addresses the use of artificial intelligence in healthcare, particularly in the context of utilization reviews for health benefit plans. It outlines specific requirements for how AI algorithms must be designed and used, ensuring fairness, transparency, and the avoidance of discrimination, which falls under the category of 'Social Impact.' Additionally, the legislation describes the requirements for accuracy, review, and oversight of AI systems, linking to 'Data Governance' and 'System Integrity.' Therefore, these categories are highly relevant as the text emphasizes accountability and safety concerning AI's role in healthcare processes.


Sector:
Healthcare (see reasoning)

The text is directly related to the healthcare sector, as it specifically defines how AI should be utilized by utilization review agents within health benefit plans, assessing clinical cases based on AI algorithms. The focus is on regulatory compliance and the ethical use of AI in healthcare settings. Given the explicit mention of healthcare applications and requirements in the context of AI utilization, a high score in this sector is warranted.


Keywords (occurrence): artificial intelligence (3) algorithm (12) show keywords in context

New Jersey S2964: Creates standards for independent bias auditing of automated employment decision tools.

Description: Creates standards for independent bias auditing of automated employment decision tools.
Collection: Legislation
Status date: March 18, 2024
Status: Introduced
Primary sponsor: Andrew Zwicker (sole sponsor)
Last action: Introduced in the Senate, Referred to Senate Labor Committee (March 18, 2024)

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

This legislation primarily impacts Social Impact as it addresses biases in employment decisions made by automated employment decision tools (AEDTs), which can affect the job opportunities of individuals. The legislation mandates independent bias auditing, which aims to ensure fairness and accountability in AI systems used in hiring, thus addressing potential discrimination and promoting equitable treatment. Given the specific mention of bias audits and compliance with anti-discrimination laws, this score is high. Data Governance is also highly relevant, as it involves ensuring that the data used by AEDTs is accurate and free from biases, as indicated by the legislation's requirements for audits based on historical and test data. System Integrity is moderately relevant since the legislation doesn’t explicitly mention system security, though the requirement for transparency aligns with core integrity concepts. Robustness is less relevant here as the focus of this bill is more on auditing and compliance rather than performance benchmarks for AI. Overall, the strongest connections are with Social Impact and Data Governance, which are crucial given that the bill directly relates to preventing bias in employment scenarios.


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

The primary sectors impacted by this legislation include Private Enterprises, Labor, and Employment, as it concerns the use of AEDTs within workforce hiring practices, promoting fairness and accountability in employment decisions. The legislation requires employers to be transparent about their use of these tools and their assessment processes, directly impacting how businesses operate concerning employment. Government Agencies and Public Services may also be relevant to some extent, as the regulation could involve public sector employment entities, but is primarily targeted toward private employers. Judicial System is not significantly addressed as the text focuses on employment auditing rather than any legal adjudication process. The remaining sectors such as Politics and Elections, Healthcare, Academic and Research Institutions, and Nonprofits and NGOs are not directly applicable here as they don’t pertain to the scope of automated employment decisions. Thus, the most pertinent sector for this legislation is Private Enterprises, Labor, and Employment.


Keywords (occurrence): artificial intelligence (2) machine learning (1) automated (7) show keywords in context

Missouri SB1377: Enacts regulations on automated license plate reader systems

Description: Enacts regulations on automated license plate reader systems
Collection: Legislation
Status date: Jan. 31, 2024
Status: Introduced
Primary sponsor: Mike Cierpiot (sole sponsor)
Last action: Second Read and Referred S Transportation, Infrastructure and Public Safety Committee (Feb. 8, 2024)

Category:
Data Governance
System Integrity (see reasoning)

The text explicitly addresses the regulation of automated license plate reader systems, which involves the use of computer algorithms to process data. While it touches upon the governance and management of technology through regulations, it does not deeply explore the broader social impacts of AI, data privacy concerns, or the integrity of the system beyond how it may apply to automated license plate readers. It discusses specific terms and rafts legal boundaries for usage without addressing wider nuances of AI's influence.


Sector:
Government Agencies and Public Services (see reasoning)

This bill directly pertains to government use of AI technology, specifically regarding public safety systems like license plate readers. It limits the use of these systems by governmental bodies and outlines associated data handling, which is pertinent to the regulation of AI in governmental contexts. The relevance is moderate since it discusses the implementation and implications of such technology in public agencies but lacks broader implications for other sectors.


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

Vermont S0184: An act relating to the temporary use of automated traffic law enforcement (ATLE) systems

Description: An act relating to the temporary use of automated traffic law enforcement (ATLE) systems
Collection: Legislation
Status date: May 10, 2024
Status: Passed
Primary sponsor: Martine Gulick (3 total sponsors)
Last action: Senate Message: Signed by Governor May 30, 2024 (May 10, 2024)

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

The text primarily focuses on the implementation of Automated Traffic Law Enforcement (ATLE) systems and Automated License Plate Recognition (ALPR) technologies. The usage of automated systems for traffic enforcement ties directly into discussions around AI and automation as it utilizes algorithms for monitoring and recording violations, which makes it pertinent to all categories. The Social Impact category is relevant due to the societal implications of deploying ATLE systems, including potential concerns about surveillance, accuracy in the use of this technology, and how penalties are enforced based on recorded data. The Data Governance category is relevant because the act discusses the collection, management, and retention of data collected by these systems, addressing the necessity of legitimate law enforcement purposes for data usage, which is necessary for privacy and accuracy considerations. The System Integrity category is relevant due to the references to operational checks, maintenance of accuracy, and the integrity of data collected which are crucial to ensuring the systems function correctly and are not misused. Finally, the Robustness category applies as it pertains to the implementation of standards and requirements for the operation of the ATLE systems, ensuring they are properly calibrated and tested, which relates to performance benchmarks and regulatory compliance.


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

This text is highly relevant to the Government Agencies and Public Services sector, as it directly involves the deployment of automated systems by the Agency of Transportation for public safety purposes. It also relates moderately to the Judicial System sector, given that the regulations concerning civil violations and the adjudication process are mentioned. The restrictions on data access and retention also touch on concerns relevant to the Privacy sector, but this is not a defined sector in the criteria given. However, the emphasis on law enforcement uses of the systems makes it primarily pertinent to government operations rather than other sectors.


Keywords (occurrence): automated (37) show keywords in context

United States SB4434: Modernizing Retrospective Regulatory Review Act

Description: A bill to improve retrospective reviews of Federal regulations, and for other purposes.
Collection: Legislation
Status date: May 23, 2024
Status: Introduced
Primary sponsor: Mike Lee (3 total sponsors)
Last action: Read twice and referred to the Committee on Homeland Security and Governmental Affairs. (May 23, 2024)

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

Mississippi HB529: Utility-type vehicles and side-by-sides; authorize operation of on public county and municipal roads and streets.

Description: An Act To Regulate The Operation Of Utility-type Vehicles (utvs) Or Side-by-sides On The Public County And Municipal Roads And Streets Within The State Of Mississippi; To Define Terms Used In This Act; To Require The Registration Of Utvs With The Department Of Revenue In The Same Manner As Passenger Motor Vehicles; To Authorize The Operation Of On County And Municipal Public Roads And Streets With Posted Speed Limit Of 55 Miles Per Hour Or Less; To Require Owners Of Utvs And Side-by-sides To ...
Collection: Legislation
Status date: Feb. 4, 2025
Status: Other
Primary sponsor: Steve Massengill (sole sponsor)
Last action: Died In Committee (Feb. 4, 2025)

Category: None (see reasoning)

The text primarily focuses on the regulation of utility-type vehicles (UTVs) and side-by-sides on public roads. While it includes some safety features that might relate to system integrity, it does not pertain to AI systems or their societal impact, data governance, or robustness in any significant way. AI-specific language such as 'autonomous vehicle' is mentioned briefly; however, it is not the focal point of the legislation. Therefore, relevance to the categories is minimal in all respects, mostly falling into a slightly relevant or not relevant area.


Sector: None (see reasoning)

The text does not explicitly involve any of the specified sectors. It does mention the operation and regulation of vehicles, potentially suggesting some relevance to Government Agencies and Public Services, but not to the extent that it falls under a significant legislative change or regulatory framework focused on AI in those areas. It thus rates very low on sector relevance.


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

South Dakota SB164: Prohibit the use of a deepfake to influence an election and to provide a penalty therefor.

Description: Prohibit the use of a deepfake to influence an election and to provide a penalty therefor.
Collection: Legislation
Status date: Feb. 25, 2025
Status: Engrossed
Primary sponsor: Liz Larson (9 total sponsors)
Last action: Remove from Consent Calendar H.J. 478 (March 6, 2025)

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

The text specifically addresses the use of deepfakes, which relates directly to the social impact by attempting to mitigate misinformation and potential harm to candidates through AI-generated content. It emphasizes the need for responsible use of technology, aiming to protect individuals and uphold the integrity of electoral processes. In addition, specifics about legal penalties and defenses indicate a strong relevance to legal frameworks, thereby touching on accountability and protection against harm. Therefore, it is crucial in the context of social impact legislation. Data governance is somewhat relevant as it discusses the integrity of the information being disseminated but doesn't directly address data management practices. System integrity is mentioned, as the legislation implicates ethical use of AI tools, but the primary focus remains on the social implications and the need for integrity within election processes. Similarly, robustness has marginal relevance but is overshadowed by more pressing concerns about misinformation and its societal ramifications.


Sector:
Politics and Elections
Judicial system (see reasoning)

The text addresses deepfakes in the context of their influence on elections, thus falling squarely within the relevance of the Politics and Elections sector. The implications of AI technology, specifically deepfakes, are discussed in a legislative context designed to regulate their use in the electoral process, aiming to protect candidates from manipulation and misinformation. Government Agencies and Public Services has slight relevance due to possible implications regarding enforcement by government entities, while Judicial System pertains moderately because it outlines legal instruments for redress. While there may be tangential connections to Private Enterprises, Labor, and Employment if considering marketing or campaigning practices, this connection isn’t strong. The text does not explicitly connect to other sectors like Healthcare or Academic and Research Institutions but does highlight the need for ethical norms around AI usage in public spheres, making it a clear fit for the Politics and Elections category.


Keywords (occurrence): artificial intelligence (3) deepfake (21) show keywords in context

North Carolina S580: DOT Legislative Changes.-AB

Description: DOT Legislative Changes.-AB
Collection: Legislation
Status date: April 4, 2023
Status: Introduced
Primary sponsor: Thomas McInnis (5 total sponsors)
Last action: Ref To Com On Rules and Operations of the Senate (April 5, 2023)

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