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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.

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5015 results:


Virginia HB2554: Artificial Intelligence Transparency Act; established.

Description: Artificial Intelligence Transparency Act established. Requires developers of generative artificial intelligence systems made available in the Commonwealth to ensure that any generative artificial intelligence system that produces audio, images, text, or video content includes on such AI-generated content a clear and conspicuous disclosure that meets certain requirements specified in the bill. The bill also requires developers of generative artificial intelligence systems to implement reasonab...
Summary: The Artificial Intelligence Transparency Act mandates transparency in AI-related consumer transactions in Virginia, prohibiting fraudulent practices and misrepresentations by suppliers to protect consumers.
Collection: Legislation
Status date: Jan. 11, 2025
Status: Introduced
Primary sponsor: Rozia Henson (sole sponsor)
Last action: Left in Communications, Technology and Innovation (Feb. 4, 2025)

Category:
Societal Impact
Data Governance (see reasoning)

The AI-related portions of the text explicitly discuss the requirement for developers of generative AI systems to ensure transparency and accountability by clearly disclosing when content is generated by AI. This addresses issues of consumer protection and the potential for misinformation, which directly relates to societal impacts of AI. The legislation also implies accountability for outputs of AI systems, which further aligns with challenges pertaining to social trust and the influence of AI-generated content on public discourse. Therefore, the Social Impact category is rated as very relevant. The text also emphasizes the importance of accurate disclosures and could relate to data governance indirectly, but mainly focuses on societal implications rather than on the secure management of data itself. System Integrity and Robustness are less emphasized, as the text does not delve into security measures, human oversight, or performance benchmarks; therefore both categories score lower.


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

The text primarily addresses the implications of generative AI in terms of consumer protection and misinformation which could be relevant across several sectors. Politics and Elections is not applicable since there's no mention of AI use in elections. However, Government Agencies and Public Services and Healthcare may be affected indirectly, but not directly considered. The impact of AI on Private Enterprises could also be noted due to implications on commercial practices. Academic and Research Institutions might be considered because of the transparency needed in AI, but the text focuses more on commercial than educational aspects. These non-direct references do not strongly emphasize their relevance in the context of the legislation.


Keywords (occurrence): artificial intelligence (25) foundation model (1) chatbot (2) show keywords in context

Maryland SB949: Vehicle Laws - Fully Autonomous Vehicles

Description: Establishing certain standards and requirements for the operation of fully autonomous vehicles on highways in the State; requiring, before operating a fully autonomous vehicle on a highway in the State, a person to submit a law enforcement interaction plan to the Motor Vehicle Administration; and establishing that a State agency or local political subdivision may not prohibit the operation of fully autonomous vehicles on highways under their jurisdiction.
Summary: Senate Bill 949 establishes regulations for fully autonomous vehicles in Maryland, ensuring safety standards, operational guidelines, and prohibiting local bans on their highway operation by October 1, 2025.
Collection: Legislation
Status date: Feb. 3, 2025
Status: Introduced
Primary sponsor: Sara Love (7 total sponsors)
Last action: Hearing 3/05 at 1:00 p.m. (Feb. 4, 2025)

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

The text explicitly addresses the operation, standards, and requirements for fully autonomous vehicles, which falls within the purview of all four categories. In terms of Social Impact, it discusses the implications of automated driving systems on roadway safety and public policy without a human driver, which is very relevant. For Data Governance, while it discusses interaction plans and compliance factors, it is less focused on data management, albeit there are elements that could relate to data security practices. Regarding System Integrity, mandates for operational control and failure protocols suggest strong relevance to the integrity and safety of AI systems operating vehicles. Lastly, in terms of Robustness, the emphasis on certification and safety standards connects it greatly to ensuring the robustness of AI technologies in real-world applications.


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

The text pertains to the sector of Government Agencies and Public Services since it regulates the use of AI in autonomous vehicles which will be managed and overseen by state governmental authorities. The regulation has a significant impact on public safety and transport policies establishing how these vehicles are integrated into society. It is also relevant to the sector of Private Enterprises, Labor, and Employment, as it impacts companies operating transportation networks that may utilize autonomous vehicles, yet less prominent in other sectors like Politics and Elections or Healthcare. The text does not specifically address judicial systems or academic research institutions, making it less relevant to those sectors.


Keywords (occurrence): automated (9) autonomous vehicle (15)

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