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Legislation
About these categories

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

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

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

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

About these sectors

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

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

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

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

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

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

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

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

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

Clear All

4162 results:


Pennsylvania HR170: Directing the Joint State Government Commission to establish an advisory committee to conduct a study on the field of artificial intelligence and its impact and potential future impact in Pennsylvania.

Description: A Resolution directing the Joint State Government Commission to establish an advisory committee to conduct a study on the field of artificial intelligence and its impact and potential future impact in Pennsylvania.
Collection: Legislation
Status date: July 3, 2024
Status: Passed
Primary sponsor: Robert Merski (24 total sponsors)
Last action: Adopted (125-77) (July 3, 2024)

Category:
Societal Impact
Data Governance (see reasoning)

This text explicitly discusses various aspects of artificial intelligence (AI) and its societal implications. The resolution aims to study AI's effects on industries, labor, disinformation, and academic integrity. It seeks to establish transparency in the utilization of algorithms, addresses the potential job displacement caused by automation, and emphasizes the need for responsible and ethical development of AI in Pennsylvania. Therefore, the Social Impact category is very relevant due to the focus on societal implications, while Data Governance is moderately relevant as it implies the need for secure data management in relation to AI usage. System Integrity is less relevant, focusing on security measures, and Robustness is not significantly covered as it does not discuss AI performance benchmarks or certification directly.


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

The text addresses the use of AI in various sectors including healthcare, labor and industry, and education. It discusses how AI impacts jobs, particularly in organized labor, as well as its implications for academic integrity. The resolution also signifies an exploration of AI's application within the government, although it does not delve deeply into specifics of any single sector. Therefore, its relevance is high for Government Agencies and Public Services, moderate for Healthcare and Private Enterprises, and lower for sectors like Politics and Elections, which do not feature prominently in the text's discourse.


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

Illinois HB5115: IDPH-DIAGNOSTIC ALGORITHM

Description: Amends the University of Illinois Hospital Act and the Hospital Licensing Act. Provides that before using any diagnostic algorithm to diagnose a patient, a hospital must first confirm that the diagnostic algorithm has been certified by the Department of Public Health and the Department of Innovation and Technology, has been shown to achieve as or more accurate diagnostic results than other diagnostic means, and is not the only method of diagnosis available to a patient. Sets forth provisions ...
Collection: Legislation
Status date: Feb. 8, 2024
Status: Introduced
Primary sponsor: Daniel Didech (sole sponsor)
Last action: Referred to Rules Committee (Feb. 8, 2024)

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

The text makes significant mentions of 'diagnostic algorithm' as an application of AI in healthcare, establishing a regulatory framework for its use in hospitals. It addresses issues of accuracy, transparency, and accountability in the use of these systems, which directly relate to social impacts and data governance. Since it specifies measures to ensure the biases and discrimination of AI systems are regularly evaluated and addressed, it speaks to social implications and ethical standards in AI usage. Therefore, this text is highly relevant to the Social Impact and Data Governance categories. Although the concern for system integrity is present through mentions of certification and oversight, it is not the main focus, hence the relevance is moderate. Robustness is less applicable here as the focus is not on benchmarks and performance standards, rather on ethical usage. Overall, the connection to AI is strong but with varying degrees of relevance to each category.


Sector:
Healthcare (see reasoning)

The text specifically addresses the use of AI in healthcare settings and the regulation of diagnostic algorithms utilized by hospitals. It outlines provisions that hospitals must comply with regarding the certification of such algorithms, accuracy standards, and the rights of patients regarding the use of these algorithms for diagnosis. Thus, the legislation is highly relevant to the Healthcare sector. While there are implications for other sectors (e.g., government agencies due to regulatory oversight), the primary focus remains on healthcare applications. Other sectors such as Politics and Elections, Judicial System, Private Enterprises, and Nonprofits do not fit as directly, reiterating that the strongest sector relevance is in Healthcare.


Keywords (occurrence): algorithm (31) show keywords in context

Illinois HB2620: FOIA-DEADLINES, LICENSE PLATES

Description: Amends the Freedom of Information Act. Changes the definition of "recurrent requester" to mean a person who, in the 12 months immediately preceding the request, has submitted to the same public body (i) a minimum of 40 (instead of 50) requests for records, (ii) a minimum of 10 (instead of 15) requests for records within a 30-day period, or (iii) a minimum of 5 (instead of 7) requests for records within a 7-day period. Requires a public body to either comply with or deny a request for public r...
Collection: Legislation
Status date: Feb. 15, 2023
Status: Introduced
Primary sponsor: Terra Costa Howard (3 total sponsors)
Last action: Rule 19(a) / Re-referred to Rules Committee (April 5, 2024)

Category:
Data Governance (see reasoning)

The text pertains primarily to the Freedom of Information Act (FOIA) and outlines changes in the definitions and requirements related to public requests for records. The term 'automated' is used in the context of 'automated license plate recognition systems' (ALPR), which refers to a technology that uses cameras and algorithms to identify vehicle license plates. This aspect suggests relevance to AI, particularly in issues related to data management and transparency regarding automated systems. However, no significant focus is given to the broader implications of AI on society, governance, or impact, leading to lower scores in social impact, system integrity, and robustness. Data governance principles are slightly relevant due to the structure it outlines for data and definitions but without a strong emphasis on bias or comprehensive data management practices.


Sector:
Government Agencies and Public Services (see reasoning)

The text largely focuses on the amendment of the Freedom of Information Act, which does not specifically impact any particular sector related to the predefined categories. It does have minor implications for government agencies as they are responsible for complying with information requests, thus it rates slightly higher in this domain. However, its overall relevance to sectors such as healthcare, judicial, and others listed is minimal. The mention of automated license plate recognition systems does not extend to broader governmental use of AI in public services beyond the transparency aspect.


Keywords (occurrence): automated (6) show keywords in context

United States SB1291: Protecting Kids on Social Media Act

Description: A bill to require that social media platforms verify the age of their users, prohibit the use of algorithmic recommendation systems on individuals under age 18, require parental or guardian consent for social media users under age 18, and prohibit users who are under age 13 from accessing social media platforms.
Collection: Legislation
Status date: April 26, 2023
Status: Introduced
Primary sponsor: Brian Schatz (11 total sponsors)
Last action: Read twice and referred to the Committee on Commerce, Science, and Transportation. (April 26, 2023)

Category:
Societal Impact
Data Governance (see reasoning)

This document explicitly addresses the use of 'algorithmic recommendation systems,' highlighting concerns about the impact of these systems on minors, including age verification requirements and parental consent. This speaks to the societal implications of AI, particularly in relation to the safeguarding of children and the ethical considerations of algorithmically driven content. Therefore, the Social Impact category is highly relevant. The Data Governance category receives a moderately relevant score as it touches upon personal data requirements for age verification and the management of personal data related to minors. The System Integrity category is slightly relevant due to the mention of overseeing technological aspects such as data management and security in the context of age verification, but it does not emphasize system integrity measures in a significant way. Robustness is deemed not relevant since there are no mentions of performance benchmarks or auditing for AI systems. Overall, the bill centers more on social implications and data governance rather than system integrity or robustness.


Sector: None (see reasoning)

The bill is primarily concerned with the protection of minors on social media, which relates closely to the Social Impact sector, particularly in the context of how AI-driven algorithms can influence minors. It does not directly address the role of AI in elections, judicial systems, healthcare, or other defined sectors, making the scores for Politics and Elections, Judicial System, Healthcare, Private Enterprises, Labor, and Employment, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, and Hybrid, Emerging, and Unclassified all not relevant. The Government Agencies and Public Services sector receives a slightly relevant score as it touches upon the role of governmental oversight through mandated regulations.


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

United States SB3888: TAME Extreme Weather Act Transformational Artificial intelligence to Modernize the Economy against Extreme Weather Act

Description: A bill to mandate the use of artificial intelligence by Federal agencies to adapt to extreme weather, and for other purposes.
Collection: Legislation
Status date: March 6, 2024
Status: Introduced
Primary sponsor: Brian Schatz (4 total sponsors)
Last action: Read twice and referred to the Committee on Commerce, Science, and Transportation. (March 6, 2024)

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

The text of the TAME Extreme Weather Act explicitly involves the application of artificial intelligence (AI) across various federal agencies to enhance climate adaptation efforts, particularly concerning extreme weather. The use of AI to improve forecasting, resource allocation, and resilience is clearly pertinent to 'Social Impact' as it demonstrates efforts to mitigate the adverse effects of climate change on society, which includes assessing and optimizing responses to extreme weather events. Additionally, the act includes mandates for data gathering, training datasets, and the integration of AI technologies, thus relating to 'Data Governance' through the collection and use of weather-related datasets and ensuring their quality. However, while systemic integrity and robustness may be implied through the legislative measures described, the primary focus remains squarely on the application and implications of AI technologies with respect to extreme weather. Overall, the text highlights the critical role that AI might play in the future of climate adaptation policy-making, establishing significant links to Social Impact and Data Governance categories, and to some extent, to System Integrity and Robustness, but to a lesser degree.


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

The act’s focus on employing AI for weather forecasting and emergency response has significant implications for the Government Agencies and Public Services sector. It mandates federal agencies to harness AI, reflecting the government's initiative to improve public service delivery concerning environmental crises. The focus on federal operational frameworks for extreme weather also suggests relevance to both the Healthcare sector—especially in terms of safeguarding public health during extreme weather—and to Private Enterprises, Labor, and Employment, as it might imply new practices or regulations for businesses affected by the evolving climate landscape. However, the direct implications for other sectors, like Politics and Elections, Judicial System, and NGOs, are not explicitly indicated in the text. Therefore, the clear relevance to Government Agencies and Public Services stands out strongly, with additional, though lower, relevance to Healthcare and Private Enterprises.


Keywords (occurrence): artificial intelligence (37) machine learning (2) automated (1) show keywords in context

New York S00577: Prohibits the knowing and reckless promotion of unlawful or false material; provides remedies for the violation of such prohibition.

Description: Prohibits the knowing and reckless promotion of unlawful or false material; provides remedies for the violation of such prohibition.
Collection: Legislation
Status date: Jan. 5, 2023
Status: Introduced
Primary sponsor: Brad Hoylman-Sigal (2 total sponsors)
Last action: REFERRED TO JUDICIARY (Jan. 3, 2024)

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

The text explicitly mentions the use of algorithms and automated systems in the context of promoting unlawful or false material. This directly relates to the 'Social Impact' category as it addresses the implications of AI-driven content promotion on public safety and health. The legislation is particularly concerned with the harmful promotion that could stem from AI technologies. In terms of 'Data Governance', while it doesn't focus primarily on data management and accuracy within AI systems, it implicitly raises considerations regarding the content that algorithms may promote and how data may be leveraged in these automated systems. For 'System Integrity', there's a concern regarding oversight of algorithms that can prioritize harmful content, potentially indicating a need for safeguards, while 'Robustness' does not appear to be directly relevant since the text does not discuss AI performance benchmarks or qualities. Thus, 'Social Impact' receives a high score while the other categories receive lower relevance scores.


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

The text is most relevant to 'Politics and Elections' as it inhibits the reckless promotion of harmful or false material, which could impact political campaigning and the dissemination of information in electoral processes. It also may have relevance for 'Government Agencies and Public Services' due to the implications for public safety and potential enforcement by governmental bodies. However, it is less relevant to the other sectors which do not explicitly feature AI or its application in a direct manner. Therefore, 'Politics and Elections' receives a high score, while other sectors receive lower scores reflecting their marginal relevance.


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

Kentucky HB734: AN ACT relating to the promotion of family well-being and making an appropriation therefor.

Description: Create new sections of KRS Chapter 205 to require the eligibility periods for all public assistance programs administered by the Cabinet for Health and Family Services be extended to the maximum period of eligibility permitted under federal law; prohibit the Cabinet for Health and Family Services from relying exclusively on automated, artificial-intelligence based, or algorithmic software in the identification of fraud in programs administered by the cabinet; require Cabinet for Health and Fa...
Collection: Legislation
Status date: Feb. 26, 2024
Status: Introduced
Primary sponsor: Killian Timoney (sole sponsor)
Last action: to Appropriations & Revenue (H) (March 5, 2024)

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

The text explicitly addresses the use of automated and AI-based technologies within the context of the Cabinet for Health and Family Services. The legislation prohibits reliance solely on these technologies for identifying fraud, ensuring that human oversight is mandatory. This directly relates to Social Impact, as it touches on accountability and the implications of AI on public assistance programs. The Data Governance category is relevant since it concerns how data is managed and utilized, especially in preventing fraud. System Integrity is also relevant due to the emphasis on human review and oversight, which ties into the transparency and security of AI systems used in public services. Robustness is less relevant here, as the focus isn't on benchmarks or performance evaluations of AI systems but rather their use in a specific context where human oversight is emphasized.


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

The text primarily relates to Government Agencies and Public Services as it focuses on the administration of public assistance programs by the Cabinet for Health and Family Services. The reference to AI use in tracking and managing public assistance claims directly ties this legislation to this sector. While components of Healthcare are touched upon, such as Medicaid, the primary focus remains on public services and their governance. It does not strongly address other sectors such as Politics and Elections, Judicial System, or Nonprofits, making those categories less relevant.


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

PUBLIC BILLS AND RESOLUTIONS

Collection: Congressional Record
Status date: Sept. 20, 2024
Status: Issued
Source: Congress

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

The legislation explicitly mentions 'artificial intelligence systems' and addresses the need to update a vulnerability database concerning these systems. This reflects relevance to various aspects of AI and establishes a basis for accountability and governance concerning AI systems. Such considerations are critical to understanding the societal impact, data governance, system integrity, and robustness of AI technologies.


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

The mention of 'artificial intelligence' pertains to its implications on multiple sectors. This includes the need for secure AI systems (System Integrity), better data management and mitigation of biases (Data Governance), and overall societal concerns surrounding AI technologies (Social Impact). Given these points, the legislation applies broadly to various sectors, suggestive of necessary regulations and standards for AI's use.


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

Text of Senate Amendment 3290

Collection: Congressional Record
Status date: Sept. 19, 2024
Status: Issued
Source: Congress

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

The text includes several mentions of Artificial Intelligence and its applications in defense, particularly in relation to weapon systems. This clearly aligns with the potential social impact of AI, making it relevant in assessing ethical considerations and accountability of such applications. Data governance is moderately relevant as it may involve the management of data pertaining to AI systems within military contexts. System integrity is very relevant since the bill addresses the security and operational effectiveness of AI-enabled weapon systems. Robustness is also relevant as it pertains to ensuring the effectiveness and reliability of AI systems employed in military operations.


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

The text explicitly discusses the establishment of a Center of Excellence for AI-enabled weapon systems, directly involving government agencies and the military. This makes it highly relevant to the government sector, particularly how AI is integrated within public services and defense operations. The mention of collaboration with industry and academia also indicates an intersection with private enterprises and academic institutions, but the strongest connection remains within government agencies focused on defense. Other sectors, such as healthcare, political processes, or non-profits, are less represented in this text.


Keywords (occurrence): artificial intelligence (38) automated (1) synthetic media (2) show keywords in context

PUBLIC BILLS AND RESOLUTIONS

Collection: Congressional Record
Status date: Sept. 19, 2024
Status: Issued
Source: Congress

Category:
Societal Impact (see reasoning)

The text includes bills focused on AI consumer literacy, indicating a direct relevance to the Social Impact category, as it addresses how AI affects individuals and society at large. The text does not explicitly discuss data management, system security, or performance benchmarks of AI, making the Data Governance, System Integrity, and Robustness categories less relevant. Therefore, Social Impact is marked as highly relevant while the remaining categories are not.


Sector: None (see reasoning)

The text primarily addresses legislation related to AI consumer literacy and a potential inclusion of antidiscrimination provisions which might touch lightly on judicial implications. However, these sectors do not show a strong presence concerning the application or management of AI within specific sectors. Politics and Elections, Government Agencies and Public Services sectors are also not highlighted in this text since it does not pertain to AI regulation in political campaigns, public services, or governmental oversight. Thus, while there may be minimal relevance to the Judicial System and possibly other sectors, they do not warrant higher scores.


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

GUIDING UNIFORM AND RESPONSIBLE DISCLOSURE REQUIREMENTS AND INFORMATION LIMITS ACT OF 2023

Collection: Congressional Record
Status date: Sept. 19, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

The text addresses changes to disclosure requirements and establishes a framework for evaluating the materiality of disclosures in the context of federal securities laws. However, it does not contain any explicit references or implications related to artificial intelligence or the terms associated with AI. The focus is primarily on regulatory issues around business disclosures rather than how AI might influence those processes. Thus, relevance to the categories significantly tied to AI is low.


Sector: None (see reasoning)

The legislation focuses on federal securities laws, including the establishment of a Public Company Advisory Committee and restrictions on disclosure, which may impact business operations indirectly but does not deal explicitly with the regulations surrounding AI technologies. Hence, while there may be some marginal relevance to business practices, it does not specifically target any of the sectors defined, particularly those that would require AI implications.


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

Constitutional Authority and Single Subject Statements for H.R. 9737

Collection: Congressional Record
Status date: Sept. 20, 2024
Status: Issued
Source: Congress

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

The text explicitly mentions 'artificial intelligence' in the context of improving the tracking and processing of security and safety incidents and risks associated with AI. This prompts a relevance to the categories concerning the impact and integrity of AI systems. Social Impact is relevant as it touches on the implications of AI on safety and security incidents. System Integrity is quite relevant because the focus on addressing security and safety incidents implies a need for transparent and controlled management of AI applications. Robustness is moderately relevant as it may relate to benchmarks in safety improvements of AI systems, while Data Governance is less relevant since it doesn't focus on data management practices but rather safety tracking. Therefore, the scoring should reflect high relevance for Social Impact and System Integrity, moderate relevance for Robustness, and low relevance for Data Governance.


Sector:
Government Agencies and Public Services (see reasoning)

The text does not specifically address any particular sector in detail. However, it mentions improving security and safety incidents related to AI, which can broadly be interpreted as applicable to Government Agencies and Public Services because safety and risk management are essential functions within government frameworks. The content makes no reference to specific applications in healthcare, private enterprises, education, nonprofits, or international cooperation, nor does it pertain to political campaigns. Thus, we can assign a moderate relevance score only to Government Agencies and Public Services.


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

TEXT OF AMENDMENTS

Collection: Congressional Record
Status date: Sept. 19, 2024
Status: Issued
Source: Congress

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

The text prominently features 'Artificial Intelligence' and discusses its application in military settings, specifically focusing on the establishment of centers for developing AI-enabled weapon systems. Such discussions directly relate to the ethical implications and societal impacts of relying on AI in defense contexts. Thus, the relevance to the Social Impact category is substantial, as it addresses potential societal repercussions, accountability, and implications for security. Data Governance appears relevant due to mentions of data-related responsibilities and partnerships that may include ensuring the accuracy and security of data used in AI systems. System Integrity is linked to the need for transparency and security in AI systems established by the Department of Defense, particularly those concerning weapon systems. Robustness is relevant as the legislation addresses advanced computing infrastructures that support AI capabilities, indicating a focus on developing metrics and benchmarks for AI performance in a military domain.


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

The legislation details initiatives related to the use of AI in military contexts, emphasizing the Department of Defense's roles and responsibilities in developing AI technology for military applications. Thus, it is highly relevant to the Government Agencies and Public Services sector. The emphasis on military applications and weapon systems may also imply implications for the Private Enterprises, Labor, and Employment sector, as it relates to industry partnerships and contributions to defense technology. However, its primary focus on military applications suggests that sectors like Healthcare, Academic and Research Institutions, and others are less relevant in this context. Therefore, the main relevance is firmly placed within the Government Agencies and Public Services sector.


Keywords (occurrence): artificial intelligence (38) automated (1) synthetic media (2) show keywords in context

Constitutional Authority and Single Subject Statements for H.R. 9671

Collection: Congressional Record
Status date: Sept. 18, 2024
Status: Issued
Source: Congress

Category:
Societal Impact (see reasoning)

The text contains explicit references to 'artificial intelligence' in the context of legislation regarding research and development at the Department of Energy. This indicates a focus on the advancement of AI technology, which can impact society significantly, particularly in how AI might be integrated into energy systems. However, the text does not elaborate on implications related to social impact, data governance, system integrity, or performance benchmarks, limiting its relevance to the broader aspects of these categories. Therefore, the AI-related content scores moderately relevant in some areas, but not strongly enough to warrant high scores across all categories.


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

The mention of artificial intelligence in the context of research and development at the Department of Energy suggests potential applications of AI in energy systems and governmental operations; however, the text lacks specifics on regulation or impact on formal sectors like politics, healthcare, or law. Therefore, the scoring will reflect limited relevance to most sectors, with a slight acknowledgment of government agency involvement.


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

New York A01942: Prohibits the knowing and reckless promotion of unlawful or false material; provides remedies for the violation of such prohibition.

Description: Prohibits the knowing and reckless promotion of unlawful or false material; provides remedies for the violation of such prohibition.
Collection: Legislation
Status date: Jan. 23, 2023
Status: Introduced
Primary sponsor: Deborah Glick (4 total sponsors)
Last action: referred to judiciary (Jan. 3, 2024)

Category:
Societal Impact
System Integrity (see reasoning)

The text discusses the promotion of unlawful or false material and mentions the use of algorithms and automated systems for content prioritization. This ties into the Social Impact category due to implications for misinformation and public safety. It is also relevant to System Integrity, as the act deals with regulated behavior concerning how content is prioritized and disseminated through AI systems. Data Governance is slightly relevant due to the considerations regarding the management and categorization of content, though it does not directly address secure data management practices. Robustness is not directly applicable as the focus is not on benchmarks or AI performance metrics.


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

The legislation's focus on promoting lawful content and preventing harmful misinformation has implications for various sectors, particularly Politics and Elections due to the relevance of misinformation in electoral contexts. It is also highly relevant for Government Agencies and Public Services as laws like these are instrumental in maintaining system integrity in public communication. However, it does not specifically address how AI operates within the Judicial System, Healthcare, Private Enterprises, Labor and Employment, Academic Institutions, International Cooperation, Nonprofits, or emergent sectors, hence their scores are low.


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

Kentucky SB34: AN ACT relating to the promotion of family well-being and making an appropriation therefor.

Description: Create new sections of KRS Chapter 205 to require the eligibility periods for all public assistance programs administered by the Cabinet for Health and Family Services be extended to the maximum period of eligibility permitted under federal law; prohibit the Cabinet for Health and Family Services from relying exclusively on automated, artificial-intelligence based, or algorithmic software in the identification of fraud in programs administered by the cabinet; require Cabinet for Health and Fa...
Collection: Legislation
Status date: Jan. 2, 2024
Status: Introduced
Primary sponsor: Whitney Westerfield (sole sponsor)
Last action: to Appropriations & Revenue (S) (Jan. 5, 2024)

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

The text explicitly references the use of automated, artificial intelligence-based, or algorithmic software in the context of public assistance programs. The legislation highlights the limitations imposed on the Cabinet for Health and Family Services in its reliance on AI for fraud detection and emphasizes the necessity of human oversight, thus addressing potential societal impacts related to these automated systems. Given the clear articulation of these components, the Social Impact category is very relevant. Additionally, since it discusses the secure and accurate management of data and the accountability concerning its use, it is also relevant to Data Governance. System Integrity is relevant due to the emphasis on the need for human review before actions are taken based on algorithmic recommendations, ensuring oversight in automated processes. Robustness is less relevant here as the legislation does not primarily focus on performance benchmarks or auditing compliance for AI systems, but rather on how they should be utilized responsibly in the context of public assistance.


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

The legislation primarily addresses how AI is used within public assistance programs, making it highly relevant to Government Agencies and Public Services as it outlines new guidelines and restrictions on the usage of AI in these contexts. It touches on elements that could pertain to Private Enterprises due to the implications for any vendors involved in these automated systems, but the primary focus remains on governmental responsibilities. There is no specific focus on other sectors like the Judicial System, Healthcare, or Academic Institutions as they do not come into play within this text. Therefore, the score for Government Agencies and Public Services is the highest, while other sectors receive lower relevancy scores.


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

EXECUTIVE COMMUNICATIONS, ETC.

Collection: Congressional Record
Status date: Sept. 17, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

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)

ARMS SALES NOTIFICATIONS

Collection: Congressional Record
Status date: Sept. 17, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

The text primarily addresses the notification of arms sales, focusing on technological specifications and military agreements rather than any significant discussion on AI, automated systems, or related frameworks. The mention of 'Automated Communication Engineering Software' hints at automation, but it's not comprehensive enough to have a significant impact aligned with the category definitions. Overall, the text lacks relevance regarding the social implications of AI, data governance, system integrity, or any robustness associated with AI evaluations.


Sector: None (see reasoning)

The text does not delineate any aspects of AI related to the specified sectors such as politics, government, healthcare, etc. Its focus is primarily on defense sales and technological specifications for military equipment without addressing AI regulations or implications directly impacting any of the sectors mentioned. The only relevant mention is of automated communication software, which lacks context and significance to be categorized within any specific sector.


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

TEXT OF AMENDMENTS

Collection: Congressional Record
Status date: Sept. 17, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

The text does not contain any explicit references to AI, its applications, or its ethical impacts on society. It focuses on issues related to military personnel records and the processes to ensure their declassification and public access. The legislation discusses oversight and transparency mechanisms but does not pertain to AI technologies, thus making it irrelevant for all categories related to AI.


Sector: None (see reasoning)

The text primarily concerns military records and their management, with no mention of AI-related sectors or technologies. Therefore, it holds no relevance to any of the nine sectors such as Politics and Elections or Government Agencies and Public Services, as it focuses instead on archival practices and legislative oversight.


Keywords (occurrence): artificial intelligence (1)

United States SB5152: Artificial Intelligence Civil Rights Act of 2024

Description: A bill to establish protections for individual rights with respect to computational algorithms, and for other purposes.
Collection: Legislation
Status date: Sept. 24, 2024
Status: Introduced
Primary sponsor: Edward Markey (2 total sponsors)
Last action: Read twice and referred to the Committee on Commerce, Science, and Transportation. (Sept. 24, 2024)

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

This legislation explicitly addresses the impact of computational algorithms, especially in relation to civil rights and discrimination. AI, being heavily involved in algorithmic decision-making, is directly pertinent to concerns about fairness and bias. It helps protect individuals from algorithmic discrimination, thus making it highly relevant to the Social Impact category. In addition, it discusses pre-deployment evaluations of algorithms, which relates to System Integrity via the provisions ensuring oversight and control over the algorithms deployed. The mention of standards for algorithms and evaluations directly links to Robustness concerning performance and accountability of AI systems. Data Governance is also relevant as it encompasses the management of data used by algorithms with provisions for user rights and protections. Therefore, overall relevance is high across all categories, with explicit references to AI and algorithms necessitating further scrutiny and legislation.


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

The text is not limited to one sector but spans multiple contexts where AI and algorithms have significant influence. For Politics and Elections, it features provisions that directly relate to electoral processes, such as voting and voter registration, in connection with discriminatory practices. Similarly, the Healthcare section is relevant due to mentions of healthcare-related decisions influenced by algorithms. Regarding Government Agencies and Public Services, the bill discusses how algorithms affect access to government benefits and legal services. The impacts on Private Enterprises, Labor, and Employment are also clear with respect to algorithms' roles in hiring and employee management. Also touching on Judicial Systems, it considers the justice implications of algorithmic discrimination. Academic and Research Institutions may engage with this through algorithmic fairness studies and impact evaluations. Therefore, the text is broadly relevant across many sectors with significant implications for how AI is applied in various domains.


Keywords (occurrence): artificial intelligence (5) machine learning (1) algorithm (128) show keywords in context
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