...gating economic disruption and identifying 31
new economic opportunities created by automation and artificial intelligence. 32
The committee's recommendations shall include con sideration of workforce 33
impacts and potential growth within emerging industries projected to expand 34
alongside these technologies, includ...
...22
Governor. 23
(2) Two persons representing employers or trade organizations focused on the 24
automated workplace, appointed by the Governor. 25
(3) Two persons who are members of the Senate at the time of appointment, at 26
least one of who m represents the minority party, appointed by the Presiden...
4776 results:
Description: Study Automation and the Workforce
Summary: Senate Bill 746 establishes a Study Committee on Automation and the Workforce in North Carolina to assess automation's effects on employment, particularly for low-income and minority workers, and recommend mitigation strategies.
Collection: Legislation
Status date: March 25, 2025
Status: Introduced
Primary sponsor: DeAndrea Salvador
(6 total sponsors)
Last action: Ref To Com On Rules and Operations of the Senate (March 26, 2025)
Keywords (occurrence):
artificial intelligence (1)
automated (1)
show keywords in context
Description: Crimes and punishments; sexual obscenity; making certain acts unlawful; effective date.
Summary: This bill criminalizes the nonconsensual dissemination of private sexual images and artificially generated sexual depictions in Oklahoma, establishing penalties for offenders and defining relevant terms. It aims to protect individuals from privacy violations.
Collection: Legislation
Status date: March 26, 2025
Status: Engrossed
Primary sponsor: Toni Hasenbeck
(3 total sponsors)
Last action: First Reading (March 26, 2025)
Keywords (occurrence):
artificial intelligence (3)
automated (1)
show keywords in context
Description: Relative to consumer health data. Consumer Protection and Professional Licensure.
Summary: The bill establishes the "Consumer Health Data Act" in Massachusetts, aiming to enhance privacy protections by requiring explicit consumer consent for the collection and sharing of health-related personal data.
Collection: Legislation
Status date: Feb. 27, 2025
Status: Introduced
Primary sponsor: Lindsay Sabadosa
(4 total sponsors)
Last action: Senate concurred (Feb. 27, 2025)
Keywords (occurrence):
machine learning (1)
show keywords in context
Description: A bill to prohibit the distribution of materially deceptive AI-generated audio or visual media relating to candidates for Federal office, and for other purposes.
Summary: The "Protect Elections from Deceptive AI Act" aims to prohibit the distribution of misleading AI-generated audio or visual media related to federal candidates, safeguarding electoral integrity.
Collection: Legislation
Status date: Sept. 12, 2023
Status: Introduced
Primary sponsor: Amy Klobuchar
(6 total sponsors)
Last action: Placed on Senate Legislative Calendar under General Orders. Calendar No. 388. (May 15, 2024)
Keywords (occurrence):
artificial intelligence (1)
machine learning (1)
deep learning (2)
show keywords in context
Description: Creates various sections of KRS Chapter 186 to establish a regulatory framework for the operation of fully autonomous vehicles on public highways, to define terms, to establish requirements for autonomous vehicles and automated driving systems, to provide that from the effective date of the Act until July 31, 2026, any fully autonomous vehicle for which the declared gross weight is more than 62,000 pounds shall be required to have an appropriately credentialed human driver in the vehicle to m...
Summary: The bill establishes regulations for the operation of fully autonomous vehicles without human drivers in Kentucky, focusing on safety, insurance, and compliance with traffic laws while promoting the use of automated driving systems.
Collection: Legislation
Status date: April 12, 2024
Status: Passed
Primary sponsor: Josh Bray
(4 total sponsors)
Last action: delivered to Secretary of State (Acts Ch. 176) (April 12, 2024)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): automated (25) autonomous vehicle (29) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
This legislation primarily focuses on the operation and regulation of fully autonomous vehicles, which inherently involve AI and automated driving systems. The Social Impact category is relevant due to potential societal implications of autonomous vehicles, such as safety, ethics, and the role of human agency in driving. The Data Governance category is moderately relevant as it relates to the data handling processes associated with vehicle accidents and operational details. The System Integrity category is very relevant, given the security measures and operational protocols involved in managing automated driving systems. The Robustness category is slightly relevant in that it concerns compliance with performance standards of these automated systems but does not primarily focus on benchmarks or systematic evaluation. Therefore, the scores will reflect these evaluations.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
The text primarily concerns the use of AI technologies in the context of autonomous vehicles. It touches upon critical sectors such as Government Agencies and Public Services due to regulatory implications on public transport. It also relates to the Private Enterprises, Labor, and Employment sector as industrial settings for AI technology in automotive sectors are heavily influenced by these regulations. There are minimal direct mentions relevant to Judicial System, Healthcare, Academic Institutions, or NGOs in this context. Thus, the scores indicate strong relevance only for Government Agencies and Public Services, and Private Enterprises, Labor, and Employment.
Keywords (occurrence): automated (25) autonomous vehicle (29) show keywords in context
Description: Enacts the "New York artificial intelligence consumer protection act", in relation to preventing the use of artificial intelligence algorithms to discriminate against protected classes.
Summary: The "New York Artificial Intelligence Consumer Protection Act" aims to prevent discrimination against protected classes by regulating high-risk artificial intelligence algorithms through documentation, risk management, and audits to ensure compliance.
Collection: Legislation
Status date: Jan. 14, 2025
Status: Introduced
Primary sponsor: Kristen Gonzalez
(sole sponsor)
Last action: REFERRED TO INTERNET AND TECHNOLOGY (Jan. 14, 2025)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (96) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
The 'New York Artificial Intelligence Consumer Protection Act' explicitly addresses AI by preventing discrimination based on algorithmic outputs, which directly aligns with the Social Impact category due to its emphasis on ethical applications of AI that affect protected classes. It also touches on technical aspects of data management and bias auditing relevant to Data Governance. The requirement for risk management and oversight mechanisms indicates a consideration of System Integrity as it pertains to accountability and protection against misuse of AI. Although the text mentions measures for performance and evaluation, it does not focus on establishing new benchmarks or metrics for AI systems, making Robustness less relevant in this case.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
The legislation is centered around consumer protection in the context of AI algorithms, which relates primarily to the private sector where businesses deploy AI systems. It has implications for various sectors, including Public Services (ensuring fair access to services and preventing discrimination) and perhaps contact with Government Agencies as it emphasizes compliance and audits, but these are not dominant themes. It does not directly address areas like Healthcare, Judicial System, or International Cooperation, which lessens their relevance significantly. Academic and research aspects are not highlighted either. The relevance to Nonprofits or NGOs appears minimal, though they may be involved in advocacy for ethical AI policies. Therefore, the most appropriate classification would be under Private Enterprises, related to labor and employment since the Act addresses the impact of AI on employment decisions.
Keywords (occurrence): artificial intelligence (96) show keywords in context
Description: Citing this act as the "Promoting Work, Deterring Fraud Act of 2024"; providing requirements for reemployment assistance benefit conditions for non-Florida residents; removing requirements that certain skills assessments of claimants be voluntary; revising circumstances under which the department disqualifies claimants from benefits; requiring the department to verify claimants' identities before paying benefits; requiring the department to procure an online workforce search and match tool fo...
Summary: The "Promoting Work, Deterring Fraud Act of 2024" enhances eligibility verification for Florida's reemployment assistance benefits, imposing stricter identity checks, cross-checks against databases, and mandatory reporting requirements for claimants.
Collection: Legislation
Status date: March 8, 2024
Status: Other
Primary sponsor: Jay Trumbull
(sole sponsor)
Last action: Died in Appropriations Committee on Transportation, Tourism, and Economic Development (March 8, 2024)
Category:
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (1) show keywords in context
Data Robustness (see reasoning)
The text primarily addresses the verification of reemployment assistance benefit eligibility and the implementation of an online workforce search and match tool. While it references 'artificial intelligence generation' in the context of matching job seekers to opportunities, it does not delve into the broader societal impacts of AI, issues of data governance related to AI systems, or questions of system integrity or robustness in these AI applications. Therefore, it is relevant mainly in terms of its technological aspect but not deeply in any of the four categories. This leads to moderate relevancy due to the explicit mention of AI in the hiring tool context.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
The text is particularly relevant to the 'Government Agencies and Public Services' sector since it outlines measures taken by the Department of Commerce regarding reemployment assistance, including identity verification and fraud prevention through AI tools. It also touches upon workforce development and job matching, which are relevant to public employment services provided by the government. The sectors of 'Private Enterprises, Labor, and Employment' and 'Academic and Research Institutions' may see slight relevance through possible interactions with workforce development tools and training opportunities, but the primary focus is on government administrative functions.
Keywords (occurrence): artificial intelligence (1) show keywords in context
Description: Requires the division of criminal justice services to formulate a protocol for the regulation of the use of artificial intelligence and facial recognition technology in criminal investigations; restricts the use of artificial intelligence-generated outputs in court.
Summary: This bill mandates New York’s criminal justice services to establish protocols for regulating the use of AI and facial recognition in investigations, while prohibiting their use as evidence in court to protect defendants' rights.
Collection: Legislation
Status date: March 21, 2025
Status: Introduced
Primary sponsor: Rodneyse Bichotte Hermelyn
(sole sponsor)
Last action: referred to codes (March 21, 2025)
Keywords (occurrence):
artificial intelligence (7)
machine learning (1)
show keywords in context
Description: Establishes guidelines for creditworthiness determinations concerning affordable housing programs.
Summary: This bill establishes guidelines for evaluating creditworthiness in affordable housing applications, aiming to prevent discrimination against low- and moderate-income applicants with damaged credit due to financial struggles.
Collection: Legislation
Status date: Jan. 9, 2024
Status: Introduced
Primary sponsor: Shirley Turner
(2 total sponsors)
Last action: Introduced in the Senate, Referred to Senate Community and Urban Affairs Committee (Jan. 9, 2024)
Category:
Societal Impact (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): algorithm (1) show keywords in context
Societal Impact (see reasoning)
The text discusses the establishment of guidelines for evaluating creditworthiness in affordable housing, with a focus on how algorithms and risk scores can lead to discrimination against low- and moderate-income households. It highlights the potential for AI-related systems (like credit scoring algorithms) to negatively affect people's access to housing based on biased outputs. Therefore, it is relevant to the Social Impact category. While some mentions of data and assessment processes hint at data governance, the primary focus is on the social ramifications of using these assessments rather than strictly the management or security of data within AI systems. The System Integrity category does not apply here, as the legislation does not specifically address security measures for AI. Robustness is also not relevant, as the legislation does not deal with performance benchmarks for AI systems.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
The text relates to the Government Agencies and Public Services sector due to its implications for public housing programs and regulation of landlords. It does not directly address Politics and Elections, Judicial System, Healthcare, or any other specific sector. While it has indirect relevance to Private Enterprises (landlords as businesses), the primary focus is on public housing access and creditworthiness theories, not enterprise-specific legislation.
Keywords (occurrence): algorithm (1) show keywords in context
Description: Creating a charter of people's personal data rights.
Summary: The bill establishes a "People's Privacy Act" in Washington, granting residents rights over their personal data, including consent requirements for collection and usage, and imposing penalties for violations.
Collection: Legislation
Status date: Jan. 26, 2023
Status: Introduced
Primary sponsor: Shelley Kloba
(4 total sponsors)
Last action: By resolution, reintroduced and retained in present status. (Jan. 8, 2024)
Category:
Societal Impact
Data Governance (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (3) automated (5) show keywords in context
Societal Impact
Data Governance (see reasoning)
The text is primarily focused on personal data rights and privacy, particularly as they relate to the handling of personal information by entities within Washington state. It emphasizes the significance of protecting personal data that may be used in automated processes, and it addresses potential harms stemming from privacy violations, including discrimination driven by AI systems. The presence of terms such as 'algorithms' plainly relates to the Data Governance and Social Impact categories due to its emphasis on data security and the consequences of its misuse on marginalized communities. Thus, relevance to the discussed categories will vary. The System Integrity category could be only slightly relevant as it touches on oversight and obligations related to data collection and processing but doesn't explicitly outline measures for AI system integrity. The Robustness category is not explicitly relevant since benchmarks, compliance, and oversight for AI performance are not discussed.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
The text details legislation related to data privacy and personal rights in the context of Washington state. While it does not specifically mention sectors such as Healthcare or Education, it addresses issues that can closely touch upon the sectors of Government Agencies and Public Services (as it regulates entities interacting with personal data) and Private Enterprises, Labor, and Employment (due to implications for businesses handling personal information). The primary sector connections here will thus be with Government Agencies and Private Enterprises, which focused on data handling standards.
Keywords (occurrence): artificial intelligence (3) automated (5) show keywords in context
Description: Creating the Right to Compute Act and requiring shutdowns of AI controlled critical infrastructure
Summary: The "Right to Compute Act" establishes the right to own and use computational resources, mandates shutdown protocols for AI-controlled critical infrastructure, and emphasizes risk management policy compliance.
Collection: Legislation
Status date: March 28, 2025
Status: Enrolled
Primary sponsor: Daniel Zolnikov
(sole sponsor)
Last action: (S) Sent to Enrolling (March 28, 2025)
Keywords (occurrence):
artificial intelligence (13)
machine learning (3)
show keywords in context
Description: Enacts regulations on automated license plate reader systems
Summary: This bill regulates automated license plate reader systems in Missouri, prohibiting state agencies from purchasing or using them, while excluding certain law enforcement and third-party data uses.
Collection: Legislation
Status date: Jan. 31, 2024
Status: Introduced
Primary sponsor: Mike Cierpiot
(sole sponsor)
Last action: Second Read and Referred S Transportation, Infrastructure and Public Safety Committee (Feb. 8, 2024)
Category:
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): automated (5) show keywords in context
Data Governance
System Integrity (see reasoning)
The text explicitly addresses the regulation of automated license plate reader systems, which involves the use of computer algorithms to process data. While it touches upon the governance and management of technology through regulations, it does not deeply explore the broader social impacts of AI, data privacy concerns, or the integrity of the system beyond how it may apply to automated license plate readers. It discusses specific terms and rafts legal boundaries for usage without addressing wider nuances of AI's influence.
Sector:
Government Agencies and Public Services (see reasoning)
This bill directly pertains to government use of AI technology, specifically regarding public safety systems like license plate readers. It limits the use of these systems by governmental bodies and outlines associated data handling, which is pertinent to the regulation of AI in governmental contexts. The relevance is moderate since it discusses the implementation and implications of such technology in public agencies but lacks broader implications for other sectors.
Keywords (occurrence): automated (5) show keywords in context
Description: Amend The South Carolina Code Of Laws By Adding Article 6 To Chapter 5, Title 39 So As To Stop Certain Social Media Censorship, To Provide Penalties, And To Provide Exceptions.
Summary: The Stop Social Media Censorship Act aims to prevent online censorship by social media platforms, establishing penalties for deceptive practices and protecting users' political and religious speech in South Carolina.
Collection: Legislation
Status date: Jan. 10, 2023
Status: Introduced
Primary sponsor: James Burns
(4 total sponsors)
Last action: Member(s) request name added as sponsor: Beach (Feb. 2, 2023)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Politics and Elections
Government Agencies and Public Services
Judicial system (see reasoning)
Keywords (occurrence): algorithm (3) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text discusses social media censorship and the use of algorithms, making it relevant to all four categories. In terms of 'Social Impact', it raises issues on the impact of censorship on political and religious speech, which directly aligns with societal impacts of AI-driven moderation. For 'Data Governance', while not explicitly focused on data management, the reference to algorithms and the requirement for fair practices in speech indirectly invokes considerations of how data-related practices affect users. 'System Integrity' is relevant due to the mention of algorithmic use and potential biases in social media platforms, seeking to ensure users have human-level oversight in case of disputes. 'Robustness' is relevant as the bill discusses maintaining standards for algorithms that govern speech, although the main focus is on censorship rather than performance metrics. Overall, there is a significant emphasis on the social implications and the governance of algorithms with respect to public discourse and trust, contributing to higher scores.
Sector:
Politics and Elections
Government Agencies and Public Services
Judicial system (see reasoning)
The legislation prominently addresses issues pertinent to the regulation of AI through algorithms on social media, especially in the context of political speech, making it highly relevant to 'Politics and Elections'. The potential penalties and standards for algorithmic moderation also lend relevance to 'Government Agencies and Public Services', as officials may need to enforce these regulations. 'Judicial System' relevance is evident through its implications for legal actions users can take against social media platforms. While healthcare and private enterprise sectors are not directly addressed, the principle of algorithm accountability may resonate in these areas as they intersect with operational practices of various entities. Overall, 'Politics and Elections' stands out as the most relevant sector closely tied to the legislative text's focus on censorship and algorithmic influence.
Keywords (occurrence): algorithm (3) show keywords in context
Description: Enacts the "political artificial intelligence disclaimer (PAID) act"; requires political communications that use synthetic media to disclose that they were created with the assistance of artificial intelligence; requires committees that use synthetic media to maintain records of such usage.
Summary: The "Political Artificial Intelligence Disclaimer (PAID) Act" mandates disclosure of synthetic media usage in political communications and requires committees to maintain and report records of such usage to ensure transparency.
Collection: Legislation
Status date: Jan. 17, 2025
Status: Introduced
Primary sponsor: Kevin Parker
(sole sponsor)
Last action: REFERRED TO ELECTIONS (Jan. 17, 2025)
Category:
Societal Impact
Data Governance (see reasoning)
Sector:
Politics and Elections (see reasoning)
Keywords (occurrence): artificial intelligence (3) automated (1) synthetic media (5) show keywords in context
Societal Impact
Data Governance (see reasoning)
The text specifically addresses the impact of AI in the context of political communications, especially focusing on synthetic media and the necessity for disclosure regarding AI assistance. This touches on issues of accountability and transparency in AI use in political discourse, which are key elements of the Social Impact category. Given its focus on ensuring that political communications made with AI tools do not mislead voters, the relevance to Social Impact is extremely high. It also indirectly relates to Data Governance as it implies the management of records related to the use of AI in political contexts, but its primary emphasis is clearly on social implications. Although it discusses some aspects of oversight and record-keeping, it does not touch directly on system integrity or robustness in a significant way. Therefore, only Social Impact is rated as highly relevant, while Data Governance is considered moderately relevant due to its connection to record keeping but lacks a direct focus on data management issues.
Sector:
Politics and Elections (see reasoning)
The text deals specifically with the regulation of synthetic media in political communications, indicating a clear tie to the politics and elections sector. The need for disclosure about the use of artificial intelligence highlights the efforts to ensure transparency in political processes, making it extremely relevant to the political sector. It does not pertain to government agencies, the judicial system, healthcare, or other sectors because its primary focus lies within the political domain. Thus, it receives a high score in the Politics and Elections sector. Other sectors do not apply as they do not involve direct relevance to the AI's use in political contexts.
Keywords (occurrence): artificial intelligence (3) automated (1) synthetic media (5) show keywords in context
Description: HEALTH AND SAFETY -- REPRODUCTIVE FREEDOM AND GENDER AFFIRMING CARE HEALTH DATA PRIVACY ACT - Creates the reproductive freedom and gender affirming care health data privacy act.
Summary: The bill establishes the Reproductive Freedom and Gender Affirming Care Health Data Privacy Act, aimed at protecting consumer health data related to reproductive and gender-affirming care in Rhode Island.
Collection: Legislation
Status date: Feb. 28, 2025
Status: Introduced
Primary sponsor: Jason Knight
(10 total sponsors)
Last action: Introduced, referred to House Health & Human Services (Feb. 28, 2025)
Keywords (occurrence):
machine learning (1)
show keywords in context
Description: For legislation to implement annual statewide public employee cybersecurity training. Advanced Information Technology, the Internet and Cybersecurity.
Summary: This bill mandates annual cybersecurity training for all state, county, and municipal employees in Massachusetts, aiming to enhance public cybersecurity awareness and establish a comprehensive state cybersecurity framework.
Collection: Legislation
Status date: Feb. 27, 2025
Status: Introduced
Primary sponsor: Michael Moore
(2 total sponsors)
Last action: Hearing scheduled for 04/09/2025 from 01:00 PM-05:00 PM in A-1 (March 24, 2025)
Keywords (occurrence):
artificial intelligence (13)
machine learning (2)
automated (32)
algorithm (1)
show keywords in context
Description: To amend the Federal Election Campaign Act of 1971 to provide further transparency and accountability for the use of content that is generated by artificial intelligence (generative AI) in political advertisements by requiring such advertisements to include a statement within the contents of the advertisements if generative AI was used to generate any image or video footage in the advertisements, and for other purposes.
Summary: The REAL Political Advertisements Act mandates transparency in political ads by requiring disclosures when AI-generated content, like images or videos, is used, enhancing accountability in political communications.
Collection: Legislation
Status date: May 2, 2023
Status: Introduced
Primary sponsor: Yvette Clarke
(sole sponsor)
Last action: Referred to the House Committee on House Administration. (May 2, 2023)
Category:
Societal Impact
System Integrity (see reasoning)
Sector:
Politics and Elections (see reasoning)
Keywords (occurrence): artificial intelligence (6) show keywords in context
Societal Impact
System Integrity (see reasoning)
The text explicitly addresses the use of artificial intelligence (AI) in political advertisements and emphasizes the importance of transparency and accountability in these ads. This directly relates to the social implications of AI on public discourse, particularly concerning misinformation and the integrity of democratic processes. The legislation aims to mitigate the risks associated with the misuse of AI-generated content in political contexts, establishing a clear connection to the social impact of AI. Therefore, 'Social Impact' scores high. In terms of 'Data Governance', while the act implies indirect concerns about data through its transparency requirements, it does not directly tackle data management issues like accuracy or bias in datasets. Hence, it scores low here. For 'System Integrity', the requirement for clear disclaimers enhances the integrity of the information presented, but it does not delve into comprehensive measures for system security or human oversight. Consequently, it receives a moderate score. Lastly, 'Robustness' deals with the specific benchmarks and compliance for AI systems, which is not the primary focus of this act, resulting in a low score.
Sector:
Politics and Elections (see reasoning)
The text is specifically about political advertisements and their regulation in the context of AI, directly aligning it with the 'Politics and Elections' sector. The act mandates transparency regarding the use of AI in these advertisements, enhancing the democratic process. While there may be elements affecting 'Government Agencies and Public Services', it is not primarily focused on government operations outside of election processes, so that score is lower. The bill does not attempt to address the use of AI in healthcare, the judicial system, employment, research, international cooperation, or the operation of nonprofits. It neither fits into 'Hybrid, Emerging, and Unclassified' as it explicitly pertains to a defined sector. Therefore, the strongest match remains with 'Politics and Elections', resulting in a high score.
Keywords (occurrence): artificial intelligence (6) show keywords in context
Description: For legislation to implement the recommendations of the special commission on facial recognition technology. The Judiciary.
Summary: The bill implements recommendations on facial recognition technology, restricting law enforcement's use, requiring oversight, and ensuring accountability, aiming to enhance privacy rights and mitigate potential misuse.
Collection: Legislation
Status date: Feb. 16, 2023
Status: Introduced
Primary sponsor: Orlando Ramos
(40 total sponsors)
Last action: Accompanied a new draft, see H4359 (Feb. 12, 2024)
Category:
Societal Impact
System Integrity (see reasoning)
Sector:
Judicial system (see reasoning)
Keywords (occurrence): automated (5) algorithm (1) show keywords in context
Societal Impact
System Integrity (see reasoning)
The text discusses legislation focused on facial recognition technology, categorizing it as a form of biometric surveillance technology. This directly engages with societal concerns, particularly regarding how such technologies could impact privacy, civil rights, and potential misuse by law enforcement. The mention of regulations preventing unlawful biometric surveillance and requirements for accountability suggests a significant intersection with social impact. The aspect of holding law enforcement agencies accountable and ensuring transparency around facial recognition searches, including the implications of data use, is integral for evaluating the social ramifications of AI technologies. Therefore, Social Impact is rated very relevant. For Data Governance, while there are suggestions for documentation and reporting of facial recognition searches, the text focuses more on usage and accountability rather than specific data management policies, making it slightly relevant. System Integrity is pertinent due to the mentions of human intervention and regulatory requirements that enhance security and transparency in the usage of the technology. Robustness is less relevant as the text focuses more on legislative measures than on performance benchmarks or compliance audits for AI systems, so it is rated not relevant.
Sector:
Judicial system (see reasoning)
The text is primarily focused on the use of facial recognition technology, which is closely associated with the Judicial System due to its implications in law enforcement, investigations, and the legal consequences that arise from the use of such technology. It articulates how law enforcement can use facial recognition and sets rules for its application in judicial proceedings, highlighting its relevance to the sector. The discussion does not specifically engage with Politics and Elections or Government Agencies beyond their regulatory roles, as it primarily focuses on law enforcement agencies. It also does not touch upon Healthcare, Private Enterprises, Academic Institutions, International Cooperation, Nonprofits, or Emerging Sectors. Therefore, Judicial System is rated very relevant while the other sectors are rated not relevant as they are not addressed in the context of this legislation.
Keywords (occurrence): automated (5) algorithm (1) show keywords in context
Description: Creates standards for independent bias auditing of automated employment decision tools.
Summary: The bill establishes standards for independent bias auditing of automated employment decision tools (AEDTs) in New Jersey, ensuring compliance with anti-discrimination laws and requiring transparency from employers about their use of AEDTs.
Collection: Legislation
Status date: March 18, 2024
Status: Introduced
Primary sponsor: Andrew Zwicker
(sole sponsor)
Last action: Introduced in the Senate, Referred to Senate Labor Committee (March 18, 2024)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (2) machine learning (1) automated (7) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
This legislation primarily impacts Social Impact as it addresses biases in employment decisions made by automated employment decision tools (AEDTs), which can affect the job opportunities of individuals. The legislation mandates independent bias auditing, which aims to ensure fairness and accountability in AI systems used in hiring, thus addressing potential discrimination and promoting equitable treatment. Given the specific mention of bias audits and compliance with anti-discrimination laws, this score is high. Data Governance is also highly relevant, as it involves ensuring that the data used by AEDTs is accurate and free from biases, as indicated by the legislation's requirements for audits based on historical and test data. System Integrity is moderately relevant since the legislation doesn’t explicitly mention system security, though the requirement for transparency aligns with core integrity concepts. Robustness is less relevant here as the focus of this bill is more on auditing and compliance rather than performance benchmarks for AI. Overall, the strongest connections are with Social Impact and Data Governance, which are crucial given that the bill directly relates to preventing bias in employment scenarios.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
The primary sectors impacted by this legislation include Private Enterprises, Labor, and Employment, as it concerns the use of AEDTs within workforce hiring practices, promoting fairness and accountability in employment decisions. The legislation requires employers to be transparent about their use of these tools and their assessment processes, directly impacting how businesses operate concerning employment. Government Agencies and Public Services may also be relevant to some extent, as the regulation could involve public sector employment entities, but is primarily targeted toward private employers. Judicial System is not significantly addressed as the text focuses on employment auditing rather than any legal adjudication process. The remaining sectors such as Politics and Elections, Healthcare, Academic and Research Institutions, and Nonprofits and NGOs are not directly applicable here as they don’t pertain to the scope of automated employment decisions. Thus, the most pertinent sector for this legislation is Private Enterprises, Labor, and Employment.
Keywords (occurrence): artificial intelligence (2) machine learning (1) automated (7) show keywords in context
Description: An Act relating to elections; relating to voters; relating to voting; relating to voter preregistration for minors at least 16 years of age; relating to voter registration; relating to the Alaska Public Offices Commission; relating to synthetic media in electioneering communications; relating to campaign signs; relating to public official financial disclosures; relating to the crime of unlawful interference with voting in the first degree; and providing for an effective date.
Summary: This bill addresses various aspects of election processes in Alaska, including voter registration, residency definitions, election administration, campaign contributions, and preventing election interference, aiming to enhance voting integrity and accessibility.
Collection: Legislation
Status date: Jan. 24, 2025
Status: Introduced
Primary sponsor: Rules
(sole sponsor)
Last action: REFERRED TO FINANCE (March 28, 2025)
Keywords (occurrence):
artificial intelligence (2)
synthetic media (7)
show keywords in context