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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:


Wisconsin AB664: Disclosures regarding content generated by artificial intelligence in political advertisements, granting rule-making authority, and providing a penalty. (FE)

Description: An Act to amend 11.1303 (title); and to create 11.1303 (2m) of the statutes; Relating to: disclosures regarding content generated by artificial intelligence in political advertisements, granting rule-making authority, and providing a penalty. (FE)
Collection: Legislation
Status date: March 21, 2024
Status: Passed
Primary sponsor: Adam Neylon (29 total sponsors)
Last action: Published 3-22-2024 (March 21, 2024)

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

The text explicitly discusses the regulation of AI-generated content, specifically synthetic media, in political advertisements. This addresses the social impact of AI on public discourse, transparency in political communications, and the potential for misinformation through unmarked AI-generated content, which is highly relevant to social impact. Additionally, there is an implication of data governance concerning the clarity and accuracy of disclosures about the nature of the media presented. The focus on compliance and the penalties for failure to disclose AI-generated content indicates relevance to system integrity. However, there are no direct mentions of performance benchmarks or robust standards, which limits the relevance to robustness.


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

The legislation is primarily focused on the impact of AI in the context of politics and elections, promoting transparency and accountability in political advertising, which directly aligns with the Politics and Elections sector. There are indirect implications for Government Agencies and Public Services as the enforcement and rule-making aspects may involve state or federal agency oversight, but the core focus remains on political communications. The other sectors do not see relevance as they are not addressed directly in this legislation; it remains firmly rooted in the context of political advertisements and their implications.


Keywords (occurrence): artificial intelligence (2) synthetic media (6) show keywords in context

Illinois SB2314: SAFE PATIENT LIMITS ACT

Description: Creates the Safe Patient Limits Act. Provides the maximum number of patients that may be assigned to a registered nurse in specified situations. Provides that nothing shall preclude a facility from assigning fewer patients to a registered nurse than the limits provided in the Act. Provides that the maximum patient assignments may not be exceeded, regardless of the use and application of any patient acuity system. Requires the Department of Public Health to adopt rules governing the implementa...
Collection: Legislation
Status date: Feb. 10, 2023
Status: Introduced
Primary sponsor: Celina Villanueva (8 total sponsors)
Last action: Added as Co-Sponsor Sen. Mattie Hunter (March 7, 2024)

Category: None (see reasoning)

The Safe Patient Limits Act primarily focuses on establishing maximum patient loads for registered nurses within healthcare facilities, which directly affects how patient care is administered and the overall healthcare workforce. However, it does not make significant reference to AI-related technology, such as automated decision-making processes or algorithmic assessments in patient care. As such, while the act is relevant to healthcare and the implications it carries for staff and patients, it does not engage deeply with the implications of AI in any capacity. Therefore, the scores reflect a recognition of healthcare impacts but a lack of specific AI relevance within the provided text.


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

The legislation is explicitly centered on healthcare and nursing practices, setting patient limits for registered nurses. Thus, while it does not address AI directly, it profoundly impacts the healthcare sector by outlining staffing requirements and responsibilities of healthcare professionals. Conversely, the legislation does not target other sectors such as public service functionalities, legal systems, or government functions. The scoring reflects a strong relevance to healthcare without extending to significant overlap with other sectors.


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

Illinois SB3613: FOIA-JUDICIAL BRANCH

Description: Amends the Freedom of Information Act. Provides that, for purposes of the Act, "public body" includes the judicial branch and components of the judicial branch of the State. Exempts records that pertain to the preparation of judicial opinions and orders. Excludes denials of requests of records from the judicial branch or components of the judicial branch from the jurisdiction of the Public Access Counselor.
Collection: Legislation
Status date: Feb. 9, 2024
Status: Introduced
Primary sponsor: Robert Martwick (sole sponsor)
Last action: Referred to Assignments (Feb. 9, 2024)

Category: None (see reasoning)

The text primarily amends the Freedom of Information Act and does not specifically address or incorporate any language directly related to Artificial Intelligence (AI), algorithms, or other related technologies. The focus on public access to judicial records does not discuss the societal implications, data governance, system integrity, or robustness of AI systems. Thus, all categories are assigned a score of 1, indicating they are not relevant to the content of the text.


Sector: None (see reasoning)

The text deals with amending provisions regarding the Freedom of Information Act as it pertains to the judicial branch. There is no mention of AI usage, regulation, or impact within the political, governmental, judicial, healthcare, employment, academic, or other sectors described. For these reasons, all sectors receive a score of 1, indicating no relevance to the text.


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

New York A00539: Provides that a person may operate a fully autonomous vehicle on the public roads of this state without a human driver provided that the automated driving system is engaged and the vehicle meets certain conditions; defines terms; requires insurance and that such vehicle is registered as a fully a...

Description: Provides that a person may operate a fully autonomous vehicle on the public roads of this state without a human driver provided that the automated driving system is engaged and the vehicle meets certain conditions; defines terms; requires insurance and that such vehicle is registered as a fully autonomous vehicle; makes related provisions.
Collection: Legislation
Status date: Jan. 9, 2023
Status: Introduced
Primary sponsor: Kenneth Burgos (5 total sponsors)
Last action: enacting clause stricken (July 22, 2024)

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

The text is primarily focused on the regulation and operation of autonomous vehicles, which directly pertains to AI through the mention of automated driving systems. The relevance to the categories is assessed as follows: For Social Impact, the legislation addresses the implications of autonomous vehicles on safety, public use, and potential societal changes related to transport, thus scoring a 4 (Very relevant). In terms of Data Governance, while there are mentions of conditions and requirements, the emphasis lies more on operation than data management, placing it at a 2 (Slightly relevant). System Integrity is significant since the text establishes regulations around the operation of these systems, including safety and response procedures, earning a score of 4 (Very relevant). Similarly, robustness is implicated through the demand for performance standards and safety checks for autonomous systems, leading to a score of 4 (Very relevant). Overall, the key focus areas of the text indicate it concerns itself with how AI in vehicles impacts society, system safety, and operational performance.


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

The legislation strongly addresses how AI operates within the transportation sector, particularly focusing on autonomous vehicles. In the context of Politics and Elections, there's no direct applicability, which earns a 1 (Not relevant). Government Agencies and Public Services receive a score of 5 (Extremely relevant) as the legislation will directly affect how local and state agencies manage and regulate public road usage. For the Judicial System, while there may be indirect implications regarding liability and accountability, the text does not focus on judicial applications, leading to a score of 2 (Slightly relevant). In Healthcare, there are no connections, scoring a 1 (Not relevant). Private Enterprises, Labor, and Employment scores a 3 (Moderately relevant) since the operations could affect businesses offering transportation services. Academic and Research Institutions receive a score of 2 (Slightly relevant) at best, given implications for research into autonomous vehicle systems. International Cooperation and Standards is not addressed which results in a score of 1 (Not relevant). Nonprofits and NGOs have no mention in this context earning a score of 1 (Not relevant), while Hybrid, Emerging, and Unclassified sectors might consider autonomous driving technology as emerging, so it scores a 3 (Moderately relevant).


Keywords (occurrence): automated (24) autonomous vehicle (23) show keywords in context

New York A03308: Enacts the "digital fairness act"; requires any entity that conducts business in New York and maintains the personal information of 500 or more individuals to provide meaningful notice about their use of personal information; establishes unlawful discriminatory practices relating to targeted adve...

Description: Enacts the "digital fairness act"; requires any entity that conducts business in New York and maintains the personal information of 500 or more individuals to provide meaningful notice about their use of personal information; establishes unlawful discriminatory practices relating to targeted advertising.
Collection: Legislation
Status date: Feb. 2, 2023
Status: Introduced
Primary sponsor: Catalina Cruz (2 total sponsors)
Last action: referred to consumer affairs and protection (Jan. 3, 2024)

Category:
Societal Impact
Data Governance (see reasoning)

The text of the Digital Fairness Act addresses several aspects related to social impact, particularly concerning the misuse of personal information and the potential harms such as discrimination and erosion of trust in digital interactions. It highlights the need for transparency, accountability, and fairness in how personal information is processed. This suggests a focus on the societal implications of AI systems, especially how algorithms can disproportionately affect historically disadvantaged groups. Therefore, social impact is rated highly. For data governance, the text explicitly discusses the management of personal information, consent requirements, and the need for accurate data practices, which aligns strongly with governance concerns in AI. System integrity is tangentially relevant since it deals with the manipulation and security of personal data through algorithms but is not the primary focus of the text. Robustness, on the other hand, is less applicable as the text does not primarily focus on performance benchmarks or auditing, which are core to this category. Therefore, it scores low. Overall, social impact and data governance emerge as the most relevant categories.


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

The text relates closely to multiple sectors. The Government Agencies and Public Services sector is relevant since the act discusses the use of automated decision systems by governmental entities, focusing on ensuring they operate fairly and transparently. The Private Enterprises, Labor, and Employment sector is also significantly applicable as it addresses businesses' responsibilities in using personal data ethically, especially in the digital advertising sphere. The lack of explicit references to AI applications in the Judicial System, Healthcare, or the remaining sectors leads to lower relevance for them. Academic and Research Institutions and Nonprofits and NGOs are also less relevant as the legislation primarily targets businesses doing commerce in New York. Therefore, Government Agencies and Public Services and Private Enterprises, Labor, and Employment are the most fitting sectors.


Keywords (occurrence): automated (97) algorithm (1) show keywords in context

Text of Senate Amendment 3282

Collection: Congressional Record
Status date: Sept. 16, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

The text primarily focuses on various administrative and operational aspects related to the Department of State and its workforce. There is no explicit mention of artificial intelligence, algorithms, or any AI-related technologies within the key sections extracted from the text. Hence, legislative aspects concerning social impact, data governance, system integrity, and robustness of AI systems are not present. The mention of aspects like electronic medical records and performance evaluations may parallel AI functionalities involving data and decision-making, but these references do not inherently connect to the broader implications and challenges associated with AI. Therefore, this text is not relevant to any of the categories defined.


Sector: None (see reasoning)

The text discusses administration matters concerning the Department of State and workforce matters while also mentioning electronic medical records without explicit connection to any specific sector related to AI. There's no discussion present that directly addresses the use of AI in politics, government services, healthcare, or employment. Therefore, there is insufficient content to categorize this amendment under any of the sectors defined. The absence of AI-related terminology or significant context around these sectors means that it has no relevance to them.


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

EXECUTIVE AND OTHER COMMUNICATIONS

Collection: Congressional Record
Status date: Sept. 16, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

The text primarily consists of communications laid before the Senate related to various regulatory actions and reports from different government departments. There are mentions of terms such as 'Automated Valuation Models' related to financial systems, but there are no direct references to AI technologies or their societal impact, data governance, system integrity, or robustness. Hence, the relevance of the categories to the content of the text is very low.


Sector: None (see reasoning)

The content does not specifically address AI applications in any sector listed. While there are rules mentioned that relate to government organizations and financial institutions, none of these directly pertain to the use or regulation of AI within the sectors. Therefore, the relevance of all sectors is minimal.


Keywords (occurrence): automated (2)

Daily Digest/CONGRESSIONAL PROGRAM AHEAD

Collection: Congressional Record
Status date: Sept. 16, 2024
Status: Issued
Source: Congress

Category:
Societal Impact
System Integrity (see reasoning)

The text does not prominently focus on specific AI-related issues as it mainly outlines congressional activities, upcoming meetings, and agenda items without detailed legislation referencing AI. However, there are mentions indicating that aspects of AI are being examined, particularly through hearings related to AI and the technology's impact. The relevance of AI to the categories can only be inferred rather than drawn directly from clear discussion points in the text.


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

The text outlines congressional actions where AI is mentioned but does not delve deeply into any specific sectoral issues related to AI. However, it hints at potential implications for various sectors, such as hearings by the Judiciary Committee that focus on AI insights, which could relate to broader political and legal discussions. Furthermore, certain bills seem to touch upon government and public service applications of AI, suggesting a minimal but notable engagement with these sectors.


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

California SB1223: Consumer privacy: sensitive personal information: neural data.

Description: An act to amend Section 1798.140 of the Civil Code, relating to privacy.
Collection: Legislation
Status date: Sept. 28, 2024
Status: Passed
Primary sponsor: Josh Becker (sole sponsor)
Last action: Chaptered by Secretary of State. Chapter 887, Statutes of 2024. (Sept. 28, 2024)

Category:
Societal Impact
Data Governance (see reasoning)

The text explicitly addresses the collection and management of sensitive personal information, specifically neural data, which is directly related to data governance. This bill aims to include neural data under the umbrella of sensitive personal information governed by the California Consumer Privacy Act. This involves the secure and accurate collection and management of biometric information, fitting well within the Data Governance category. It does not extensively speak to social impacts or system integrity, and robustness does not apply since there are no new benchmarks or performance evaluations discussed. However, there is a clear connection to managing data appropriately to protect individual rights and privacy in AI systems, leading to a high relevance to Data Governance. Thus, the final reasoning here aligns the text significantly with data governance due to the strong emphasis on privacy, control, ethical handling, and oversight related to neural data and consumer protection.


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

This bill primarily focuses on consumer privacy in relation to neural data, which does not directly address specific sectors like Politics and Elections, Government Agencies and Public Services, Judicial System, Healthcare, Private Enterprises, Labor, and Employment, or Academic and Research Institutions. However, because it deals with sensitive personal information that can affect a wide range of stakeholders and contexts, there remains a moderate relevance due to its potential implications in various sectors dealing with consumer data. Still, the sector discussions are not a primary focus of this text, justifying a modest relevance score for academic, private, and public sector interactions with AI data. Therefore, scores reflect this understanding with an emphasis on all sectors being slightly relevant but not directly addressed.


Keywords (occurrence): artificial intelligence (1) automated (8) show keywords in context

TEXT OF AMENDMENTS

Collection: Congressional Record
Status date: Sept. 16, 2024
Status: Issued
Source: Congress

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

This text explicitly mentions Artificial Intelligence in the context of cybersecurity and procurement for the Department of Defense, focusing on the development, deployment, and security of AI technologies. Therefore, it has significant implications for concerns surrounding Social Impact, particularly regarding accountability and security in AI systems as they relate to military applications. The section on physical and cybersecurity procurement requirements for artificial intelligence systems shows a direct correlation between cybersecurity protocols and the integrity of AI technologies, which aligns well with System Integrity. There is also an emphasis on risk management and best practices, which reflects aspects relevant to Robustness. Data Governance is also pertinent due to the mention of data used in the development of AI systems and management protocols designed to ensure integrity, although it’s not as prominent as the system integrity aspects. Thus, all categories have relevance to varying degrees, but Social Impact, Data Governance, and System Integrity are particularly notable due to their focus on the implications of AI in a defense context.


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

The text is highly relevant to the Government Agencies and Public Services sector as it outlines the Department of Defense's specific requirements for the procurement and security of AI technologies. It addresses the frameworks and partnerships necessary for robust cybersecurity measures for AI systems affecting national security, directly relating to governmental functionality and public safety. There are also implications for the Private Enterprises and labor sector due to the mention of commercial partnerships in developing AI systems and cybersecurity measures. Though it mentions interactions with various stakeholders in the private sector, the main focus remains on defense applications, making the Government Agencies and Public Services sector the most relevant, while the Private Enterprises may receive moderate relevance due to its indirect effects on industry practices. Other sectors such as Judicial System, Healthcare, and Nonprofits have little to no relevance based on the content provided.


Keywords (occurrence): artificial intelligence (33) automated (1) show keywords in context

SENATE COMMITTEE MEETINGS

Collection: Congressional Record
Status date: Sept. 16, 2024
Status: Issued
Source: Congress

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

The text primarily involves the scheduling of Senate committee meetings, with a notable mention of artificial intelligence in the context of federal procurement, development, and use. This specific mention indicates a legislative focus on integrating AI into government practices, which has broader implications for social impact, data governance, system integrity, and robustness. However, the overall text is procedural and does not deeply explore any of these areas in detail, making the connections slightly tenuous yet relevant to future implications and oversight of AI.


Sector:
Government Agencies and Public Services (see reasoning)

The document contains mentions of AI in the context of congressional and federal activities, hinting at regulation concerning government use of AI technologies. This aligns it moderately with the Government Agencies and Public Services sector since the legislation concerns federal operations. Other sectors such as Politics and Elections may also be lightly relevant given the mention of tech providers in relation to election threats, but the text does not extensively delve into campaign regulations or AI impacts on electoral processes.


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

Text of Senate Amendment 3277

Collection: Congressional Record
Status date: Sept. 16, 2024
Status: Issued
Source: Congress

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

The text of Senate Amendment 3277 revolves primarily around the procurement and cybersecurity of artificial intelligence systems within the Department of Defense. It discusses the need for a defined security framework specifically for AI systems, highlighting various cybersecurity risks, such as insider threats and supply chain vulnerabilities. It emphasizes the importance of establishing best practices for securing AI technologies, which directly aligns with the concepts of System Integrity and Robustness. Furthermore, the amendment addresses potential impacts on national security, thus also relating to the Social Impact of AI systems. Data Governance is implicitly relevant due to the emphasis on managing data and algorithms used in these AI systems, although it is not the main focus. Overall, this legislation is heavily oriented towards safety, integrity, and societal implications of AI technology, making it particularly relevant for the categories defined.


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

Given that this amendment focuses on the use of artificial intelligence systems within the Department of Defense, it has a strong relevance to the Government Agencies and Public Services sector. The discussions of cybersecurity partnerships and frameworks for securing AI technologies apply to military and defense contexts, indicating significant implications in national security. There is no specific mention of AI's role in areas like politics, health, or judiciary, which makes other sectors less relevant. While there are aspects of private enterprise engagement, the emphasis remains firmly on governmental applications of AI technologies. Therefore, it is justifiable to rate the Government Agencies and Public Services sector highly while giving lower scores to others.


Keywords (occurrence): artificial intelligence (33) show keywords in context

STATEMENTS ON INTRODUCED BILLS AND JOINT RESOLUTIONS

Collection: Congressional Record
Status date: Sept. 12, 2024
Status: Issued
Source: Congress

Category:
Societal Impact
Data Governance (see reasoning)

The text primarily focuses on regulating communications regarding prescription drugs, particularly in the context of social media, but it does mention the use of artificial intelligence (AI) applications specifically for market surveillance activities. This indicates a degree of relevance to AI, particularly in how AI may be utilized to aggregate public communications and analyze promotional communications. However, the focus is largely on addressing misleading communications rather than the broader social implications of AI. Therefore, the relevance of each category should be assessed carefully. Social Impact is moderately relevant due to implications concerning misleading communications that could affect consumers' perceptions and decisions regarding health. Data Governance is relevant as the proposed regulations touch on compliance and monitoring of communications around drugs, possibly involving data use. System Integrity could be considered slight due to the mention of AI in the context of enhancing regulations but lacks explicit security or oversight mandates. Robustness could be deemed slightly relevant as well given the mention of methodologies and analytical tools, yet it does not specifically mention benchmarks or certifications for AI applications.


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

In terms of sectors, the text is highly relevant to Healthcare due to its direct focus on regulations and the impact on prescription drugs and healthcare communications. Private Enterprises, Labor, and Employment also have relevance as it addresses the role of social media influencers who may be involved in marketing drugs, potentially affecting employment and business practices in the health sector. Government Agencies and Public Services is pertinent as the legislation deals with health communication regulations and involves government oversight through the FDA. No other sectors apply strongly, as the text does not address political campaigns, judicial processes, academic regulations, international cooperation, or nonprofit contexts significantly.


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

Illinois HB4292: FOIA-JUDICIAL BRANCH

Description: Amends the Freedom of Information Act. Provides that, for purposes of the Act, "public body" includes the judicial branch and components of the judicial branch of the State. Exempts records that pertain to the preparation of judicial opinions and orders. Excludes denials of requests of records from the judicial branch or components of the judicial branch from the jurisdiction of the Public Access Counselor.
Collection: Legislation
Status date: Dec. 20, 2023
Status: Introduced
Primary sponsor: Curtis Tarver (sole sponsor)
Last action: Rule 19(a) / Re-referred to Rules Committee (April 5, 2024)

Category: None (see reasoning)

This text primarily amends existing legislation, the Freedom of Information Act, with a focus on the inclusion of the judicial branch and its components as 'public bodies.' It does not contain specific references to AI or its applications. Although the legislation affects the transparency and access to information in government processes, it does not address AI's social impact, data governance, system integrity, or robustness specifically, as there are no mentions of these topics or relevant AI terms. Thus, the relevance of each category is determined to be low.


Sector: None (see reasoning)

The legislation does not directly address the use or regulation of AI across any sectors mentioned. It focuses solely on amendments related to transparency and records within the judicial branch and does not touch on sectors such as healthcare, politics, or business, where AI applications might be relevant. There are no explicit mentions of AI technologies or their implications in the listed sectors.


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

New York S02277: Enacts the "digital fairness act"; requires any entity that conducts business in New York and maintains the personal information of 500 or more individuals to provide meaningful notice about their use of personal information; establishes unlawful discriminatory practices relating to targeted adve...

Description: Enacts the "digital fairness act"; requires any entity that conducts business in New York and maintains the personal information of 500 or more individuals to provide meaningful notice about their use of personal information; establishes unlawful discriminatory practices relating to targeted advertising.
Collection: Legislation
Status date: Jan. 19, 2023
Status: Introduced
Primary sponsor: Brian Kavanagh (sole sponsor)
Last action: REFERRED TO INTERNET AND TECHNOLOGY (Jan. 3, 2024)

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

The text of the Digital Fairness Act addresses various issues related to the impact of AI and data algorithms on society, such as discrimination resultant from targeted advertising and automated decision systems. It acknowledges the potential harms caused by the misuse of personal information—issues that directly correlate with societal concerns about AI's influence, discrimination, and privacy. Additionally, the text mentions the need for oversight and transparency in automated decision-making, indicating the role AI plays in potential civil rights infringements, further intensifying its relevance in the social impact framework. Given this pointed focus on discrimination and fairness in technology use, the category of Social Impact is scored very high. Regarding Data Governance, the legislation explicitly targets the management of personal data and the algorithms affecting that data, such as obtaining informed consent for processing personal information, suggesting robust oversight on data practices. Hence, this category is rated very relevant. System Integrity discusses regulations ensuring security and accountability in AI deployment; since the text's purpose is partly to ensure transparency and fair use of algorithms, it aligns well here but is somewhat less central than the previous categories, resulting in a moderate score. Robustness, concerning AI performance benchmarks, is less applicable as the document emphasizes data privacy and protection rather than benchmarks for AI systems, thus earning it a low relevance score.


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

The Digital Fairness Act focuses primarily on protection for individuals in digital contexts by regulating how their personal information is handled, particularly concerning targeted advertising and potential biases that could affect individuals unfairly in a number of ways including employment and financial services. It relates to Government Agencies and Public Services, as it pertains to how public entities might utilize personal information and automated decision systems that could impact civil rights, earning a moderate score. The legislative intent does not directly address the Judicial System, Healthcare, or Academic and Research Institutions, thus those sectors receive low scores. The implications for Private Enterprises, Labor, and Employment are significant given the focus on accountability of businesses regarding consumer data practices, earning this sector a moderate score as well. International Cooperation and Standards receive a slight score considering the broad implications of data regulation but are not a central theme in this text. Nonprofits and NGOs are similarly affected as organizations that might collect personal data, hence a slightly relevant score, while the hybrid category could apply but is also low due to lack of specificity. Overall, the primary relevance centers around individual data protection in business practices with tolerable ties to government regulations.


Keywords (occurrence): automated (97) algorithm (1) show keywords in context

New Jersey A1760: Requires BPU to provide funding for purchase and installation of photovoltaic technologies for age-restricted community clubhouse facilities from societal benefits charge.

Description: Requires BPU to provide funding for purchase and installation of photovoltaic technologies for age-restricted community clubhouse facilities from societal benefits charge.
Collection: Legislation
Status date: Jan. 9, 2024
Status: Introduced
Primary sponsor: Brian Rumpf (sole sponsor)
Last action: Introduced, Referred to Assembly Telecommunications and Utilities Committee (Jan. 9, 2024)

Category: None (see reasoning)

The text primarily discusses provisions related to funding for photovoltaic technologies, with no direct mention of AI or its associated concepts. There may be some associations with social impacts concerning energy sustainability, but they are not substantiated with AI references, impairing relevance to the defined categories. Therefore, each category receives a low score since the text is mainly focused on energy policy rather than AI implications.


Sector: None (see reasoning)

The text is entirely focused on energy policy, specifically addressing photovoltaic technology and its implications for age-restricted communities. There are no references or discussions related to the sectors outlined, as AI does not appear within the context of this legislative bill. Each sector neither intersects with the content of the bill nor engages with AI frameworks or systems, leading to low scores across the board.


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

Wisconsin SB644: Disclosures regarding content generated by artificial intelligence in political advertisements, granting rule-making authority, and providing a penalty. (FE)

Description: An Act to amend 11.1303 (title); and to create 11.1303 (2m) of the statutes; Relating to: disclosures regarding content generated by artificial intelligence in political advertisements, granting rule-making authority, and providing a penalty. (FE)
Collection: Legislation
Status date: April 15, 2024
Status: Other
Primary sponsor: Romaine Quinn (31 total sponsors)
Last action: Failed to pass pursuant to Senate Joint Resolution 1 (April 15, 2024)

Category:
Societal Impact (see reasoning)

The text focuses primarily on the requirement for disclosures regarding content generated by artificial intelligence in political advertisements. This highlights the legislation's direct implications on society, especially with respect to informing the public about the authenticity of information they encounter, which ties directly into the social impact of AI. The legislation addresses the risk of misinformation and manipulation that can arise from synthetic media in political discourse. The bill also involves the imposition of penalties for non-compliance, further emphasizing accountability. Therefore, I rate Social Impact as very relevant. Data Governance is slightly relevant as it pertains to the use of data in AI, but is not the central focus of the text. System Integrity is not relevant because the text does not address security or transparency of AI systems. Robustness is not relevant since there are no discussions about benchmarks or performance measures of AI systems mentioned in the text.


Sector:
Politics and Elections (see reasoning)

The legislation specifically addresses the use of AI in political advertisements, indicating a clear focus on the political and electoral processes. It sets out requirements for disclosure of AI-generated content in political communications, directly linking the regulation of AI to political integrity and voter awareness. Thus, I assess Politics and Elections as extremely relevant. The Government Agencies and Public Services sector is slightly relevant because government bodies will likely be involved in the enforcement of this legislation but is not the main focus of the bill. Other sectors such as Judicial System, Healthcare, Private Enterprises, Academic Institutions, International Cooperation, Nonprofits, and Hybrid sectors do not see relevance in this bill as it is narrowly focused on political advertising.


Keywords (occurrence): artificial intelligence (2) synthetic media (10) show keywords in context

Illinois HB5228: AI USE IN GOVT CONTRACTS

Description: Amends the Illinois Procurement Code. Requires a vendor who contracts for government services, grants, or leases or purchases of software or hardware to disclose if artificial intelligence technology is, has been, or will be used in the course of fulfilling the contract or in the goods, technology, or services being purchased. Provides that the disclosure must be provided to the chief procurement officer, the Department of Innovation and Technology, and the General Assembly. Provides that, if...
Collection: Legislation
Status date: Feb. 8, 2024
Status: Introduced
Primary sponsor: Abdelnasser Rashid (sole sponsor)
Last action: Rule 19(a) / Re-referred to Rules Committee (April 5, 2024)

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

The text is very relevant to the Social Impact category as it discusses transparency and accountability concerning the use of AI technology in government contracts, which directly relates to the societal effects of AI practices. It also indicates the need for disclosure regarding how these technologies may affect the delivery of public services and the implications for accountability, potentially addressing biases, fairness, and trust in the governance process. For Data Governance, the text is extremely relevant as it mandates specific disclosures and details regarding the use of AI, which relates to secure and accurate management of data within these systems. The System Integrity category is relevant because the law ensures oversight and accuracy in disclosing AI use, promoting transparency in government dealings. There is some relevance to the Robustness category, but it is not as strong as the others, as the focus is more about transparency and disclosure rather than performance benchmarks or compliance auditing.


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

In terms of sectors, this text has strong relevance to Government Agencies and Public Services, as it deals with contracting for government services and thus directly involves government operations and their relationship with AI. It has relevance to Private Enterprises, Labor, and Employment as well, since it discusses vendors and their obligations in contracts, but this relevancy is secondary to government processes. The text does not specifically touch on other sectors like Politics and Elections, Judicial System, Healthcare, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, or Hybrid, Emerging, and Unclassified, as it does not relate to these areas.


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

New York S01759: Relates to how online dating services handle fraudulent members; requires certain disclosures.

Description: Relates to how online dating services handle fraudulent members; requires certain disclosures.
Collection: Legislation
Status date: Jan. 13, 2023
Status: Introduced
Primary sponsor: James Skoufis (2 total sponsors)
Last action: SUBSTITUTED BY A1057C (May 29, 2024)

Category: None (see reasoning)

The legislation primarily focuses on online dating services and their handling of fraudulent member activities, which does not directly address the broader social implications of AI technology. While algorithmic matching is mentioned, it is limited and specific to the functioning of these services rather than a comprehensive assessment of AI's societal impact or ethical considerations. However, it does touch upon issues of consumer protection and accountability, which may slightly align with social impact concerns. The data governance implications are minimal, as the text does not deal extensively with data integrity or privacy management in relation to AI systems. System integrity is similarly lightly touched upon concerning the operational aspects of these services but lacks significant AI-driven controls or oversight. As there are no substantial references to new benchmarks or standards in AI performance or robustness of AI systems, the robustness category is also deemed irrelevant.


Sector: None (see reasoning)

The text discusses aspects related to online dating services without delving into broader applications of AI in various sectors. There are minimal references to governmental roles, and while there is a consumer protection aspect, it does not cover how AI is employed within the online dating framework substantially. The legislative aspects touch on possible fraudulent practices but do not elaborate on how AI systems may specifically influence or contribute in the provided context. Thus, it does not fit neatly into any established sector but could land under Consumer Protection. Overall, it does not strongly align with any specific sector related to AI. The scoring reflects that while AI is tangentially mentioned, its role and implications are not substantial enough across sectors to warrant a higher score.


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

Illinois SB2795: SAFE PATIENT LIMITS ACT

Description: Creates the Safe Patient Limits Act. Provides the maximum number of patients that may be assigned to a registered nurse in specified situations. Provides that nothing shall preclude a facility from assigning fewer patients to a registered nurse than the limits provided in the Act. Provides that the maximum patient assignments may not be exceeded, regardless of the use and application of any patient acuity system. Requires the Department of Public Health to adopt rules governing the implementa...
Collection: Legislation
Status date: Jan. 17, 2024
Status: Introduced
Primary sponsor: Michael Halpin (sole sponsor)
Last action: Rule 3-9(a) / Re-referred to Assignments (March 15, 2024)

Category: None (see reasoning)

The text of the Safe Patient Limits Act focuses primarily on nursing regulations, staffing requirements, and patient care standards within healthcare facilities. While it addresses crucial areas such as patient assignments and staffing ratios, it lacks direct references to AI-related aspects such as automated decision-making or algorithms. Therefore, any connection to AI is indirect, mainly regarding how it could influence staffing procedures or patient monitoring if integrated; hence, the relevance scores are low for all categories.


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

This text significantly pertains to healthcare, focusing on patient care, nurse assignments and competencies, and the administration of health services. There's a straightforward and strong connection since the legislation aims to improve healthcare delivery and ensure patient safety by regulating nurse-patient ratios and qualifications, making it highly relevant to the Healthcare sector. Other sectors are either not applicable or tangentially related, justifying low scores across them.


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