...emonstrate that its marketing, underwriting, rating, claims handling, fraud investigations, and any algorithm or model used for those business practices do not disparately impact any group of customers based on race, color, national or ethnic origin, religion, sex, sexual orientation, disability, gender iden...
...strate 21that its marketing, underwriting, rating, claims handling, 22fraud investigations, and any algorithm or model used for 23those business practices do not disparately impact any group 24of customers based on race, color, national or ethnic origin, 25religion, sex, sexual orientation, disability, gende...
4932 results:
Description: Amends the Illinois Insurance Code. Provides that the amendatory Act may be referred to as the Motor Vehicle Insurance Fairness Act. Provides that no insurer shall refuse to issue or renew a policy of automobile insurance based in whole or in part on specified prohibited underwriting or rating factors. Sets forth factors that are prohibited with respect to underwriting and rating a policy of automobile insurance. Sets forth provisions concerning the use of territorial factors. Provides that e...
Summary: The Motor Vehicle Insurance Fairness Act prohibits insurers from using discriminatory factors in automobile insurance underwriting, ensuring fair practices, transparency, and public participation in rate changes.
Collection: Legislation
Status date: Feb. 6, 2024
Status: Introduced
Primary sponsor: Javier Cervantes
(5 total sponsors)
Last action: Added as Chief Co-Sponsor Sen. Willie Preston (Feb. 20, 2024)
Category:
Societal Impact
Data Governance (see reasoning)
Sector:
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): algorithm (2) show keywords in context
Societal Impact
Data Governance (see reasoning)
The text discusses amendments to the Illinois Insurance Code, specifically regarding the use of algorithms and models in insurance underwriting and rating practices. It prohibits discrimination based on various underwriting factors and mandates that insurers demonstrate that their practices do not have a disparate impact on different groups. This is particularly relevant to the category of Social Impact as it tackles issues of bias and fairness in automated systems. It touches upon Data Governance as well, since the legislation requires transparency in the use of algorithms affecting insurance decisions. However, there is less emphasis on System Integrity and Robustness, given the document’s main focus on fairness and non-discrimination rather than security or performance benchmarks.
Sector:
Private Enterprises, Labor, and Employment (see reasoning)
The text is primarily focused on regulations related to the insurance sector, particularly regarding automobile insurance and the fairness of insurance practices. It mentions algorithms and underwriting in the context of ensuring non-discrimination, which are relevant to Private Enterprises, Labor, and Employment. However, it does not specifically address political legislation, government agencies, healthcare, academia, or international cooperation. The information primarily addresses practices within the private insurance sector, as it pertains to how insurance companies operate with respect to algorithms.
Keywords (occurrence): algorithm (2) show keywords in context
Description: Establishes the position of chief artificial intelligence officer and such person's functions, powers and duties; including, but not limited to, developing statewide artificial intelligence policies and governance, coordinating the activities of any and all state departments, boards, commissions, agencies and authorities performing any functions using artificial intelligence tools; makes related provisions.
Summary: The bill establishes a Chief Artificial Intelligence Officer in New York to develop statewide AI policies, coordinate state agencies on AI use, and ensure compliance with laws and ethical standards regarding AI systems.
Collection: Legislation
Status date: June 4, 2024
Status: Engrossed
Primary sponsor: Kristen Gonzalez
(3 total sponsors)
Last action: referred to governmental operations (June 4, 2024)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Academic and Research Institutions
International Cooperation and Standards (see reasoning)
Keywords (occurrence): artificial intelligence (36) machine learning (1) automated (12) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The legislation very directly relates to the implementation and oversight of artificial intelligence systems at the state level, which inherently involves considerations of social impact, data governance, system integrity, and robustness. It creates a dedicated role (Chief Artificial Intelligence Officer) to oversee the policies, governance, and usage of AI tools across various governmental departments. Such an establishment is critical for ensuring that societal impacts—like safety, privacy, and discrimination—are appropriately managed (Social Impact). The legislation outlines the duties of the AI officer to ensure data security, privacy, and compliance with laws (Data Governance). It also stipulates oversight measures and audits for AI systems, supporting transparency and accountability within systems (System Integrity). Lastly, it mandates the development of standards and metrics for AI performance, contributing to benchmarks for robustness. All these aspects are closely intertwined with AI governance and responsible usage, thus demanding a comprehensive approach to scoring across the categories.
Sector:
Government Agencies and Public Services
Academic and Research Institutions
International Cooperation and Standards (see reasoning)
The text addresses the role of AI across various government activities, ensuring that its application is ethical, secure, and effective. Consequently, it fits under 'Government Agencies and Public Services' as it centers on establishing a framework for AI governance within state operations and enhances the efficiency of services delivered. While it does not directly mention the judicial system or healthcare, the consideration for fairness and audit within government functions can hint at a broader impact affecting those sectors too. However, its primary focus remains on government functions, thereby warranting a higher relevance score in this sector.
Keywords (occurrence): artificial intelligence (36) machine learning (1) automated (12) show keywords in context
Description: Prohibits collecting of certain costs associated with offshore wind projects from ratepayers.
Summary: This bill prohibits New Jersey ratepayers from being charged for certain costs related to offshore wind projects, aiming to protect consumers from financial burdens associated with these initiatives.
Collection: Legislation
Status date: April 11, 2024
Status: Introduced
Primary sponsor: Holly Schepisi
(sole sponsor)
Last action: Introduced in the Senate, Referred to Senate Environment and Energy Committee (April 11, 2024)
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): algorithm (1) show keywords in context
The text primarily focuses on legislative measures dealing with offshore wind projects and associated costs for ratepayers, with no direct references to AI technologies or considerations. Thus, none of the categories can be deemed relevant based on their specific definitions. There are no discussions of social impacts related to AI, issues of data governance in AI systems, system integrity concerning AI, or robustness of AI technologies within the context of this text. Overall, the text does not touch on AI topics at all, leading to scores of 1 for all categories.
Sector: None (see reasoning)
The legislation makes no mention or implications regarding the use of AI within the sectors defined, especially concerning political campaigns, governmental AI applications, judicial systems using AI, healthcare AI integration, impacts on private sector labor and employment regarding AI, academic and research institution applications of AI, international standards pertaining to AI, or nonprofit usage of AI. Hence, all sectors receive a score of 1.
Keywords (occurrence): algorithm (1) show keywords in context
Description: A bill to establish artificial intelligence standards, metrics, and evaluation tools, to support artificial intelligence research, development, and capacity building activities, to promote innovation in the artificial intelligence industry by ensuring companies of all sizes can succeed and thrive, and for other purposes.
Summary: The Future of Artificial Intelligence Innovation Act of 2024 aims to establish standards and tools for AI, fostering research, development, and innovation across all company sizes to support the AI industry.
Collection: Legislation
Status date: April 18, 2024
Status: Introduced
Primary sponsor: Maria Cantwell
(9 total sponsors)
Last action: Placed on Senate Legislative Calendar under General Orders. Calendar No. 725. (Dec. 18, 2024)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Academic and Research Institutions
International Cooperation and Standards
Nonprofits and NGOs (see reasoning)
Keywords (occurrence): artificial intelligence (171) machine learning (1) automated (9) foundation model (1) algorithm (2) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text discusses the establishment of artificial intelligence standards, evaluation tools, and a safety institute, emphasizing the relevance to Social Impact through its focus on enhancing AI standards for public benefit. It also fits under System Integrity as it addresses measures for ensuring the reliability and security of AI systems through the collaboration of various federal agencies and development of best practices. Data Governance is relevant as the bill includes mandates for developing guidelines related to the secure and ethical use of AI, thus ensuring data practices are considered. Robustness is also pertinent as the text aims to create metrics and benchmarks for evaluating AI performance, including compliance with international standards. Overall, the text aims to enhance the safety, governance, and utility of AI technology, making all categories interconnected and significantly relevant to the legislation.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Academic and Research Institutions
International Cooperation and Standards
Nonprofits and NGOs (see reasoning)
This legislation is relevant across multiple sectors but most prominently in Government Agencies and Public Services as it discusses the application of AI standards and evaluation tools for improving governmental AI service delivery. International Cooperation and Standards also holds relevance due to the mention of partnerships and collaborations with international entities to align AI standards. Academic and Research Institutions are included as the text refers to partnerships with universities for research purposes. The text does not specifically target any sectors such as Politics and Elections or Healthcare, resulting in lower scores for those areas. Overall, it addresses the intersection between AI innovation, government efficiency, and international collaboration.
Keywords (occurrence): artificial intelligence (171) machine learning (1) automated (9) foundation model (1) algorithm (2) show keywords in context
Description: A bill to amend the National Quantum Initiative Act to provide for a research, development, and demonstration program, and for other purposes.
Summary: The Department of Energy Quantum Leadership Act of 2024 amends the National Quantum Initiative Act to establish a comprehensive program for research, development, and demonstration in quantum technology, enhancing U.S. leadership and workforce in this field.
Collection: Legislation
Status date: Aug. 1, 2024
Status: Introduced
Primary sponsor: Richard Durbin
(5 total sponsors)
Last action: Placed on Senate Legislative Calendar under General Orders. Calendar No. 633. (Nov. 21, 2024)
Category:
Data Governance
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Academic and Research Institutions
International Cooperation and Standards (see reasoning)
Keywords (occurrence): artificial intelligence (2) machine learning (1) algorithm (2) show keywords in context
Data Governance
Data Robustness (see reasoning)
The 'Department of Energy Quantum Leadership Act of 2024' has substantial implications for AI, particularly through its explicit mention of machine learning within the context of quantum computing and advanced computational systems. It recognizes the intersection of quantum technologies with AI and machine learning applications, which suggests a direct impact on data processing and decision-making models. The initiative's purpose of advancing quantum science can have clear societal implications in terms of ethical uses and the governance of AI technologies as they converge with quantum capabilities. However, it does not directly address issues related to AI’s social impact, data governance, system integrity, or robustness without exploring their ramifications. Thus, it aligns partially with these categories of legislation but not predominantly in any single focus.
Sector:
Government Agencies and Public Services
Academic and Research Institutions
International Cooperation and Standards (see reasoning)
This legislation primarily pertains to the academic and research sectors through its focus on developing quantum information science and associated technologies. However, it also impacts governmental and enterprise sectors as it addresses workforce development, commercialization, and public institution collaboration in advancing quantum technology applications, which can indirectly influence AI sectors. The mention of AI and machine learning accelerators suggests a potential overlap with industrial applications but is not limited strictly to corporate practices. Thus, while the primary emphasis is academic, there are moderately relevant lines pertaining to government and private enterprise applications.
Keywords (occurrence): artificial intelligence (2) machine learning (1) algorithm (2) show keywords in context
Description: Establishes Office of Cybersecurity Infrastructure.
Summary: The bill establishes the Office of Cybersecurity Infrastructure in New Jersey to develop and implement cybersecurity and AI policies, ensuring secure interactions between public and private organizations and residents.
Collection: Legislation
Status date: Nov. 14, 2024
Status: Introduced
Primary sponsor: Robert Karabinchak
(2 total sponsors)
Last action: Introduced, Referred to Assembly Science, Innovation and Technology Committee (Nov. 14, 2024)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Nonprofits and NGOs (see reasoning)
Keywords (occurrence): artificial intelligence (2) machine learning (1) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text discusses the establishment of the Office of Cybersecurity Infrastructure, which is tasked with establishing AI policies for the integration of AI into public and private institutions. The mention of 'AI policies' implies a regulatory framework that could impact social dynamics and governance structures, hence relating to social impact. Data governance is also relevant, as the bill focuses on secure technology integration that could involve data-related legislation. System integrity and robustness may see relevance through the establishment of controls for AI integration. Since the act involves responsibilities for the cybersecurity and integrated AI technologies in state functions, it supports these categories significantly. However, the primary focus remains on the societal impacts of AI through the lens of cybersecurity and governance.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Nonprofits and NGOs (see reasoning)
The bill is most relevant to the Government Agencies and Public Services sector as it pertains directly to the establishment of a governmental office that oversees cybersecurity infrastructure and the integration of AI in state affairs. It will likely influence all public service sectors through the introduction of AI policies. It has less direct relevance to other sectors such as Politics and Elections, Healthcare, and Private Enterprises, as those contexts are not explicitly covered within the scope of the text.
Keywords (occurrence): artificial intelligence (2) machine learning (1) show keywords in context
Description: A bill to amend the Federal Election Campaign Act of 1971 to provide further transparency for the use of content that is substantially generated by artificial intelligence in political advertisements by requiring such advertisements to include a statement within the contents of the advertisements if generative AI was used to generate any image, audio, or video footage in the advertisements, and for other purposes.
Summary: The AI Transparency in Elections Act of 2024 mandates that political advertisements disclose the use of artificial intelligence-generated content, enhancing transparency in political communications.
Collection: Legislation
Status date: March 6, 2024
Status: Introduced
Primary sponsor: Amy Klobuchar
(2 total sponsors)
Last action: Placed on Senate Legislative Calendar under General Orders. Calendar No. 389. (May 15, 2024)
Category:
Societal Impact
System Integrity (see reasoning)
Sector:
Politics and Elections (see reasoning)
Keywords (occurrence): artificial intelligence (12) machine learning (2) show keywords in context
Societal Impact
System Integrity (see reasoning)
The text of the AI Transparency in Elections Act of 2024 explicitly addresses the use of artificial intelligence in political advertisements, including definitions and requirements related to generative artificial intelligence. The bill mandates that any advertisement employing content generated or significantly altered by AI must include clear disclaimers. It directly relates to social impact in terms of misinformation and public trust in election processes. The need for accountability in AI-generated media is also emphasized, impacting consumer protection regarding misinformation. Thus, it conveys a strong relevance to both Social Impact and System Integrity, while the relevance to Data Governance and Robustness is less pronounced since the primary focus is on transparency in communications rather than data management or performance benchmarks. The respective scores reflect the identified significance of each area to the text.
Sector:
Politics and Elections (see reasoning)
The legislation focuses on political advertisements and their regulation, particularly in the electoral context. It includes the use of AI in political communication and seeks to enhance transparency to safeguard the integrity of electoral processes, thus making it highly relevant to the Politics and Elections sector. The mention of generative AI elements provides substantial context for regulation within this sector. Other sectors like Government Agencies and Public Services, Judicial System, and Healthcare show minimal direct relevance since the text does not primarily deal with those areas. Scores are allocated based on this evaluation of direct relevance to the respective sectors.
Keywords (occurrence): artificial intelligence (12) machine learning (2) show keywords in context
Description: To protect the safety of children on the internet.
Summary: The Kids Online Safety Act aims to protect children's safety on the internet by mandating high-impact online platforms to implement safeguards against mental health issues, compulsive usage, and exploitative behavior, while ensuring transparency and parental controls.
Collection: Legislation
Status date: April 9, 2024
Status: Introduced
Primary sponsor: Gus Bilirakis
(65 total sponsors)
Last action: Ordered to be Reported (Amended) by Voice Vote. (Sept. 18, 2024)
Category:
Societal Impact
Data Governance (see reasoning)
Sector:
Government Agencies and Public Services
Judicial system
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): machine learning (1) automated (3) recommendation system (6) algorithm (13) show keywords in context
Societal Impact
Data Governance (see reasoning)
The Kids Online Safety Act explicitly addresses the safety of children on the internet. Although there is limited direct reference to AI technologies, specific aspects relate to how AI-driven personalized recommendation systems impact minors. This necessitates an understanding of the social implications of these technologies, particularly regarding mental health and compulsive usage. The bill implies an awareness of possible AI-related harms (like algorithmic manipulation) and proposes safeguards and transparency, connecting it to social impact. Overall, its relevance to social impact is considerable, while it shows moderate relevance to data governance concerning the management of personal data and algorithms for minors. The need for system integrity measures is recognized but less emphasized, and robustness is not directly addressed. Thus, scores will reflect varying extents of relevance based on these observations.
Sector:
Government Agencies and Public Services
Judicial system
Private Enterprises, Labor, and Employment (see reasoning)
The Kids Online Safety Act pertains primarily to protecting minors in online environments, which encompasses aspects of Government Agencies and Public Services through providing guidelines for online platforms, and additionally touches on Private Enterprises, Labor, and Employment as it regulates the responsibilities of online companies. There is also a potential indirect relevance to Judicial System concerning the legal implications of data protection for minors and consequences for violations. Its connection to Healthcare is less direct, but mental health issues are discussed; however, it does not delve deeply into any medical implementations. Thus, the act has a focus on specific jurisdictions but does not encompass fully any singular sector as per the definitions given.
Keywords (occurrence): machine learning (1) automated (3) recommendation system (6) algorithm (13) show keywords in context
Description: To reauthorize wildlife habitat and conservation programs, and for other purposes.
Summary: The Servicemember Quality of Life Improvement and National Defense Authorization Act for Fiscal Year 2025 authorizes military funding, personnel strengths, and various defense activities to enhance the quality of life for servicemembers.
Collection: Legislation
Status date: Dec. 23, 2024
Status: Passed
Primary sponsor: David Joyce
(13 total sponsors)
Last action: Became Public Law No: 118-159. (Dec. 23, 2024)
Category:
Societal Impact
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (136) machine learning (8) automated (32) large language model (1) algorithm (1) show keywords in context
Societal Impact
System Integrity
Data Robustness (see reasoning)
The legislation primarily focuses on military activities, personnel management, and the authorization of funds for various defense programs. However, it includes specific references to artificial intelligence, such as Section 221, which addresses defining the AI workforce, and Section 225, which discusses the duties related to AI models and technologies. Given that these references indicate a clear connection to AI's role in defense strategies and personnel requirements, several categories are relevant. The strongest relevance is to 'System Integrity' due to mandates for controlling AI systems, followed closely by 'Robustness' given the focus on AI performance benchmarks and compliance. 'Social Impact' is relevant but to a lesser degree, and 'Data Governance' has weak associations without explicit connections to data management.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
This legislation is primarily related to 'Government Agencies and Public Services' as it lays out provisions for military operations, funding, and the enhancement of defense capabilities. It directly involves the Department of Defense and military personnel, making it highly relevant. There are also associations with 'Private Enterprises, Labor, and Employment' concerning workforce definitions and AI integration, but these connections are less direct. Other sectors like Healthcare and Judiciary show little to no relevance.
Keywords (occurrence): artificial intelligence (136) machine learning (8) automated (32) large language model (1) algorithm (1) show keywords in context
Description: Establishes the New York workforce stabilization act; requires certain businesses to conduct artificial intelligence impact assessments on the application and use of such artificial intelligence and to submit such impact assessments to the department of labor prior to the implementation of the artificial intelligence; establishes a surcharge on certain corporations that use artificial intelligence or data mining or have greater than fifteen employees displaced by artificial intelligence of a ...
Summary: The New York Workforce Stabilization Act mandates businesses to conduct artificial intelligence impact assessments before implementation, focusing on worker displacement. It also imposes surcharges on corporations displacing workers through AI.
Collection: Legislation
Status date: May 15, 2024
Status: Introduced
Primary sponsor: Michelle Hinchey
(3 total sponsors)
Last action: REFERRED TO LABOR (May 15, 2024)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (14) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text mentions the requirement for businesses to conduct artificial intelligence impact assessments, which directly connects to the regulation of AI systems and their societal implications. It addresses potential job displacement due to AI use and outlines stipulations for data management related to sensitive information utilized by AI, fitting the Social Impact category. The need for companies to ensure the integrity of AI use also aligns with System Integrity, as assessments will likely cover aspects of security and oversight. Robustness appears relevant due to the mention of standardized assessments and reporting. Data Governance is also applicable as the text outlines data management and the ethical handling of employee-related data. Each reasoning reflects the multifaceted impact of AI and the legislative response to it, emphasizing clear connections to the categories defined.
Sector:
Private Enterprises, Labor, and Employment (see reasoning)
The text is primarily aimed at businesses regarding their use of artificial intelligence and its implications. The specific requirements for impact assessments indicate a strong relevance to the Private Enterprises, Labor, and Employment sector, as the legislation revolves around employment impacts and adjustments related to AI. It doesn't specifically address political campaigns or judicial regulation, making the other sectors less relevant. However, the mention of the Department of Labor indicates that there could be some administrative oversight and involvement of Government Agencies and Public Services, which is a minor connection. Overall, the primary focus on private enterprises heavily influences the sector assignment.
Keywords (occurrence): artificial intelligence (14) show keywords in context
Description: Establishes Artificial Intelligence Apprenticeship Program and artificial intelligence apprenticeship tax credit program.
Summary: The bill establishes an Artificial Intelligence Apprenticeship Program in New Jersey, promoting partnerships between employers and educational institutions, while offering tax credits to organizations hiring qualified AI apprentices.
Collection: Legislation
Status date: Nov. 18, 2024
Status: Introduced
Primary sponsor: Angela Mcknight
(2 total sponsors)
Last action: Introduced in the Senate, Referred to Senate Labor Committee (Nov. 18, 2024)
Category:
Societal Impact (see reasoning)
Sector:
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (28) show keywords in context
Societal Impact (see reasoning)
The text establishes an Artificial Intelligence Apprenticeship Program focused on training individuals for roles in the AI industry. It references the 'artificial intelligence industry' multiple times, emphasizing the development of AI technologies and applications. Therefore, this legislation is highly relevant to the Social Impact category, as it aims to equip the workforce with the skills necessary for growth within AI sectors, potentially reducing unemployment and increasing opportunities. Regarding Data Governance, while the legislation touches on training in data analytics, it does not specifically address secure data practices or oversight. For System Integrity, there is no mention of security, transparency, or control mandates relating to AI systems. The Robustness category also seems not applicable, as the focus is primarily on apprenticeships rather than benchmarks or performance standards for AI development. Thus, only Social Impact is robustly relevant.
Sector:
Private Enterprises, Labor, and Employment (see reasoning)
The text focuses on establishing an apprenticeship program within the artificial intelligence sector. It is directly relevant to Private Enterprises, Labor, and Employment by addressing workforce development in AI, creating job opportunities, and incentivizing employers to train apprentices. It does not directly touch upon Governance Agencies or the Judicial System, nor does it pertain to Healthcare, Academic Institutions, or International Cooperation explicitly in relation to AI. Therefore, its most significant relevance lies under Private Enterprises, Labor, and Employment. Other categories receive lower scores due to the lack of direct mention or implications.
Keywords (occurrence): artificial intelligence (28) show keywords in context
Description: Establishes the position of chief artificial intelligence officer and such person's functions, powers and duties; including, but not limited to, developing statewide artificial intelligence policies and governance, coordinating the activities of any and all state departments, boards, commissions, agencies and authorities performing any functions using artificial intelligence tools; makes related provisions.
Summary: This bill establishes the role of a Chief Artificial Intelligence Officer in New York, responsible for creating policies, coordinating state AI activities, and ensuring ethical use of AI across government entities.
Collection: Legislation
Status date: May 15, 2024
Status: Introduced
Primary sponsor: Michaelle Solages
(3 total sponsors)
Last action: referred to governmental operations (May 15, 2024)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services
International Cooperation and Standards (see reasoning)
Keywords (occurrence): artificial intelligence (36) machine learning (1) automated (12) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
The text outlines the establishment of a Chief Artificial Intelligence Officer position within the state of New York, with a focus on developing statewide policies and governance regarding Artificial Intelligence (AI) and Automated Decision-Making Systems. This legislation directly addresses the social impact of AI through its emphasis on protecting the rights and safety of individuals, specifically against risks associated with discrimination and misinformation. It further ensures that AI systems are governed responsibly, which touches on societal equity and accountability. Thus, the Social Impact category is very relevant. The text also emphasizes governance and operational standards for AI, which aligns well with System Integrity, particularly as it mandates risk assessments and reports on the use of AI, indicating a commitment to security and ethical standards. Data Governance is also relevant as it stipulates guidelines around the procurement and deployment of AI systems, including the protection of data privacy. Robustness is less directly addressed, as the primary focus is on the establishment of policy rather than performance benchmarks and certifications specifically. Therefore, the scores reflect these distinctions.
Sector:
Government Agencies and Public Services
International Cooperation and Standards (see reasoning)
The legislative text pertains primarily to the regulation and governance of AI within public sector contexts. The establishment of a Chief Artificial Intelligence Officer suggests a significant influence on Government Agencies and Public Services, as it is intended to coordinate the use of AI tools across various state departments and authorities. It may also touch on aspects of International Cooperation and Standards regarding how the governance of AI could involve cross-agency recommendations and strategies, but this is less emphasized. There's no substantial content related to the other sectors like Healthcare, Private Enterprises, etc., so the focus remains largely on the governmental aspect. This leads to higher scores for Government Agencies and Public Services and moderate relevance for International Cooperation and Standards.
Keywords (occurrence): artificial intelligence (36) machine learning (1) automated (12) show keywords in context
Summary: This bill amends specific chapters of Title 5, U.S. Code, to update existing laws and rectify technical errors, ensuring alignment with recent legislative changes without altering the original intent of the law.
Collection: Congressional Record
Status date: Dec. 3, 2024
Status: Issued
Source: Congress
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): artificial intelligence (1)
The text primarily discusses technical amendments to existing chapters of the United States Code, specifically chapters 4, 10, and 131. It does not reference AI-related terminology or concepts directly. Therefore, this legislation does not have a connection to AI's social implications, data governance, system integrity, or robustness. AI-specific discussions are absent, so none of the categories are relevant to this text.
Sector: None (see reasoning)
The text does not engage with any specific sector such as politics, government agencies, healthcare, or others as defined. It merely addresses legislative amendments without mentioning any applications or effects related to AI in these sectors or fields. Thus, there is no relevance to the sectors outlined.
Keywords (occurrence): artificial intelligence (1)
Description: Designating the "Transparency in Social Media Act"; requiring foreign-adversary-owned entities operating social media platforms in the state to publicly disclose specified information in a certain manner; requiring foreign-adversary-owned entities operating social media platforms to implement a user verification system for certain entities, etc.
Summary: The Transparency in Social Media Act mandates foreign-adversary-owned social media platforms in Florida to disclose algorithm details and implement user verification for political advertisements, addressing foreign influence and promoting transparency.
Collection: Legislation
Status date: Jan. 5, 2024
Status: Introduced
Primary sponsor: Joe Gruters
(sole sponsor)
Last action: Died on Calendar (March 8, 2024)
Category:
Societal Impact
Data Robustness (see reasoning)
Sector:
Politics and Elections (see reasoning)
Keywords (occurrence): algorithm (1)
Societal Impact
Data Robustness (see reasoning)
The text explicitly discusses the use of algorithms in social media platforms and their impact on content visibility and user behavior, which is pertinent to the 'Social Impact' category. The legislation addresses concerns about transparency and user privacy related to AI-driven algorithms. There is also a focus on the need for accountability for false information which intersects with the 'Robustness' category since it indirectly addresses standards for AI performance and compliance with transparency norms. The text does not primarily focus on data handling or enforcement standards related to system control, which would tie it less to 'Data Governance' and 'System Integrity'. Therefore, it has a stronger leaning toward 'Social Impact' and 'Robustness'.
Sector:
Politics and Elections (see reasoning)
The legislation mainly addresses the operation of foreign-adversary-owned entities on social media platforms, suggesting implications for elections and public discourse due to the influence of these platforms on societal opinions. This puts the text in a moderate alignment with 'Politics and Elections', as it deals with transparency in political advertising on social media. However, it does not specifically address other sectors like healthcare or the judicial system, which makes those scores low. This also applies to 'Government Agencies and Public Services' because the primary focus is on social media entities rather than the government’s use of AI. Overall, the text is most relevant to 'Politics and Elections' and has minor links to the 'Academic and Research Institutions' due to interest in transparency studies but no strong associations to the others.
Keywords (occurrence): algorithm (1)
Description: The committee of conference on the disagreeing votes of the two branches with reference to the Senate amendment of the House Bill to provide for the future information technology needs of Massachusetts (House, No. 4648), reports recommending passage of the accompanying bill (House, No. 4889).
Summary: The bill authorizes $1.256 billion for Massachusetts' IT infrastructure, enhancing cybersecurity, broadband access, and improving service delivery across state agencies through various capital investments.
Collection: Legislation
Status date: July 29, 2024
Status: Passed
Last action: Signed by the Governor, Chapter 139 of the Acts of 2024 (July 29, 2024)
Category:
Societal Impact
Data Governance (see reasoning)
Sector:
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): artificial intelligence (2) machine learning (1) automated (1) show keywords in context
Societal Impact
Data Governance (see reasoning)
The text addresses various aspects of future information technology needs in Massachusetts, particularly the investments in IT and data cybersecurity improvements for state programs and services. The references to 'artificial intelligence' and 'machine learning' systems indicate a clear focus on the application of AI technologies in government functions and public service improvement. This underlines a commitment to utilizing AI, which directly relates to societal impacts and governance in relation to technology efficiency and service delivery. However, while the text touches upon certain elements of data governance and system integrity, it primarily emphasizes social impact through technology deployment and improvements in public service. Therefore, it is most relevant to the Social Impact category with moderate relevance to Data Governance due to the implications for data security and management.
Sector:
Government Agencies and Public Services (see reasoning)
The text outlines initiatives concerning the deployment of artificial intelligence and machine learning systems as part of the future IT infrastructure for various state government agencies, enhancing interactions between residents and public services. AI integration into government services points to significant implications for both the Government Agencies and Public Services sector. The mention of supporting municipalities and tribal governments with broadband access further emphasizes government involvement in technology. Although some aspects may intersect with other sectors, the main focus remains on enhancing public services, warranting a score of 5. Other sectors such as Healthcare or Private Enterprises do not clearly apply as the text does not address these areas specifically.
Keywords (occurrence): artificial intelligence (2) machine learning (1) automated (1) show keywords in context
Summary: The bill includes various executive communications, referring regulatory rules from multiple federal agencies to their respective congressional committees for review, enhancing oversight and transparency in governance.
Collection: Congressional Record
Status date: Sept. 17, 2024
Status: Issued
Source: Congress
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (2)
The provided text contains multiple communications from various government departments regarding regulations and rules that do not specifically mention or reference AI or related technologies. The text lacks specific discussions or implications surrounding the social impact, data governance, system integrity, and robustness of AI. Most references involve traditional areas such as financial regulations, communications, and environmental rules without linking them to AI applications or implications. Overall, the text does not demonstrate any specific impact or relevance to the designated categories regarding Artificial Intelligence.
Sector: None (see reasoning)
Similarly, the content of the text does not explicitly address AI's role in any of the specified sectors including political campaigns, government agency operations, healthcare, or judicial systems. The communications primarily focus on regulatory standards in finance, fisheries, and other non-AI related fields. Therefore, they do not pertain to the application or regulation of AI technologies within the prescribed sectors.
Keywords (occurrence): automated (2)
Description: Requesting The Hawaii Professional Chapter Of The Society Of Professional Journalists To Recommend A Process That Individuals Can Utilize To Evaluate And Identify Whether Or Not News Sources Adhere To Ethical And Objective Standards.
Summary: The bill requests the Hawaii Professional Chapter of the Society of Professional Journalists to develop a process for evaluating news sources' adherence to ethical and objective standards to combat misinformation.
Collection: Legislation
Status date: April 4, 2024
Status: Engrossed
Primary sponsor: Chris Lee
(8 total sponsors)
Last action: Referred to JHA, referral sheet 27 (April 5, 2024)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): artificial intelligence (1) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
The text addresses the growing influence of artificial intelligence in the dissemination of information and misinformation. It emphasizes the need for ethical journalistic standards in the face of AI advancements that facilitate the creation and distribution of unverifiable information. This suggests a direct relevance to the societal impacts of AI, particularly regarding misinformation and the erosion of public trust, which aligns closely with the Social Impact category. While the text touches on issues that could relate to data governance (e.g., accuracy in reporting), the primary focus is on the social implications of AI misuse. The importance of ethical standards also ties into System Integrity, but primarily, the text is concerned with the societal consequences of AI's role in information dissemination and trust. Robustness is less relevant here as it deals more with performance metrics rather than the ethical or social concerns of AI usage as highlighted in this document.
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
The text primarily addresses the role of AI in journalism and misinformation, which fits closely with sectors that relate to media and information dissemination. Although the document does not directly mention politics or electoral processes, it emphasizes the handling of truthful information, which is crucial in political contexts. The application of AI in shaping public opinion and information streams connects to both Politics and Elections and Government Agencies and Public Services, particularly how these sectors might regulate or be influenced by information dissemination. However, the issue is more broadly focused on how the media and public interpret information rather than directly acting through governmental or public services, leading to moderate scores across sectors directly involved in managing information rather than those implementing it. Other sectors like Healthcare, Private Enterprises, Academic, International Cooperation, Nonprofits, and emerging areas do not have a strong relevance to this text.
Keywords (occurrence): artificial intelligence (1) show keywords in context
Description: To direct the Director of the National Institute of Standards and Technology to update the national vulnerability database to reflect vulnerabilities to artificial intelligence systems, study the need for voluntary reporting related to artificial intelligence security and safety incidents, and for other purposes.
Summary: The AI Incident Reporting and Security Enhancement Act mandates the National Institute of Standards and Technology to update the national vulnerability database for AI systems and assess voluntary reporting of AI security incidents.
Collection: Legislation
Status date: Sept. 20, 2024
Status: Introduced
Primary sponsor: Deborah Ross
(3 total sponsors)
Last action: Ordered to be Reported by Voice Vote. (Sept. 25, 2024)
Category:
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Academic and Research Institutions
International Cooperation and Standards
Nonprofits and NGOs
Hybrid, Emerging, and Unclassified (see reasoning)
Keywords (occurrence): artificial intelligence (24) automated (1) show keywords in context
Data Governance
System Integrity
Data Robustness (see reasoning)
The text explicitly discusses the reporting and management of vulnerabilities in artificial intelligence systems, which directly ties to the integrity and robustness of AI technologies. It emphasizes the need for voluntary incident reporting related to AI security and safety incidents, indicating a significant focus on ensuring secure and well-regulated AI systems. This legislation supports the development of standards and guidance, which aligns with the concept of robustness, as it aims to establish benchmarks for AI performance. Therefore, all four categories are relevant, but particularly System Integrity and Robustness are emphasized due to the focus on security and standardization.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Academic and Research Institutions
International Cooperation and Standards
Nonprofits and NGOs
Hybrid, Emerging, and Unclassified (see reasoning)
The legislation addresses the management of vulnerabilities to artificial intelligence, which can intersect with various sectors that utilize AI technologies. However, its primary concern is the technical and security aspects rather than any specific application in a standalone sector like healthcare or government services. It broadly impacts potential incidents across various sectors without focusing solely on one. Therefore, while relevant to some sectors, it does not strongly emphasize a specific sector.
Keywords (occurrence): artificial intelligence (24) automated (1) show keywords in context
Summary: The bill introduces amendments to the Defense Production Act to enhance investment transparency and national security by requiring U.S. entities to notify authorities about certain investments in foreign entities related to critical sectors, particularly in countries of concern.
Collection: Congressional Record
Status date: Sept. 17, 2024
Status: Issued
Source: Congress
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Academic and Research Institutions
International Cooperation and Standards
Hybrid, Emerging, and Unclassified (see reasoning)
Keywords (occurrence): artificial intelligence (1)
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
In evaluating the relevance of the text to the predefined categories, significant occurrences of the term 'Artificial Intelligence' were identified in relation to covered sectors discussed in the amendment. The mention of AI specifically in the definition of covered sectors suggests implications in various aspects such as social impact (considering ethical and regulatory standards), data governance (especially around standardization of data used in AI), system integrity (ensuring transparency and regulation of AI systems), and robustness (related to the establishment of performance standards for AI). Each of these categories reflects different facets of how legislation concerning AI could manifest practically and socially. Given that AI is explicitly referenced in the context of covered sectors, there is clear relevance to each of the four categories, warranting higher scores for relevance levels.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Academic and Research Institutions
International Cooperation and Standards
Hybrid, Emerging, and Unclassified (see reasoning)
The text makes specific reference to 'Artificial intelligence' as part of the covered sectors under the proposed amendment, indicating that this legislation will directly impact how AI is regulated and utilized in security contexts. While not explicitly addressing AI applications in other sectors like healthcare or politics, the classification of AI within a security-focused legislative framework suggests direct implications for governance, transparency, and potentially the methods of operation for various governmental and commercial entities interested in AI technologies. Thus, while the text does not dictate detailed practices across every sector, its implications for sectors like government agencies and public services, private enterprises, and academic institutions are relevant. Consequently, sectors such as Government Agencies and Public Services, International Cooperation and Standards, and Private Enterprises, Labor, and Employment receive moderate to high scores.
Keywords (occurrence): artificial intelligence (1)
Summary: The bill aims to update and technically amend Title 51 of the U.S. Code to ensure it remains current while improving clarity and organization without altering existing laws or their interpretations.
Collection: Congressional Record
Status date: Dec. 3, 2024
Status: Issued
Source: Congress
Category:
None
(see reasoning)
Sector: None (see reasoning)
Keywords (occurrence): automated (1) show keywords in context
The text does not contain any explicit references to AI or related technologies (e.g., Machine Learning, Neural Networks) that would warrant significant relevance to the provided categories. While it discusses technical amendments and the improvement of laws related to government functions, it lacks any direct connection to the social implications of AI, data governance, system integrity, or benchmarks for robustness. The text primarily focuses on revisions to federal law, which does not align with the core definitions and concerns of each category.
Sector: None (see reasoning)
The text does not engage in any specific sector concerning legislation about AI. It primarily addresses updates and organization within the United States Code rather than focusing on any of the nine defined sectors. There is no mention of the use of AI in political processes, government services, judicial systems, healthcare, or any enterprises. Consequently, it does not meet the criteria for relevance to any sector, leading to a low relevance score across all categories.
Keywords (occurrence): automated (1) show keywords in context