4932 results:


Summary: The bill outlines requirements for states to submit federally enforceable plans to the EPA, including emission standards, monitoring protocols, and compliance timelines for designated facilities.
Collection: Code of Federal Regulations
Status date: July 1, 2021
Status: Issued
Source: Office of the Federal Register

Keywords (occurrence): neural network (2)

Description: To amend the State Department Basic Authorities Act to establish a Deputy Secretary of State for Economic Security, redesignate and relocate other offices of the Department of State, and for other purposes.
Summary: The Economic Security and Diplomacy Act of 2024 establishes a Deputy Secretary of State for Economic Security, redistributes roles within the State Department, and addresses U.S. economic security matters such as sanctions and trade policies.
Collection: Legislation
Status date: Nov. 5, 2024
Status: Introduced
Primary sponsor: John Moolenaar (sole sponsor)
Last action: Referred to the House Committee on Foreign Affairs. (Nov. 5, 2024)

Category:
Societal Impact
Data Governance (see reasoning)

The text primarily concerns the establishment of a new position within the Department of State related to economic security, and it does explicitly reference 'artificial intelligence and machine learning tools' in the context of data analysis. This suggests a consideration of technology and its application in enhancing government functions. However, without broader discussions or mandates on the social implications of AI or robust data governance mentioned, the Social Impact and Data Governance categories receive lower scores. The references to technology indicate a slight relevance regarding the integrity of AI systems but do not deeply engage with the systematic concerns of integrity or robustness in AI system deployment. Accordingly, the scores are moderate for Social Impact and Data Governance, and slightly relevant for System Integrity and Robustness.


Sector:
Government Agencies and Public Services (see reasoning)

The bill is significant mainly within the Government Agencies and Public Services sector, emphasizing the restructuring of the Department of State and the establishment of new roles aimed at enhancing economic security through technology integration. There is no specific mention of how AI will impact areas like healthcare or the judicial system, nor does it address AI in the context of nonprofits, academic institutions, or political elections. Thus, the primary focus on government operations leads to a score of 4 for Government Agencies and Public Services, with other sectors receiving lower relevance due to the lack of direct mention or implications.


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

Description: An act to add Title 23 (commencing with Section 100600) to the Government Code, relating to health care coverage, and making an appropriation therefor.
Summary: Assembly Bill No. 2200 proposes the California Guaranteed Health Care for All program (CalCare), establishing a universal single-payer health care system for all residents, aiming to enhance access and reduce costs.
Collection: Legislation
Status date: Feb. 7, 2024
Status: Introduced
Primary sponsor: Ash Kalra (22 total sponsors)
Last action: In committee: Held under submission. (May 16, 2024)

Category:
Societal Impact (see reasoning)

The text does not primarily focus on the social impact of AI on individuals or society; rather, it highlights health care policy changes. However, it does mention 'health information technology' and 'artificial intelligence' in Section 100602(g), indicating that AI could play a role in optimizing health care delivery, possibly improving patient care. This is relevant to Social Impact due to potential effects on health equity and access. Therefore, this category could be considered moderately relevant. Data Governance is less relevant as the text mainly discusses health coverage and does not focus on data-related issues in AI systems. System Integrity could apply since the enforcement of health standards may involve oversight techniques akin to those for AI integrity, but there are no explicit mentions related to the integrity and transparency of AI systems. Robustness is not discussed comprehensively as the bill does not specify benchmarks or performance metrics for AI applications.


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

The document is strongly relevant to healthcare since it discusses the establishment of a comprehensive healthcare system through the California Guaranteed Health Care for All program (CalCare). The mention of health information technology and artificial intelligence relates to how technology, including AI, could improve care delivery within the healthcare sector, making this sector the most relevant. Although there are aspects of government operations mentioned, such as the governance structure, the primary focus remains centered around healthcare coverage and access. There is no direct information about politics, judiciary matters, labor and employment, academic institutions, or international cooperation. Nonprofits and NGOs aren't explicitly referenced either, though the program could interact with them regarding healthcare services.


Keywords (occurrence): artificial intelligence (4) show keywords in context

Summary: The bill introduces several public measures, including establishing a Coastal Blue Carbon Initiative to enhance carbon sequestration, and various other legislative proposals addressing issues like tax incentives, veterans' affairs, and political advertisement regulations.
Collection: Congressional Record
Status date: Oct. 4, 2024
Status: Issued
Source: Congress

Category:
Societal Impact (see reasoning)

In the text, there is a single reference to 'artificial intelligence-generated content' in the context of a bill (H.R. 9913) which prohibits the Federal Communications Commission from promulgating or enforcing rules regarding its disclosure in political advertisements. This falls directly within the realm of Social Impact, as it touches on the implications of AI in political discourse. The minimal mention of AI does not sufficiently engage with data governance, system integrity, or robustness as the text does not address data management, security measures, performance benchmarks, or related issues, which are essential for those categories.


Sector:
Politics and Elections (see reasoning)

The mention of AI is primarily associated with its application in political advertisements, making this text highly relevant to the sector of Politics and Elections. No other sectors are directly addressed, as the other bills and resolutions do not pertain to the application of AI outside of this specific context. Thus, the score for Politics and Elections is high, while other sectors are not mentioned.


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

Summary: Several public bills were introduced, focusing on issues like tax code amendments for ABLE programs, voter notification requirements, drug approval processes, and improving healthcare access, among others.
Collection: Congressional Record
Status date: Sept. 17, 2024
Status: Issued
Source: Congress

Category:
Societal Impact (see reasoning)

The text outlines various bills and resolutions, among which H.R. 9639 explicitly mentions the use of artificial intelligence (generative AI) in the context of political campaign regulations. This indicates a clear social impact from AI, specifically regarding misinformation and the integrity of electoral processes. There's no other reference within these legal texts that directly relates to data governance, system integrity, or robustness for AI systems. Only the specific mention in H.R. 9639 holds relevance to these categories, thus leading us to focus our scoring primarily on social impact.


Sector:
Politics and Elections (see reasoning)

Within the outlined bills, there are references to the governance of political processes and voting, specifically through bill H.R. 9639 which addresses the prohibition of fraudulent activity in electoral procedures that potentially utilizes AI-generated content. Therefore, this falls directly under 'Politics and Elections'. The other bills listed do not make any references to AI or its implications in their respective sectors. This suggests that only the 'Politics and Elections' sector is impacted significantly while the other sectors lack any relevant mention of AI applications.


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

Description: An Act to Enact the Maine Data Privacy and Protection Act
Summary: The Maine Data Privacy and Protection Act establishes regulations for managing, collecting, and processing personal data, requiring affirmative consent and safeguarding individuals' privacy rights in data transactions.
Collection: Legislation
Status date: April 17, 2024
Status: Other
Primary sponsor: Margaret O'Neil (5 total sponsors)
Last action: Placed in Legislative Files (DEAD) (April 17, 2024)

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

This text predominantly addresses data privacy and protection, with a strong emphasis on how covered algorithms utilize AI techniques. It explicitly mentions 'artificial intelligence' and 'machine learning' when defining what constitutes a covered algorithm, suggesting a direct concern with how these technologies process personal data. The legislation appears to seek to control how AI can manipulate data about individuals, which ties it profoundly to issues of Social Impact, Data Governance, and System Integrity. However, there is a lesser emphasis on performance benchmarks for AI systems, indicating that Robustness might not be as relevant. Therefore, it scores highest on Social Impact and Data Governance, and moderately for System Integrity due to the focus on the protection and management of data involved in AI systems.


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

The legislation has strong implications for various sectors. In terms of Government Agencies and Public Services, the act outlines provisions that could affect how public entities manage personal data, especially those using AI for decision-making. However, it doesn’t explicitly mention applications in politics, the judicial system, healthcare, or other sectors. Thus, while it may have indirect relevance to multiple sectors, such as Private Enterprises through the regulation of covered data, it’s especially impactful for Government Agencies as they are responsible for handling large amounts of personal data. The final scores reflect this broad but focused relevance without strong ties to sectors like Politics and Elections, Judicial System, or Healthcare.


Keywords (occurrence): artificial intelligence (1) machine learning (1) algorithm (19) show keywords in context

Summary: The bill regulates the labeling and packaging requirements for biological products, ensuring compliance during inspections and emphasizing accurate information for safe administration and handling of vaccines, particularly for poultry and mammals.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2024
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily discusses regulations regarding the labeling and packaging of biological products. It does not explicitly address issues related to AI, such as the impacts of automated decision-making or algorithmic bias. Therefore, Social Impact and Data Governance are not relevant as they deal with societal implications of AI and data management that are not implicated in biological product packaging. System Integrity could have limited relevance concerning oversight and inspection procedures mentioned, but there is no specific mention of AI oversight. Robustness is unlikely to relate as it deals with performance benchmarking of AI systems, which the text does not mention. The absence of direct references to AI concepts or implementations results in low relevance across all categories.


Sector: None (see reasoning)

The text pertains to labeling and packaging of biological products and does not address any specific use or regulation of AI within sectors like politics, healthcare, or public services. There are no references to AI applications within government agencies or the private sector, nor does it discuss AI's role in the judicial system or the nonprofit sector. The text remains confined to regulatory details pertinent to biological products without broader implications or applications to AI, leaving relevance in all sectors at a minimum level.


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

Description: Concerns regulation of automated systems and artificial intelligence used by State agencies.
Summary: The bill establishes regulations for automated systems and AI used by New Jersey state agencies, emphasizing accountability, risk mitigation, and the creation of an oversight board to ensure ethical practices.
Collection: Legislation
Status date: Jan. 9, 2024
Status: Introduced
Primary sponsor: Troy Singleton (sole sponsor)
Last action: Introduced in the Senate, Referred to Senate State Government, Wagering, Tourism & Historic Preservation Committee (Jan. 9, 2024)

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

The text provides extensive information regarding the regulation and use of automated systems and artificial intelligence specifically in the context of State agencies. This involves the establishment of an Artificial Intelligence Officer, guidelines for the use and implementation of AI systems, and requirements to mitigate risks and ensure ethical considerations in the deployment of these technologies. EIther of the categories is highly relevant given the focus on accountability, oversight, standards, and possible impacts of AI systems on society and individuals, making them imperative to review. Moreover, terms like automated decision support system and critical decision are directly mentioned, which relate closely to 'data governance' and 'system integrity.' Thus, all four categories are very relevant to the text.


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

The text addresses the use and regulation of AI systems specifically by State agencies, indicating a clear focus on how government bodies utilize AI. This involves oversight mechanisms, public accountability, and the implications of AI deployment in government services, covering various relevant sectors such as Public Services and potentially impacting politics through governance decisions. The discussion of an advisory board composed of public members and state officials further emphasizes its government-related significance, making it relevant across multiple sectors, but with the strongest relevance to 'Government Agencies and Public Services.'


Keywords (occurrence): artificial intelligence (56) machine learning (2) automated (111) show keywords in context

Description: Requires DOH to evaluate technology uses in long-term care settings, implements certain technological requirements within long-term care settings, and clarifies existing telehealth reimbursement parity includes long-term care settings.
Summary: The bill mandates the New Jersey Department of Health to assess and enhance technology use in long-term care settings, ensuring requirements for electronic health records and telehealth reimbursement parity are met.
Collection: Legislation
Status date: June 17, 2024
Status: Introduced
Primary sponsor: Joe Danielsen (2 total sponsors)
Last action: Introduced, Referred to Assembly Aging and Human Services Committee (June 17, 2024)

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

The bill primarily deals with the evaluation and implementation of technology within long-term care facilities, with explicit mentions of artificial intelligence and smart systems aimed at improving administration and service delivery. In relation to 'Social Impact', the mention of technology enhancing care delivery and patient independence indicates a focus on positive societal outcomes; however, there is less emphasis on the broader societal implications of AI or regulation regarding psychological harm, misinformation, or bias, thus scoring moderately relevant. 'Data Governance' is relevant due to the requirement for an electronic health record system, emphasizing secure data management and interoperability, meriting a higher score for addressing the accuracy and security of personal health information. 'System Integrity' has moderate relevance given the focus on compliance and interoperability but does not delve deeply into security measures or control beyond data sharing. 'Robustness' is less relevant as there is limited focus on benchmarks for AI performance, certification, or oversight bodies directly addressing robustness in AI systems.


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

The legislation has direct implications for 'Healthcare', particularly given its focus on long-term care settings and the integration of technology to improve health outcomes. The bill encourages the use of AI and smart systems, targeting advancements in patient management and monitoring, warranting a high score for this sector. 'Government Agencies and Public Services' is also relevant, as it discusses the oversight by the Department of Health and how these technological integrations will assist state service delivery, again meriting a moderate to high score. Other sectors like 'Politics and Elections', 'Judicial System', 'Private Enterprises, Labor, and Employment', 'Academic and Research Institutions', 'International Cooperation and Standards', 'Nonprofits and NGOs', and 'Hybrid, Emerging, and Unclassified', receive lower scores, as they do not clearly pertain to the legislation's focus on healthcare and technology in long-term care settings.


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

Summary: The Servicemember Quality of Life Improvement and National Defense Authorization Act for Fiscal Year 2025 aims to authorize military funding and construction while addressing personnel needs, with ongoing discussions about foreign aid and munitions policy.
Collection: Congressional Record
Status date: June 13, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

The text primarily deals with military funding and policies related to the National Defense Authorization Act (NDAA) for Fiscal Year 2025. It expresses political opinions particularly regarding military assistance to Ukraine and general military spending. There is no explicit reference or analysis of AI-related legislation, nor does it address AI's societal impact, data governance, system integrity, or performance benchmarks related to AI. Thus, none of the defined categories are highly relevant to the text, leading to low scores across the board.


Sector: None (see reasoning)

The text largely revolves around military appropriations and does not specifically engage with regulations regarding AI in any sector, including political, governmental, judicial, healthcare, or any other defined sector. Since AI is not mentioned and its governance or implications in any sector are not addressed, relevance scores are minimal across all sectors as well.


Keywords (occurrence): artificial intelligence (19) machine learning (8) large language model (1) show keywords in context

Summary: The bill establishes guidelines for NASA's systematic review process for declassifying information, emphasizing training for classifiers, prioritizing coordination with other agencies, and ensuring compliance with classification standards.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2024
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The provided text is primarily focused on the systematic review for declassification procedures within NASA, which include guidelines for managing classified information, training for derivative classifiers, and ensuring proper classification decisions. However, there are no explicit mentions or implications regarding AI technologies or their impact on society, data management, system integrity, or robustness. The content is oriented towards administrative processes and does not engage with AI in any meaningful context, illustrating its lack of relevance to the categories outlined.


Sector: None (see reasoning)

The text primarily addresses declassification procedures specific to NASA and does not engage with the use or regulation of AI in any sector. There are no discussions of politics, government applications of AI, judicial considerations, healthcare implementations, private enterprise impacts, academic considerations, international standards, or nonprofits and NGOs. The focus is entirely on classification and declassification processes, highlighting a complete absence of AI-related content. Thus, it does not correspond to any of the defined sectors.


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

Description: An Act relating to social media and minors; and providing for an effective date.
Summary: HB 271 requires parental consent for minors to create social media accounts, mandates age verification, restricts targeted advertising, prohibits addictive features, and establishes penalties for violations.
Collection: Legislation
Status date: Jan. 16, 2024
Status: Introduced
Primary sponsor: Labor & Commerce (sole sponsor)
Last action: REFERRED TO LABOR & COMMERCE (Jan. 16, 2024)

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

The text addresses the regulation of social media platforms concerning minors, specifically focusing on consent and parental access to accounts. The mention of 'algorithm', 'artificial intelligence', and 'machine learning' directly ties it to Social Impact as it discusses technology's role in content personalization and its implications on minors. It also emphasizes accountability and monitoring responsibilities of platforms, which is relevant for System Integrity, particularly in the context of enforcing new safeguards for minors' online interactions. However, the emphasis is more about social responsibility than system robustness, though the use of technology in the regulations indicates some relevance there. Data Governance has less relevance as the focus isn't on the collection or management of data per se, but more on the permissions and parental controls related to it.


Sector:
Government Agencies and Public Services (see reasoning)

The legislation primarily targets the intersection of social media regulation and minors, which appropriately aligns with the category of Government Agencies and Public Services as it outlines legislative approaches to protect a vulnerable population using public services (social media). There are implications for politics and elections given that the regulation of content targeting minors can influence public discourse and political engagement among younger demographics, but the text doesn't explicitly address political campaigning or electoral processes. It doesn't specifically pertain to other sectors such as healthcare, judicial systems, or employment.


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

Description: A bill for an act relating to the conduct of elections, including the use of artificial intelligence and deceptive statements, and providing penalties. (Formerly HSB 599.)
Summary: The bill regulates election conduct by prohibiting the use of artificial intelligence in voting systems and mandates disclosures for AI-generated content, imposing penalties for deceptive practices in election-related materials.
Collection: Legislation
Status date: March 6, 2024
Status: Engrossed
Primary sponsor: Economic Growth And Technology (sole sponsor)
Last action: Fiscal note. (March 13, 2024)

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

This legislation explicitly addresses the use of artificial intelligence (AI) in the electoral process, particularly in terms of prohibiting its use in voting equipment and ensuring transparency regarding AI-generated content in campaign materials. This directly connects to social impact as it relates to the accountability of AI systems not only in maintaining election integrity but also in protecting public trust by mitigating misinformation and deceptive practices. The need for disclosures when AI is used in the creation of campaign materials further solidifies its relevance to the social impact of AI. Data governance is also relevant because the legislation addresses how AI-generated content should be disclosed to avoid deceptive practices and protect the integrity of election-related information. System integrity is highly relevant as the bill specifically prohibits the use of AI in automatic tabulating equipment and ballot marking devices, aiming to prevent manipulation. Robustness is less relevant since the focus here is more on accountability and transparency rather than on performance benchmarks for AI systems. Overall, the legislation has significant implications for the use of AI in elections, emphasizing the need for clear regulations on its use to safeguard democratic processes.


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

The text primarily addresses the use of AI in elections, making it most relevant to the sector of Politics and Elections. It explores how AI can and cannot be used in the election process and introduces regulations to combat misinformation, which directly relates to the conduct of elections. It also touches on aspects of Government Agencies and Public Services when considering the regulations that govern election conduct and how public service roles interact with AI technologies in ballot handling. However, the focus remains on the electoral aspect, thus justifying a higher score for Politics and Elections over other sectors. The relevance to the other sectors like Judicial System, Healthcare, Private Enterprises, Labor and Employment, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, and Hybrid, Emerging, and Unclassified is minimal or none at all as the text does not address them directly.


Keywords (occurrence): deepfake (7) show keywords in context

Summary: The bill outlines preapproved incidental activities that federal credit unions may engage in to support their business, such as certification services and charitable contributions, while establishing a process for approving new activities.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2024
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily outlines the regulations and definitions related to permissible activities for federal credit unions, with a focus on incidental powers necessary for credit unions to conduct their business. There are no explicit references or discussions regarding the impact of AI on society, data governance in AI systems, system integrity, or robustness as it pertains specifically to AI. The content is more oriented towards financial services and regulations applicable to credit unions, without any focus on AI application or influence. Therefore, the relevance to the specified categories is very low.


Sector: None (see reasoning)

The text deals with the regulatory framework for credit unions and their incidental powers, and it does not address the use of AI in any of the specified sectors. It focuses more on financial industry regulations, rather than applications or implications of AI in sectors such as politics, healthcare, public service, or similar areas. Since no mention of AI or its sector-specific applications are present, the assessment for relevance across all sectors is minimal.


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

Summary: The bill outlines the preapproved activities and services for Credit Union Service Organizations (CUSOs) while ensuring distinct corporate identities and financial independence from Federal insurance credit unions (FICUs).
Collection: Code of Federal Regulations
Status date: Jan. 1, 2024
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily discusses the preapproval of activities and services for Credit Union Service Organizations (CUSOs) and contains no explicit references to artificial intelligence or related technologies. Instead, it focuses on regulatory, governance, and operational aspects surrounding credit unions and their interactions with CUSOs. There are no elements related to social impact, data governance, system integrity, or robustness, as these topics are not addressed within the context of the activities and services detailed in the text. Therefore, all categories receive low relevance scores.


Sector: None (see reasoning)

The text does not pertain directly to any specific sector concerning AI use or regulatory impact. Although it mentions services related to credit unions and regulatory practices, these fall outside the sectors defined for AI-related legislation. As such, no relevant sectors apply to this text, leading to low relevance scores across the board.


Keywords (occurrence): automated (1)

Description: House Resolution Celebrating May 2, 2024, As "rhode Island College Day" In The State Of Rhode Island
Summary: The bill designates May 2, 2024, as "Rhode Island College Day" to celebrate the institution's contributions to education and community empowerment in Rhode Island.
Collection: Legislation
Status date: May 2, 2024
Status: Passed
Primary sponsor: Karen Alzate (10 total sponsors)
Last action: House read and passed (May 2, 2024)

Category: None (see reasoning)

The text primarily discusses Rhode Island College and celebrates May 2, 2024, as Rhode Island College Day. While it mentions the college's programs in cyber security and artificial intelligence, the legislation does not address AI's broader social implications or governance in detail. Hence, it is relevant, but only to a limited extent for categories like Social Impact, Data Governance, System Integrity, and Robustness, as it does not delve deeply into these areas.


Sector:
Academic and Research Institutions (see reasoning)

The text briefly touches on AI programs at Rhode Island College, making it relevant to education but not strongly tied to other sectors. It does not engage significantly with the political, judicial, healthcare, or labor aspects of AI, and does not describe legislative actions in these domains. The mention of AI implies some relevance to Academic and Research Institutions, but it is shallow. The mention of cyber security might relate to Government Agencies and Public Services, but it is not explicit enough to award a high score there.


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

Description: Prohibits social media websites from selectively suspending candidates for elective office and creates private right of action for users whose political or religious speech has been deleted.
Summary: The bill prohibits social media sites from selectively suspending candidates for office and allows users to sue if their political or religious speech is deleted or censored.
Collection: Legislation
Status date: Jan. 9, 2024
Status: Introduced
Primary sponsor: Dawn Fantasia (2 total sponsors)
Last action: Introduced, Referred to Assembly Consumer Affairs Committee (Jan. 9, 2024)

Category:
Societal Impact
System Integrity (see reasoning)

The text touches on the impact of algorithms in the context of social media, particularly how these algorithms can censor political and religious speech. This relates to the Social Impact category, as it raises issues of fairness and accountability in the context of AI's role in public discourse. The Data Governance category is less relevant; while the term 'algorithm' is defined, there is little focus on data management or accuracy. System Integrity is somewhat relevant because it discusses algorithms' roles in decision-making but does not focus extensively on security or transparency requirements; nevertheless, it introduces concerns over oversight of algorithms. Robustness is not highly relevant as the text does not directly address benchmarks or performance standards for AI but rather focuses on enforcement and penalties related to speech suppression.


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

The text specifically addresses the regulation of social media platforms, explicitly focusing on how these platforms can manage political and religious speech related to candidates for elective office. This makes it highly relevant to the Politics and Elections sector, as it directly pertains to electoral processes and candidate rights within the political sphere. It is also relevant to the Government Agencies and Public Services sector as it may implicate public service delivery via social media; however, it does not delve into specific applications of AI in governmental operations. There is minimal relevance to Judicial System, Healthcare, Private Enterprises, Labor and Employment, Academic and Research Institutions, and Nonprofits and NGOs as the text does not discuss those sectors' relationships with AI. The International Cooperation and Standards sector does not apply, nor is there sufficient content in the text to warrant classification under Hybrid, Emerging, and Unclassified.


Keywords (occurrence): algorithm (4) show keywords in context

Description: An act to add and repeal Part 5 (commencing with Section 4800) of Division 1 of the Unemployment Insurance Code, relating to benefits.
Summary: The bill establishes the California Unconditional Benefit Income (CalUBI) Pilot Program to provide $1,000 monthly for one year to individuals unemployed due to automation or AI, promoting economic security.
Collection: Legislation
Status date: Feb. 16, 2024
Status: Introduced
Primary sponsor: Evan Low (sole sponsor)
Last action: In committee: Set, first hearing. Hearing canceled at the request of author. (April 8, 2024)

Category:
Societal Impact (see reasoning)

The text specifically discusses the California Unconditional Benefit Income (CalUBI) Pilot Program, which is designed to provide financial assistance to individuals who become unemployed due to automation or artificial intelligence. This directly ties to the SOCIAL IMPACT category, as it addresses economic security and stability in relation to job displacement caused by AI and automation. The legislative aims are to promote welfare for individuals affected by these technologies and may also consider fairness and bias related to AI-driven unemployment, making this extremely relevant. In terms of DATA GOVERNANCE, while there are elements related to the eligibility criteria based on accurate data about employment status, the text does not deeply engage with issues like data management or compliance with privacy laws. Therefore, it's rated as slightly relevant. For SYSTEM INTEGRITY, mandates for transparency or oversight mechanisms in AI processes are not highlighted, so relevance is low. In regards to ROBUSTNESS, while the underlying principles about addressing AI performance parameters could be relevant, the text does not explicitly discuss performance benchmarks or auditing AI systems, resulting in low relevance here as well.


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

The text addresses the implications of automation and artificial intelligence on employment which ties closely to the sector of PRIVATE ENTERPRISES, LABOR, AND EMPLOYMENT, given the context of job displacement and labor market adjustments as a result of these technologies. The introduction of a universal basic income program indicates potential impacts on employment practices, making this sector highly relevant. Additionally, it touches on government efforts through specific proposals which connects it to GOVERNMENT AGENCIES AND PUBLIC SERVICES, but not to the extent that it overarches the primary concern around employment replacement. Other sectors such as POLITICS AND ELECTIONS or JUDICIAL SYSTEM are not directly relevant as the text does not discuss regulation within those frameworks. In the context of HEALTHCARE and ACADEMIC AND RESEARCH INSTITUTIONS, there is no direct reference made in the text, hence the scores reflect that absence of relevance. Nonprofits and international cooperation do not appear to be immediate concerns addressed, placing those further down in relevance too.


Keywords (occurrence): artificial intelligence (11) show keywords in context

Description: The purpose of this bill is to prohibit insurance rates in WV from being based upon credit or insurance scores.
Summary: The bill prohibits West Virginia insurance rates from being based on credit scores, ensuring no denial, cancellation, or non-renewal of personal insurance policies due to credit histories.
Collection: Legislation
Status date: Feb. 13, 2024
Status: Introduced
Primary sponsor: Charles Sheedy (sole sponsor)
Last action: To House Banking and Insurance (Feb. 13, 2024)

Category: None (see reasoning)

The text primarily addresses insurance practices and the prohibition of using credit or insurance scores to determine premiums. It does not explicitly address issues related to AI, such as discrimination through algorithmic decisions, data governance, or maintaining system integrity associated with AI technologies. Therefore, the text's relevance to Social Impact, Data Governance, System Integrity, or Robustness is minimal. Consequently, all categories will receive lower scores reflecting this limited relevance.


Sector: None (see reasoning)

The bill addresses insurance practices broadly, focusing on prohibiting certain rating practices rather than AI-specific usage or regulations. Thus, its relevance to the specified sectors is limited. While the bill could indirectly affect sectors like Private Enterprises or Government Agencies if they deal with insurance, this connection is not explicitly defined, leading to overall lower scores across all sectors.


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

Description: The purpose of this bill is to create the criminal offenses of creating, producing, distributing, receiving, or possessing with intent to distribute visual depictions artificial intelligence created child pornography when no actual minor is depicted.
Summary: The bill prohibits the creation, distribution, or possession of AI-generated child pornography in West Virginia, criminalizing such actions to protect children from exploitation.
Collection: Legislation
Status date: Feb. 20, 2024
Status: Engrossed
Primary sponsor: Amy Nichole Grady (11 total sponsors)
Last action: On 3rd reading with right to amend, Special Calendar (March 8, 2024)

Category:
Societal Impact (see reasoning)

The text explicitly addresses the use of Artificial Intelligence in the context of creating, producing, or distributing child pornography. It discusses the specific issues related to AI-generated depictions and their potential to evade sanctions meant for traditional child pornography. Since the legislation primarily concerns the social risks posed by AI technologies in terms of child exploitation, it is very relevant to the Social Impact category. The legislation does discuss some governance aspects about data surrounding AI-generated media, but its primary focus is not on data management or security of those AI systems. System Integrity and Robustness are not addressed since they pertain to security measures and performance benchmarks, which are secondary to the focus of the bill on social harm. Therefore, the Social Impact category scores highest with a 5, while the others score much lower on relevance.


Sector:
Judicial system (see reasoning)

The legislation directly relates to the impact of AI technologies within the realm of child protection and the legal ramifications of producing and distributing AI-generated child pornography. It is particularly aligned with the concerns surrounding societal and legal issues connected to AI misuse, thus making it relevant to the sector of the Judicial System. However, it does not specifically address the use of AI in political, healthcare, employment, or public service contexts, which limits its relevance in those areas. It does not relate to non-profits and academic institutions either. Therefore, I consider Judicial System to be somewhat relevant, with a score of 3, while all other sectors score 1 due to the lack of specific references or relevance.


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