All Items
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.

Clear All

4770 results:


Washington HB1226: Making supplemental transportation appropriations for the 2023-2025 fiscal biennium.

Description: Making supplemental transportation appropriations for the 2023-2025 fiscal biennium.
Summary: This bill provides supplemental transportation appropriations for the 2023-2025 fiscal biennium, focusing on transportation funding, capital improvements, environmental initiatives, and traffic safety measures in Washington state.
Collection: Legislation
Status date: Jan. 13, 2025
Status: Introduced
Primary sponsor: Jake Fey (3 total sponsors)
Last action: Public hearing in the House Committee on Transportation at 4:00 PM. (Jan. 15, 2025)

Category: None (see reasoning)

The text is mainly focused on transportation appropriations and funding for projects; there is minimal relevance to social impact, data governance, system integrity, or robustness as it does not discuss AI systems, algorithms, or their implications. However, the mention of a 'public dataset under an open license' alludes to some aspect of data governance, but it is very limited and does not engage fully with the comprehensive requirements of this category. Consequently, all categories receive low scores, primarily because the central discussion revolves around financial appropriations without exploring AI directly or indirectly.


Sector: None (see reasoning)

The text focuses on transportation funding and appropriations without any mention of the sectors defined (such as politics, healthcare, public services, etc.) and thus does not provide specific relevance to political processes or public services either. This lack of direct connection results in low scores across all sectors as the text is fundamentally about budget appropriations, allocations to projects, and reports rather than usage or interactions of AI in any defined sector.


Keywords (occurrence): automated (15) autonomous vehicle (2) show keywords in context

New York A09312: Aligns state and local procurement laws with federal law prohibiting the procurement of certain information and communications technology and electronic parts or products which are determined to pose a risk to state and national security.

Description: Aligns state and local procurement laws with federal law prohibiting the procurement of certain information and communications technology and electronic parts or products which are determined to pose a risk to state and national security.
Summary: The bill prohibits New York state and local entities from procuring certain information technology deemed security risks by federal law, aiming to enhance state and national security compliance.
Collection: Legislation
Status date: Feb. 27, 2024
Status: Introduced
Primary sponsor: Jenifer Rajkumar (6 total sponsors)
Last action: ordered to third reading rules cal.503 (June 6, 2024)

Category:
System Integrity (see reasoning)

The text primarily focuses on the procurement restrictions regarding certain information and communications technology due to security risks. It explicitly mentions automated decision-making systems, but does not delve into the broader social impacts of AI, data governance surrounding AI systems, system integrity beyond procurement, or robustness in the context of AI performance. The explicit mention of automated decision-making could indicate some relevance to system integrity, but it's primarily about procurement and security matters.


Sector:
Government Agencies and Public Services (see reasoning)

The text's relevance is tangential to sectors like Government Agencies and Public Services, as it discusses government procurement procedures. However, it does not directly address the use of AI technologies in these contexts. There's minimal relevance to other sectors, as it does not pertain to politics, the judicial system, healthcare, private enterprises, academia, or international standards. The overarching theme regarding security and procurement impacts primarily government operations.


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

Washington HB1934: Establishing an artificial intelligence task force.

Description: Establishing an artificial intelligence task force.
Summary: The bill establishes an artificial intelligence task force in Washington to assess and recommend regulations for generative AI, ensuring safety, privacy, and civil rights protection while fostering innovation.
Collection: Legislation
Status date: Jan. 8, 2024
Status: Introduced
Primary sponsor: Travis Couture (22 total sponsors)
Last action: House Rules "X" file. (Feb. 20, 2024)

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

The text establishes an AI task force in Washington that addresses various societal considerations regarding the use of artificial intelligence, notably around equity, accountability, and transparency. These elements make the text relevant to Social Impact, particularly as it notes the risks of bias and harm posed by AI technologies. Furthermore, the text emphasizes responsible use and regulations, which align closely with Data Governance. The discussions around standards, protections, and human oversight point toward System Integrity, as the task force plans to recommend regulations to ensure accountability and security in AI functions. The consideration of benchmarks and compliance aligns with Robustness, especially since the task force will examine existing protocols and make recommendations. Overall, the text signals a proactive approach to the implications of AI in society, addressing key concerns associated with each of the categories.


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

The AI task force will examine the implications of AI technology across several sectors, including healthcare, labor, and law enforcement. The text directly engages with societal and governmental contexts, particularly in managing the impact of AI on vulnerable communities and ensuring that state-level practices reflect sound governance. However, it does not target legislation exclusively crafted for politics and elections, nor is it specifically tailored to the judicial system or academic settings. Therefore, while it broadly engages relevant sectors, some are more in focus than others.


Keywords (occurrence): artificial intelligence (28) machine learning (1) show keywords in context

Tennessee SB2460: AN ACT to amend Tennessee Code Annotated, Title 2; Title 4; Title 8; Title 38; Title 39 and Title 47, Chapter 18, relative to synthetic media.

Description: As introduced, creates a violation under the Tennessee Consumer Protection Act of 1977 for a person or entity that alters the appearance, action, or speech of an individual through the use of synthetic media in a communication that is knowingly distributed publicly with the intent to malign, slander, defame, or otherwise intentionally mislead the public and damage the reputation of the individual. - Amends TCA Title 2; Title 4; Title 8; Title 38; Title 39 and Title 47, Chapter 18.
Summary: The bill amends Tennessee law to regulate synthetic media, allowing individuals to seek damages if manipulated media is used maliciously against them, while requiring disclosures about alterations.
Collection: Legislation
Status date: Jan. 30, 2024
Status: Introduced
Primary sponsor: Raumesh Akbari (sole sponsor)
Last action: Assigned to General Subcommittee of Senate Commerce and Labor Committee (March 13, 2024)

Category:
Societal Impact
Data Governance (see reasoning)

The text explicitly addresses 'synthetic media' and 'artificial intelligence,' which are central to the discussion of the impact of AI on society. The legislation aims to mitigate potential harm from misrepresentation through AI-generated content, directly linking to issues of consumer protection and misinformation. Therefore, it falls under the category of Social Impact due to its focus on protecting individuals from malicious uses of AI technology. Data Governance is relevant because it involves how data regarding individuals is manipulated and ensured to be accurate. However, it does not directly cover data management practices related to AI systems beyond its implications for generated media. System Integrity is not prominently addressed since the bill does not specifically mention security or transparency measures for AI systems themselves, even though some aspects of integrity are implied through accountability. Robustness is less relevant as the bill does not discuss performance benchmarks or standards for AI systems, focusing instead on liabilities associated with misuse of AI. Thus, the relevant categories score highly because they address significant contemporary concerns tied to AI in society.


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

The legislation touches upon the implications of synthetic media in the context of misinformation and public perception, particularly regarding its impact on individuals. It does not specifically address AI's role in politics, which would pertain to elections. Government Agencies may be indirectly affected in their regulatory roles but are not the primary focus. The judicial system is relevant as individuals can seek injunctive relief, but this does not strongly align with the broader legislative focus. Healthcare, private enterprises, and academic institutions are not directly relevant to the content of the bill. International standards are also not addressed. The inclusion of NGOs may apply tangentially since they might work on issues of misinformation. The Hybrid, Emerging, and Unclassified sector once again does not fit as neatly as the principal sectors. Overall, the strongest relevance is to the impact on society through misinformation and personal reputation, hence the scores assigned.


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

California SJR2: Classified workers’ rights.

Description: Relative to classified workers.
Summary: The bill urges federal legislation to secure rights for classified workers, ensuring safe working conditions, competitive wages, job security, and access to benefits and professional development opportunities.
Collection: Legislation
Status date: March 3, 2025
Status: Introduced
Primary sponsor: Sabrina Cervantes (3 total sponsors)
Last action: Read second time and amended. Ordered to third reading. (March 27, 2025)

Category:
Societal Impact
Data Governance (see reasoning)

The text primarily addresses the rights and conditions of classified workers, focusing on their compensation, working conditions, job security, and the impact of electronic monitoring, data, algorithms, and artificial intelligence technology on their jobs. While it mentions AI and technology, it does so mainly in the context of seeking worker rights and protections related to these technologies, as well as not addressing how AI specifically affects their roles or the systems they work with. Thus, the relevance of the categories is assessed as follows: The Social Impact category is relevant as it relates to workers' rights and safety, which is crucial given AI's potential impact on these areas. Data Governance is relevant given the mention of algorithms and data collection in the workplace, although it's not a primary focus. System Integrity has some relevance due to the mention of monitoring and the need for safeguards but is not deeply explored. Robustness is not applicable since the text does not focus on performance benchmarks or compliance for AI systems.


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

The text discusses classified workers in educational settings, emphasizing their rights and how AI and technology may impact their work environments. The sector of Government Agencies and Public Services is relevant as it concerns employees working in public education systems. Private Enterprises, Labor, and Employment is relevant due to the discussion of worker rights and employment conditions; however, it is more focused on public sector workers. Other sectors like Politics and Elections or Healthcare do not find a strong connection in the context of this resolution.


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

United States HB9693: SAFE for Survivors Act of 2024 Security And Financial Empowerment for Survivors Act of 2024 Survivors’ Employment Sustainability Act

Description: To promote the economic security and safety of survivors of domestic violence, dating violence, sexual assault, or stalking, and for other purposes.
Summary: The SAFE for Survivors Act of 2024 aims to enhance economic security and safety for survivors of domestic violence, sexual assault, and stalking by providing protections like safe leave and unemployment compensation.
Collection: Legislation
Status date: Sept. 19, 2024
Status: Introduced
Primary sponsor: Debbie Dingell (11 total sponsors)
Last action: Referred to the Subcommittee on Health. (Dec. 17, 2024)

Category: None (see reasoning)

The text predominantly discusses the economic security and safety of survivors of domestic violence and related issues. AI's role is minimal, only mentioned in relation to deepfakes which raise concerns about consent, privacy, and potential misuse. However, there is no explicit broad discussion about the societal impact of AI or its governance in this context, leading to a lower relevance for all categories. Social Impact may be slightly relevant due to concerns about deepfakes contributing to victimization, but overall the content focuses on violence and support systems rather than AI systems per se. Data Governance, System Integrity, and Robustness do not connect well to the primary text because they do not address issues with data security, system transparency, or AI performance metrics.


Sector: None (see reasoning)

This legislation targets the issues faced by victims of domestic violence largely within private and public service realms, rather than specifically focusing on how AI intersects with these areas. The only touchpoint with AI is in the context of deepfakes, which is more about a component of technology rather than a broader intersection with political or social structures. Therefore, none of the sectors is highly relevant, with sectors like Government Agencies and Public Services receiving slight mention primarily because of systemic implications tied to how government handles such crises, but still remains at a low score due to lack of AI emphasis.


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

Hawaii SCR43: Strongly Supporting And Recommending The Implementation Of The Revised 2025 Hawaii Patient Bill Of Rights.

Description: Strongly Supporting And Recommending The Implementation Of The Revised 2025 Hawaii Patient Bill Of Rights.
Summary: The bill supports implementing the Revised 2025 Hawaii Patient Bill of Rights, ensuring clear communication from insurers, timely referrals, emergency care coverage, data protection, and patient autonomy in healthcare decisions.
Collection: Legislation
Status date: March 6, 2025
Status: Introduced
Primary sponsor: Carol Fukunaga (sole sponsor)
Last action: The committee(s) on HHS recommend(s) that the measure be PASSED, WITH AMENDMENTS. The votes in HHS were as follows: 4 Aye(s): Senator(s) San Buenaventura, Aquino, Hashimoto, Keohokalole; Aye(s) with reservations: none ; 0 No(es): none; and 1 Excused: Senator(s) Fevella. (March 24, 2025)

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

The text explicitly mentions AI in several sections, particularly in relation to oversight and usage in prior authorization processes (sections 8.2 and 8.3). The legislation emphasizes the need for human review of AI-generated denials, indicating a focus on maintaining control and transparency in automated decision-making within healthcare. Also, patient data protection combines with AI usage, which relates to the governance and ethical use of AI in healthcare settings. These aspects make the 'Social Impact' and 'System Integrity' categories relevant as they cover the implications of AI on patient rights and healthcare services. 'Data Governance' is also applicable due to the detailed requirements for personal data protection tied to the AI's operation. However, it doesn’t focus on performance benchmarks which makes 'Robustness' less relevant.


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

The text pertains significantly to the healthcare sector as it discusses patient rights and how healthcare providers should interact with AI technologies. It outlines specific rights that benefit patients, the obligations of insurers in using AI, and established oversight measures. This alignment makes it extremely relevant to the Healthcare sector. There's less relevance to sectors like Government Agencies and Public Services because the focus is more on patient rights rather than on broader governmental AI applications. Similarly, it doesn’t directly pertain to sectors like Politics and Elections, Judicial System, or Academic and Research Institutions which diminishes their relevance. The text does engage aspects of Private Enterprises, Labor, and Employment through its implications for insurers and healthcare providers, but it's not the primary focus.


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

Illinois HB2945: FOIA-ENGINEERING PROPOSALS

Description: Amends the Freedom of Information Act. Provides that proposals or bids submitted by engineering consultants in response to requests for proposal or other competitive bidding requests by the Department of Transportation or the Illinois Toll Highway Authority are exempt from disclosure under the Act.
Summary: This bill amends the Freedom of Information Act to exempt engineering proposals or bids submitted to the Department of Transportation or Illinois Toll Highway Authority from public disclosure, promoting confidentiality in the bidding process.
Collection: Legislation
Status date: Feb. 16, 2023
Status: Introduced
Primary sponsor: Michael Marron (sole sponsor)
Last action: Referred to Rules Committee (Feb. 16, 2023)

Category: None (see reasoning)

The text provided primarily concerns amendments to the Freedom of Information Act in Illinois that relate to the handling of proposals or bids submitted by engineering consultants. The amendments do not explicitly address AI technologies or issues. Therefore, the categories need to be evaluated based on how closely the text relates to AI in the context of social implications, governance of data, integrity of systems, or robustness of processes. Given that AI is not mentioned within the text and none of the categories of legislation directly apply, relevance is low across the board. However, there is a mention of 'automated data processing operations' in part (o), which may relate slightly to System Integrity, but it is minimal and does not explicitly discuss any AI systems or frameworks. Thus, all categories scored a 1, indicating that they are not relevant.


Sector: None (see reasoning)

The legislation does not mention the sectors outlined. There is no discussion regarding the impact of AI on political processes, public services, the judicial system, healthcare, business environments, academic institutions, international standards, nonprofit organizations, or hybrid/emerging sectors. The text solely revolves around legislative amendments that handle the management of bids and proposals with no link to AI applications or their sectors. As such, all sectors are rated 1 for not relevant.


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

United States SB2325: Algorithmic Justice and Online Platform Transparency Act

Description: A bill to prohibit the discriminatory use of personal information by online platforms in any algorithmic process, to require transparency in the use of algorithmic processes and content moderation, and for other purposes.
Summary: The Algorithmic Justice and Online Platform Transparency Act aims to prohibit discrimination in algorithmic processes by online platforms, ensuring user data transparency and equitable content moderation practices.
Collection: Legislation
Status date: July 13, 2023
Status: Introduced
Primary sponsor: Edward Markey (3 total sponsors)
Last action: Read twice and referred to the Committee on Commerce, Science, and Transportation. (July 13, 2023)

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

This legislation explicitly addresses the social impact of algorithmic processes, particularly focusing on discrimination, transparency, and user rights. Its provisions for requiring transparency and accountability from online platforms directly relate to the social consequences of AI through its influence on individuals and marginalized communities. The bill also discusses the risks associated with algorithmic decision-making, indicating concern for potential harm relevant to social dynamics, hence scoring high on social impact. In terms of data governance, the legislation stipulates specific requirements for data collection, transparency, and management of personal information which aligns directly with secure and accurate data practices. The references to algorithmic processes and the associated data practices link it moderately to the robustness and system integrity categories, but the focus on transparency and accountability strongly underscores the impact on social justice, earning a very high relevance score. Overall, this bill illustrates a strong need for ethical considerations in algorithm usage, reinforcing its relevance to all areas of potential social harm tied to AI, data governance, and systemic integrity, making it notably impactful.


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

The bill’s focus on online platforms directly engages with topics relevant to Private Enterprises, Labor, and Employment as it touches on algorithmic usage that affects job advertising and opportunities. Its references to content moderation and algorithmic processes also suggest strong implications for Government Agencies and Public Services, as they highlight how government regulatory measures can be informed by the transparency standards set for these platforms. There is an indirect relation to Nonprofits and NGOs for their roles in advocating for fair use of technology. However, the main impact is on the private sector regarding their interaction with AI, algorithmic processes, and data, resulting in a moderately high score in that area. The emphasis on algorithmic transparency and anti-discrimination is also crucial concerning governmental oversight in public services.


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

Alabama SB75: Appropriations from Education Trust Fund for the support, maintenance, and development of public education for fiscal year ending September 30, 2025.

Description: Appropriations from Education Trust Fund for the support, maintenance, and development of public education for fiscal year ending September 30, 2025.
Summary: This bill appropriates funds for the support, maintenance, and development of Alabama's public education for the fiscal year ending September 30, 2025, addressing debt service and capital needs.
Collection: Legislation
Status date: Feb. 7, 2024
Status: Introduced
Primary sponsor: Arthur Orr (sole sponsor)
Last action: Pending Senate Finance and Taxation Education (Feb. 7, 2024)

Category: None (see reasoning)

The text outlines appropriations for public education in Alabama, primarily focusing on financial allocations, programmatic areas, and compliance with financial management laws. There are no explicit references to AI or its impact. Thus, the categories concerning AI do not apply as there is no mention of social impact of AI, data governance regarding AI, integrity of AI systems, or robustness standards for AI. The text is focused on education funding, not on issues related to AI. Therefore, scores will be low for each category.


Sector: None (see reasoning)

The text pertains to the appropriations for public education which encompasses a broad range of educational programs and services. However, there is no specific mention of AI applications in the field of education, nor how it affects sectors like politics, healthcare, public service, etc. Without specific references or implications of AI, the relevance to any of the sectors is minimal. Hence, the scores reflect a lack of association with the sectors discussed.


Keywords (occurrence): artificial intelligence (1)

Minnesota SF1108: Online content discrimination prohibition

Description: Online content discrimination prohibition
Summary: This bill prohibits online content discrimination by requiring interactive computer services to refrain from restricting user accounts based on race, sex, political ideology, or religious beliefs, allowing civil action for violations.
Collection: Legislation
Status date: Feb. 2, 2023
Status: Introduced
Primary sponsor: Eric Lucero (3 total sponsors)
Last action: Referred to Judiciary and Public Safety (Feb. 2, 2023)

Category:
Societal Impact
Data Governance (see reasoning)

The text outlines a bill prohibiting online content discrimination, particularly relating to the use of algorithms to restrict user accounts based on race, sex, political ideology, or religious beliefs. This directly falls under the 'Social Impact' category as it highlights concerns about fairness and bias in online interactions, which can lead to discrimination based on sensitive attributes. The regulation of algorithms to uphold accountability aligns closely with the issues this category addresses. 'Data Governance' is also relevant as the bill pertains to how data (or content) can be restricted or discriminated against and reflects a need for oversight in the management of such data. 'System Integrity' might be slightly relevant due to the transparency mandate implied by the need for notifications when content is restricted. However, there are no explicit mentions of AI security or oversight in systems. 'Robustness' is not relevant as the bill does not address performance benchmarks or audit requirements. Overall, this text strongly aligns with 'Social Impact' and to a moderate extent with 'Data Governance'.


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

The text primarily pertains to the implications of AI in online environments and how content algorithms operate in practice. It discusses the interaction between users and interactive computer services which includes social media platforms, thus having a strong relationship with 'Politics and Elections' by implication, especially since political ideology is one of the parameters mentioned for discrimination. It has relevance to 'Government Agencies and Public Services' in terms of how these entities might regulate or be impacted by online content moderation. There is no specific mention of the 'Judicial System' as the text does not focus on legal decision-making processes but on civil actions user can take against providers. The healthcare, private enterprises, academic, international cooperation, and nonprofit sectors don't draw direct relevance from the text. Therefore, it is mostly relevant to the political context of how AI interacts with social discourse.


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

New Jersey S3432: Establishes Next New Jersey Program for artificial intelligence investments.

Description: Establishes Next New Jersey Program for artificial intelligence investments.
Summary: The Next New Jersey Program establishes tax credits to attract investments in artificial intelligence, promote job creation, and position New Jersey as an AI innovation leader.
Collection: Legislation
Status date: July 25, 2024
Status: Passed
Primary sponsor: Raj Mukherji (3 total sponsors)
Last action: Approved P.L.2024, c.49. (July 25, 2024)

Category:
Societal Impact
Data Governance (see reasoning)

This bill establishes the 'Next New Jersey Program,' which aims to promote investment in the field of artificial intelligence. It includes explicit references to AI-related innovations and acknowledges various AI-related activities, such as the development of AI algorithms and software, which directly connects to the social impact of AI in terms of job creation and economic development. It also establishes tax credits based on AI engagement, which may entail considerations of fairness and ethical implications in the labor market. Thus, there is a direct and significant connection to social impact, as these investments raise questions about equity and opportunity in technology access. Regarding data governance, while there are implications about managing data for AI systems, the bill lacks specificity around biases or inaccuracies. For system integrity, while there is foundational governance involved in managing AI-related businesses, there is minimal focus on overarching security protocols or transparency standards. Lastly, the robustness of AI systems isn't directly addressed in terms of performance benchmarks or certification processes. Therefore, the relevance scores vary based on the depth of AI engagement in each area related to the categories described.


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

The bill is particularly relevant to sectors that involve AI's development and usage in business, indicating strong ties to technology startups, and economic development related to AI innovations in New Jersey. It addresses the potential impact of AI in public and private sectors but does not focus on the political ramifications specifically, nor does it detail the application of AI within governmental agencies, the judicial system, or healthcare settings. While it highlights the importance of developing AI technologies, its primary intent appears to cater to the economic aspect rather than to a niche within established sectors. As such, it does not particularly align with the parameters of most sectors beyond 'Private Enterprises, Labor, and Employment' and 'Academic and Research Institutions', where there is some relevance to job creation and AI engagement in technology startups in research contexts.


Keywords (occurrence): artificial intelligence (8) machine learning (2) deep learning (1) show keywords in context

New Jersey A4936: Requires school districts to provide instruction on artificial intelligence; requires Secretary of Higher Education to develop artificial intelligence model curricula.

Description: Requires school districts to provide instruction on artificial intelligence; requires Secretary of Higher Education to develop artificial intelligence model curricula.
Summary: The bill mandates New Jersey school districts to teach artificial intelligence from K-12 and requires higher education institutions to offer related certificate and degree programs, promoting AI education and career pathways.
Collection: Legislation
Status date: Oct. 21, 2024
Status: Introduced
Primary sponsor: Reginald Atkins (4 total sponsors)
Last action: Introduced, Referred to Assembly Science, Innovation and Technology Committee (Oct. 21, 2024)

Category:
Societal Impact (see reasoning)

The text explicitly mentions the instruction of artificial intelligence across K-12 education and the development of AI curricula at the higher education level. As such, it has direct implications for the social impact of AI by ensuring students are educated on AI concepts, which could influence their understanding and engagement with technology in the future. The emphasis on responsible and ethical use of AI also pertains to social responsibility. For Data Governance, while there are underlying themes of how data might be used in AI education, the bill does not specify mandates for handling data, thereby making it less relevant. For System Integrity and Robustness, though related to education about AI systems, the legislation primarily focuses on curricula development rather than ensuring security or benchmarks of AI technologies. Therefore, the primary relevance appears to be in the realm of Social Impact regarding educational transformation and fostering responsible use of AI.


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

The legislation primarily addresses the incorporation of artificial intelligence instruction in educational settings, relevant to both K-12 education and higher education systems. It mandates public educational institutions to offer programs specific to AI, which directly affects governmental operations in educational contexts. While there is a connection to workforce development and preparing students for careers in AI, it does not explicitly address sectors like healthcare, politics, or other industries. Its focal point remains on academic institutions rather than private enterprises, nonprofits, or other sectors. Thus, its strongest relevance lies within the academic and research realm, while it could moderately affect the governmental sector in education due to its regulatory nature.


Keywords (occurrence): artificial intelligence (30) automated (2) show keywords in context

North Carolina S735: AI Innovation Trust Fund

Description: AI Innovation Trust Fund
Summary: The AI Innovation Trust Fund establishes a non-reverting fund in North Carolina to support responsible AI development through grants and entrepreneurship programs, while ensuring protections against misuse and harm.
Collection: Legislation
Status date: March 25, 2025
Status: Introduced
Primary sponsor: DeAndrea Salvador (6 total sponsors)
Last action: Re-ref Com On Appropriations/Base Budget (March 26, 2025)

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

The AI Innovation Trust Fund outlines important regulations and provisions concerning the development, deployment, and safety of artificial intelligence systems in North Carolina. It touches upon themes such as responsible innovation, grants for AI development, as well as potential risks associated with AI technologies, which directly aligns with the Social Impact and System Integrity categories. The focus on collaboration and governance suggests a comprehensive understanding of the societal implications of AI and the security measures necessary for its integrity. The trust fund seeks to ensure that AI technologies do not infringe on individual rights, outlining measures that developers must adhere to. There are also considerations for fairness and accountability in the development of AI models. Overall, this bill is highly relevant to all categories as it engages with the intersection of AI technology and its broader social implications, data governance, and system integrity, promoting secure and responsible AI practices.


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

The text primarily addresses the creation of an AI Innovation Trust Fund, which emphasizes collaboration between various stakeholders, including government agencies and research institutions. While it doesn’t specifically categorize legislation based exclusively on one sector, its references to collaboration with research institutions and state agencies indicate strong relevance to the Government Agencies and Public Services sector. The bill outlines development frameworks for AI, specifically targeting its societal applications, suggesting a broader implication in sectors like Private Enterprises and Academic Institutions due to its provisions related to grants and safety measures. Given these connections, it is moderately relevant overall to sectors that deal with the use and regulation of AI across various environments.


Keywords (occurrence): artificial intelligence (27) show keywords in context

Maryland HB1174: State Government - Technology Advisory Commission - Established

Description: Establishing the Technology Advisory Commission to study and make recommendations on technology and science developments and use in the State; and requiring the Commission to submit a report on its activities and recommendations to the Governor and the General Assembly by December 31 each year.
Summary: The bill establishes a Technology Advisory Commission in Maryland to study technology and science, advise on ethical artificial intelligence use, and make recommendations to enhance productivity and responsibility in technological applications.
Collection: Legislation
Status date: March 18, 2024
Status: Engrossed
Primary sponsor: Terri Hill (25 total sponsors)
Last action: Referred Education, Energy, and the Environment (March 18, 2024)

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

The text introduces the Technology Advisory Commission, specifically focusing on the study and recommendations related to technology and science in the state. It highlights concepts related to 'Algorithmic Decision Systems' and 'Responsible Artificial Intelligence' emphasizing ethical, transparent, and accountable design, development, and deployment of AI technologies. Given this focus, the legislation has clear relevance to potential social impacts of AI, responsible governance of data management, the integrity of the systems put in place, and the robustness of AI technologies in accordance with the established standards. Hence, I find that Social Impact is very relevant due to the emphasis on the ethical use of AI and addressing physical harm; Data Governance is moderately relevant due to aspects of processing and management; System Integrity is very relevant because of the need for oversight and security; and Robustness is also moderately relevant as it deals with standards and benchmarks for AI performance.


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

The proposed commission has broad implications across various sectors. The mention of interdisciplinary members from educational institutions and government agencies suggests relevance to Government Agencies and Public Services, as it will advise on responsible AI use in public technology applications. The focus on Algorithmic Decision Systems indicates a consideration for Judicial System challenges where AI may be influential in legal decision-making processes. Given that AI technologies are increasingly influencing various sectors, it also touches upon aspects of Private Enterprises, Labor, and Employment. However, it does not strongly align itself with other sectors like Healthcare or International Cooperation. Thus, Government Agencies and Public Services scores high; Judicial System moderately due to its implications on legal frameworks; Private Enterprises scores moderately but with less emphasis; and the remaining sectors receive low scores.


Keywords (occurrence): artificial intelligence (5) machine learning (5) automated (1) algorithm (1)

Connecticut SB00002: An Act Concerning Artificial Intelligence.

Description: To (1) establish various requirements concerning artificial intelligence systems, (2) require the Department of Economic and Community Development to (A) establish an artificial intelligence regulatory sandbox program, (B) plan to establish a technology transfer program, (C) establish a confidential computing cluster, (D) conduct a "CT AI Symposium", and (E) design an algorithmic computer model, (3) require the Board of Regents for Higher Education to establish a "Connecticut AI Academy" and ...
Summary: The bill establishes regulations for high-risk artificial intelligence systems, aiming to mitigate algorithmic discrimination risks. It requires transparency and accountability from developers and integrators to protect consumers effectively.
Collection: Legislation
Status date: Jan. 8, 2025
Status: Introduced
Primary sponsor: General Law Committee (38 total sponsors)
Last action: Filed with Legislative Commissioners' Office (March 24, 2025)

Category:
Societal Impact
Data Governance (see reasoning)

The text explicitly addresses algorithmic discrimination and unfair treatment associated with artificial intelligence, making it highly relevant to the Social Impact category, which encompasses issues of fairness and bias in AI systems. The legislation is aimed at consumer protection, particularly against the risks that AI may pose to individuals. This directly aligns with the category's focus on societal harm and fairness metrics. In terms of Data Governance, the text implies the need for accurate and fair AI algorithms to protect consumers but does not provide sufficient detail to warrant a higher score. It does not address data security or management practices explicitly, resulting in a lower score in this category. The System Integrity category is not applicable here, as there are no mentions of security measures or transparency standards related to AI systems within the text. Similarly, while some aspects of the legislation may hint at performance and compliance monitoring, the overarching focus is on safeguarding consumers from discrimination rather than robustness metrics, which results in a moderate relevance to Robustness. Overall, the most pertinent categorization is Social Impact due to the emphasis on accountability for AI systems and their treatment of consumers.


Sector:
Government Agencies and Public Services (see reasoning)

The text's primary focus on protecting consumers from algorithmic discrimination via the regulation of AI technologies suggests strong relevance to the Government Agencies and Public Services sector, as these regulations will likely impact how government agencies work with AI technologies to serve the public. However, it lacks specific mention of government operations or AI usage within these contexts, leading to a slightly lower relevance score. The legislation does not address aspects related to Politics and Elections or the Judicial System directly, consequently receiving lower scores in those sectors. Similarly, the text does not focus on healthcare, labor, or academic institutions, and while nonprofit concerns could be tangentially relevant, they are minimally addressed. Lastly, there's no significant mention of international cooperation, so that category is marked with the lowest score.


Keywords (occurrence): artificial intelligence (240) machine learning (1) neural network (1) automated (3) foundation model (3) show keywords in context

United States SB1101: Simplify, Don’t Amplify the IRS Act

Description: A bill to amend the Social Security Act to remove the restriction on the use of Coronavirus State Fiscal Recovery funds, to amend the Internal Revenue Code of 1986 to codify the Trump administration rule on reporting requirements of exempt organizations, and for other purposes.
Summary: The "Simplify, Don’t Amplify the IRS Act" aims to ease IRS reporting requirements for exempt organizations, enhance taxpayer privacy, and restrict IRS enforcement powers, particularly for low-income individuals.
Collection: Legislation
Status date: March 30, 2023
Status: Introduced
Primary sponsor: Mike Braun (2 total sponsors)
Last action: Read twice and referred to the Committee on Finance. (March 30, 2023)

Category:
Data Governance (see reasoning)

The text of this bill largely focuses on amending tax administration aspects and financial practices related to the Internal Revenue Service (IRS) without addressing broader implications of AI on society, data governance, system integrity, or benchmarking of AI systems. However, the use of artificial intelligence and neural machine learning is mentioned in relation to improving the IRS audit process and analyzing tax gap data. This is a specific and limited integration of AI that primarily concerns operational efficacy rather than its societal impact, data practices, or standards for reliability. As such, while there is a mention of AI, the topics addressed in this bill do not deeply intersect with the category definitions.


Sector:
Government Agencies and Public Services (see reasoning)

The bill references the IRS's intentions to implement AI for improving audit outcomes, but it does not engage with broader sector-specific matters such as regulation of AI in public services or implications for labor markets. The mention of AI is specifically in the context of calculations and efficiency for the IRS, which may relate more closely to governance rather than any overarching changes in sector norms or practices. There is minimal relevance to other defined sectors that suggest a transformative AI influence. Hence, scores vary depending on the context in which AI is mentioned.


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

North Carolina S624: AI Chatbots - Licensing/Safety/Privacy

Description: AI Chatbots - Licensing/Safety/Privacy
Summary: Senate Bill 624 regulates AI chatbots in North Carolina, instituting licensing and safety standards, particularly for those managing health information, to enhance data privacy and user protection.
Collection: Legislation
Status date: March 25, 2025
Status: Introduced
Primary sponsor: Jim Burgin (sole sponsor)
Last action: Ref To Com On Rules and Operations of the Senate (March 26, 2025)

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

The text primarily focuses on the licensing, safety, and privacy of AI chatbots. Given the substantial role AI plays in the operation of chatbots, all sections of the legislation explicitly mention AI and its implications. The most relevant category here is 'Social Impact,' as it addresses consumer protection and psychological safety concerning chatbot use. The 'Data Governance' category is also pertinent, given the regulations on data collection, usage, and user consent, which are central to privacy practices in this legislation. The 'System Integrity' category is relevant due to mentions of security measures, oversight, and human intervention protocols in chatbot operations. The ‘Robustness’ category has lower relevance, as it is focused more on performance benchmarks for AI systems rather than on safety, licensing, and privacy concerns. Overall, the text heavily aligns with the social implications and governance issues associated with AI in stakeholder interactions.


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

The legislation explicitly pertains to AI chatbots, which influences how services are provided and regulated within various sectors. The 'Healthcare' sector is particularly relevant because the text discusses chatbots that handle sensitive health information and imposes strict licensing requirements for such use. The 'Government Agencies and Public Services' sector is also relevant, as the regulation originates from the state Assembly, influencing public standards for chatbot services. The 'Private Enterprises, Labor, and Employment' sector is involved, given how businesses may deploy these AI chatbots for customer interaction, potentially affecting job functions related to customer service. Other sectors like 'Politics and Elections' or 'Judicial System' do not relate closely to the content of this text. 'Academic and Research Institutions' might also have marginal relevance due to potential educational chatbots but is very limited.


Keywords (occurrence): artificial intelligence (5) machine learning (1) chatbot (47) show keywords in context

Hawaii HB726: Relating To A Statewide Data And Artificial Intelligence Governance And Decision Intelligence Center.

Description: Establishes and appropriates funds for a data and artificial intelligence governance and decision intelligence center and necessary positions to improve data quality and data sharing statewide.
Summary: The bill establishes a statewide Data and Artificial Intelligence Governance and Decision Intelligence Center in Hawaii to enhance data quality, sharing, interoperability, and responsible AI use among government agencies.
Collection: Legislation
Status date: Jan. 21, 2025
Status: Introduced
Primary sponsor: Ikaika Hussey (6 total sponsors)
Last action: Referred to ECD, FIN, referral sheet 2 (Jan. 21, 2025)

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

The text explicitly includes terms like 'data and artificial intelligence governance', 'machine learning', and 'decision intelligence', indicating a strong focus on the implications of AI on data quality and sharing. It discusses the responsible use of AI, which is closely linked to the social impact that AI systems can have on citizens, such as promoting transparency and efficiency in government operations, thus aligning strongly with the Social Impact category. It also emphasizes the need for accurate data management and governance of AI technologies across state agencies, which is related to Data Governance. There are provisions for system integrity such as secured data sharing and proper access control, which relate to ensuring the robustness and accountability of AI systems, thus aligning moderately with System Integrity. However, the text does not directly address benchmarks or performance evaluation of AI technologies, making the relevance to Robustness less pronounced. Overall, the text falls strongly within the Social Impact and Data Governance categories, with some relevance noted for System Integrity.


Sector:
Government Agencies and Public Services (see reasoning)

There is significant relevance of the text to the Government Agencies and Public Services sector, as it focuses on establishing a governance center directly linked to the use of AI by state agencies for improving data collection and sharing for public services. The emphasis on increasing citizen satisfaction and improving government performance aligns closely with this sector. Although there are mentions of potential impacts on other sectors, such as labor and public interest concerns from AI applications, the primary focus remains within the governmental context. Therefore, the Government Agencies and Public Services sector will receive a high score whereas the connections to Political and Elections, Judicial System, Healthcare, Private Enterprises, Academic Institutions, International Cooperation, Nonprofits, or Hybrid sectors are less pronounced and not directly applicable to this text.


Keywords (occurrence): artificial intelligence (19) machine learning (3) show keywords in context

Massachusetts S2379: Relative to providing multimodal transportation technologies

Description: For legislation relative to fully autonomous vehicle and human drivers. Transportation.
Summary: This bill establishes regulations for the operation of fully autonomous vehicles and automated driving systems in Massachusetts, outlining licensing, safety standards, and the creation of on-demand autonomous vehicle networks to enhance multimodal transportation.
Collection: Legislation
Status date: Feb. 27, 2025
Status: Introduced
Primary sponsor: William Driscoll (sole sponsor)
Last action: House concurred (Feb. 27, 2025)

Keywords (occurrence): automated (25) autonomous vehicle (25) show keywords in context
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