4840 results:
Summary: The bill outlines security requirements for contractors handling classified information in international programs, focusing on risk assessments, implementation, monitoring, and disclosure procedures for sharing classified U.S. information with foreign governments.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register
The text primarily focuses on the security requirements related to classified information, particularly in the context of international agreements and the protecting of such information during transfers. It delves into procedures for handling classified data, compliance with federal laws regarding exports to foreign countries, and the security measures necessary to ensure that classified information remains protected. However, there is no explicit mention or implication of AI technologies, algorithms, or any of the related terms that would typically relate to the categories of Social Impact, Data Governance, System Integrity, or Robustness. Thus, all categories receive a score of 1 due to lack of relevance to the AI-specifications outlined in the assignment.
Sector: None (see reasoning)
The text addresses the security and regulatory measures concerning classified information systems, particularly with respect to international dealings and contractor obligations. Although it involves government operations and international standards, it does not specify the use or regulation of AI systems, neither does it address issues pertinent to the sectors provided. Thus, each sector receives a score of 1, indicating a complete lack of relevance to the specified sectors.
Keywords (occurrence): automated (1) show keywords in context
Summary: The bill reviews the Digital G.I. Bill program, aimed at modernizing outdated IT systems for veterans' claims processing, ensuring efficient service for veterans and preventing past failures.
Collection: Congressional Hearings
Status date: July 13, 2023
Status: Issued
Source: Congress
System Integrity (see reasoning)
The text focuses on the oversight and evaluation of the Digital G.I. Bill Program, which aims to modernize the technology used in processing G.I. Bill claims for veterans. While it mentions automation and the need for technological modernization, it lacks specific references to AI or related technologies such as algorithms or automated decision-making systems in the context of how they affect veterans or their services. The mention of automating claims processing hints at a relevance to AI, yet it does not explore these aspects deeply enough to merit high scores in the categories. Consequently, and due to the absence of explicit tie-ins to concepts such as fairness, bias in automated systems, data governance processes, or the robustness of AI systems, the reasoning leads to lower relevance scores across the categories.
Sector:
Government Agencies and Public Services (see reasoning)
The text is primarily about a technology modernization program aimed at improving the G.I. Bill, which may tangentially relate to the sectors of Government Agencies and Public Services due to its application in the area of veterans' services and education benefits processing. The automation and modernization of such systems can partially overlap with the use and regulation of AI in government operations, but there are no direct statements regarding AI’s impact on political campaigns, judicial systems, healthcare settings, or any other sectors mentioned. Thus, the relevance is limited largely to governmental contexts, warranting moderate relevance scores for related sectors.
Keywords (occurrence): machine learning (1) automated (7) chatbot (1) show keywords in context
Summary: The bill establishes interim guidelines for determining asbestos content in bulk insulation samples using polarized light microscopy, emphasizing safe disposal practices, public access control, and liability protection for landfill operators.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register
The text provided relates primarily to environmental regulations concerning asbestos rather than artificial intelligence. There are no mentions of AI, algorithms, or any related technology, so all four categories—Social Impact, Data Governance, System Integrity, and Robustness—are deemed not relevant. The text exclusively addresses methodology for asbestos testing, management of disposal sites, and laboratory procedures, with no connection to AI-related issues.
Sector: None (see reasoning)
The text centers around regulations pertaining to environmental health, particularly concerning asbestos, and does not address any AI applications in the nine defined sectors. The text does not discuss political campaigns, public services, the judicial system, healthcare, private enterprises, academic institutions, international standards, or nonprofits. Therefore, all sectors also receive the lowest score.
Keywords (occurrence): automated (1)
Summary: The bill establishes detailed certification, quality assurance, and quality control record provisions for emission monitoring systems, ensuring accurate reporting and compliance with environmental regulations. It aims to enhance accountability in emissions data handling.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register
Data Governance (see reasoning)
The text primarily concerns certification, quality assurance, and record-keeping requirements for emission and monitoring systems rather than the direct implications or societal aspects of AI. There’s no mention of AI technologies or their societal impact, suggesting limited relevance to the Social Impact category. The text does include detailed descriptions of standards and methodologies for monitoring emissions, indicating some relevance to data governance as it indirectly relates to data integrity and management in environmental monitoring; however, the absence of direct references to AI governance is notable. As for System Integrity, the procedures described ensure accuracy and compliance of monitoring systems, but there's no mention of AI-driven systems, thus only slightly relevant. The Robustness category is completely absent in this text as it makes no references to AI performance standards or benchmarks.
Sector: None (see reasoning)
The text does not directly reference political mechanisms, public service delivery, healthcare applications, or judicial implications of AI. The content appears primarily focused on environmental compliance and monitoring, which may affect sectors related to private enterprises engaged in emissions monitoring but does not tie specifically to the implications of AI in business practices. Therefore, relevance to the defined sectors is minimal across the board, mostly touching on Private Enterprises, Labor, and Employment, due to its mention of operational standards linked to industrial practices. However, the text does not provide enough specificity about AI in these domains.
Keywords (occurrence): algorithm (1) show keywords in context
Summary: The bill emphasizes the urgent need for legislation to establish safeguards against disinformation in elections, particularly due to the influence of AI, ahead of the 2024 elections.
Collection: Congressional Record
Status date: Nov. 9, 2023
Status: Issued
Source: Congress
Societal Impact
Data Governance (see reasoning)
The text discusses the implications of AI on elections, focusing on the risks of disinformation facilitated by AI technologies, which directly ties into the concerns related to Social Impact. It highlights the need for regulations and guardrails to protect democratic processes, emphasizing accountability and consumer protections against AI's influence. The aspects of safeguarding democracy align appropriately with preventing harmful impacts on society. Data Governance is moderately relevant, as there is an underlying theme of managing data integrity to prevent misuse in electoral contexts, although it doesn't explicitly tackle data management techniques. System Integrity and Robustness are mentioned indirectly through the need for security measures but are not central concerns in the text, leading to lower relevance scores for these categories.
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
The discussion centers on the influence of AI within the Politics and Elections sector, particularly highlighting the urgency of addressing AI-related disinformation during the upcoming elections. The text posits AI as a factor that necessitates regulatory frameworks to protect electoral integrity, making it directly relevant to this sector. Government Agencies and Public Services may connect due to the mention of bureaucratic responses and legislation, but it is not explicitly centered on government operations themselves. Other sectors such as Judicial System, Healthcare, Private Enterprises, Academic Institutions, International Cooperation, Nonprofits, and Hybrid sectors do not find substantial connections in the text, receiving lower scores overall.
Keywords (occurrence): artificial intelligence (1)
Summary: The bill addresses the significant fraud involving pandemic relief funds, emphasizing the need for innovative private sector strategies to recover approximately $200 billion in stolen taxpayer money.
Collection: Congressional Hearings
Status date: Sept. 27, 2023
Status: Issued
Source: House of Representatives
The text focuses on recouping stolen pandemic funds, particularly through the Small Business Administration (SBA). Although there are themes of accountability and fraud prevention, the text does not directly reference AI technologies or their implications within the legislative framework. Thus, it is primarily concerned with fraud, oversight, and financial integrity rather than the broader social, data governance, system integrity, or robustness issues associated with AI. Given that AI is not mentioned, the relevance to artificial intelligence legislation is low across all categories.
Sector: None (see reasoning)
The text primarily deals with the measures undertaken by the SBA and private sector solutions for fraud prevention and recovery of pandemic funds, without engaging directly with how AI may factor into these actions. While there are mentions of innovative solutions, these do not necessarily pertain to the use or regulation of AI technologies. Thus, all sectors score low as the text does not address themes specific to politics, public services, judiciary, healthcare, businesses, academic, international standards, or NGOs in relation to AI use. The focus remains on financial accountability rather than sector-specific applications of AI technologies.
Keywords (occurrence): artificial intelligence (1) show keywords in context
Summary: The bill outlines procedures for determining cycle-average engine fuel maps to ensure compliance with emission standards for vehicle manufacturers. It establishes testing protocols and parameters for fuel consumption measurement.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register
The text primarily discusses the testing, certification, and mapping of engine fuel consumption and emissions for vehicles, specifically related to regulations under the Environmental Protection Agency (EPA). It describes test provisions and methodologies for cycle-average fuel maps and emission standards compliance. Although the text references the GEM (Greenhouse Gas Emissions Model), it does not explicitly involve AI technologies, algorithms, or any related terms such as those identified in the AI portion of the task. Consequently, this text does not have a direct connection to AI concerns, leading to overall low relevance scores across all categories.
Sector: None (see reasoning)
The content is focused on fuel consumption and emissions within the automotive sector, specifically for compliance with EPA regulations. While it discusses operational methodologies for engine testing and vehicle configurations, it does not address the implications of AI in political contexts, government operations, healthcare, or any other specified sectors. The absence of references to AI in any industry context further reduces the relevance of this text to the pre-defined sectors.
Keywords (occurrence): automated (1)
Summary: The bill addresses the utilization of artificial intelligence (AI) within federal agencies, emphasizing its potential to improve operations while ensuring ethical use and compliance with existing laws and safeguards.
Collection: Congressional Hearings
Status date: Sept. 14, 2023
Status: Issued
Source: House of Representatives
Societal Impact
Data Governance
System Integrity (see reasoning)
The text discusses the use of AI by federal agencies, emphasizing its potential impact on society and government efficiency. This suggests a significant focus on Social Impact due to the mention of how AI can enhance services, potentially saving costs and improving service delivery. Additionally, concerns regarding bias and privacy rights position it as highly relevant to Data Governance as well. System Integrity is moderately relevant due to the implied need for transparency and accountability in AI usage, and Robustness is slightly relevant since it does not explicitly discuss benchmarks or performance metrics for AI systems.
Sector:
Government Agencies and Public Services
Judicial system
Private Enterprises, Labor, and Employment (see reasoning)
The text focuses on the application of AI specifically within the context of federal agencies and government operations, leading to its strong relevance to the Government Agencies and Public Services sector. The discussions around AI's impact on jobs and federal employee roles indirectly relate to Private Enterprises, Labor, and Employment, albeit less directly. The mention of misuse of AI and bias also has implications for the Judicial System due to algorithmic bias concerns. Other sectors like Politics and Elections, Healthcare, Academic and Research Institutions, Nonprofits and NGOs, International Cooperation and Standards, and Hybrid, Emerging, and Unclassified receive low relevance as they are not explicitly addressed.
Keywords (occurrence): artificial intelligence (15) machine learning (4) automated (1) chatbot (1) algorithm (1) autonomous vehicle (1) show keywords in context
Summary: This bill establishes standards and management practices for facilities using materials that emit hazardous air pollutants (MFHAP) during operations like abrasive blasting, welding, and spray painting, ensuring compliance with environmental regulations.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register
The text primarily discusses compliance standards and management practices for operations involving materials that contain or emit hazardous air pollutants (MFHAP). None of the language within the text references Artificial Intelligence (AI) or any of its related terminologies like machine learning, algorithms, automated systems, etc. Therefore, as the text does not pertain to AI, all categories related to AI legislation are irrelevant. There is no mention of AI's impact on society, data governance issues connected with AI, concerns regarding system integrity related to AI, or robustness in AI performance. Consequently, all scores for the categories will be 1.
Sector: None (see reasoning)
The text focuses on standards related to operating equipment for controlling emissions associated with certain industrial processes and does not mention any application or regulation of AI in any sectors specified. There is no reference to AI's involvement in politics, government operations, healthcare contexts, or any other sectors outlined. Therefore, it receives the lowest possible score across all sectors.
Keywords (occurrence): automated (1) show keywords in context
Summary: The bill addresses oversight of the U.S. Patent and Trademark Office (USPTO), seeking reforms to enhance patent reliability and prevent duplicative legal challenges. It aims to foster innovation and protect inventors' rights.
Collection: Congressional Hearings
Status date: July 26, 2023
Status: Issued
Source: Senate
Societal Impact
Data Governance (see reasoning)
The text outlines various aspects of oversight by the USPTO including its role in patenting processes and the implications of patent laws on technologies such as AI. The text highlights the challenges surrounding patent eligibility for technologies like artificial intelligence, emphasizing that current laws prevent certain critical technologies from being patented. This underscores the relevance to both the Social Impact and Data Governance categories as it addresses how laws surrounding IP intersect with societal innovation and data ethics. The mention of AI in obtaining patent protections establishes a direct connection. However, it doesn't heavily focus on the security or performance aspects typical of System Integrity and Robustness, so those categories receive lower scores.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment
Academic and Research Institutions (see reasoning)
The text directly mentions AI's relevance in patent law and legislative discussions surrounding innovation in the tech sector, which is important for Private Enterprises, Labor, and Employment. It also pertains to the Academic and Research Institutions sector as it discusses the implications of patent laws on innovation. The regulatory aspects and the importance of IP protection for businesses also tie it back to Government Agencies and Public Services. However, while the significance of AI in these contexts is recognized, there’s limited direct engagement with sectors like Healthcare or the Judicial System, thus scoring those sectors lower.
Keywords (occurrence): artificial intelligence (2) show keywords in context
Description: Enacts the "advanced artificial intelligence licensing act"; providing for regulation of advanced artificial intelligence systems (Part A); requiring registration and licensing of high-risk advanced artificial intelligence systems and related provisions regarding the operation of such systems (Part B); establishing the advanced artificial intelligence ethical code of conduct (Part C); and prohibiting the development and operation of certain artificial intelligence systems (Part D).
Summary: The "Advanced Artificial Intelligence Licensing Act" establishes a regulatory framework in New York for high-risk AI systems, requiring their registration and licensing, and outlining ethical conduct and operational standards.
Collection: Legislation
Status date: Oct. 27, 2023
Status: Introduced
Primary sponsor: Clyde Vanel
(4 total sponsors)
Last action: referred to science and technology (Jan. 3, 2024)
Societal Impact
Data Governance
System Integrity (see reasoning)
This legislation is highly relevant to the Social Impact category because it addresses the potential societal benefits and risks associated with advanced artificial intelligence systems, emphasizing the need for ethical conduct, public safety, and the management of high-risk AI technologies. The proposed licensing and regulatory framework aims to protect individuals and society from the risks posed by these systems, highlighting concerns about harm to psychological and physical well-being, the environment, and social equity. Data Governance is also extremely relevant, as the act entails registering and licensing advanced AI systems, ensuring bureaucratic oversight, and detailing the management of sensitive data associated with these technologies. System Integrity scores high relevance, as it regulates the use, control, and prohibited activities surrounding AI systems, advocating for transparency and safeguards to prevent harm. Robustness, while implicitly important, is less emphasized as the act does not directly focus on performance benchmarks or auditing but rather on regulatory compliance and ethical standards; therefore, it receives a lower relevance score.
Sector:
Government Agencies and Public Services
Healthcare
Private Enterprises, Labor, and Employment (see reasoning)
The act has clear relevance to several sectors, particularly in Government Agencies and Public Services, as it aims to regulate how these built systems interact with public safety and support government functions. The act also applies to Healthcare due to its specific mention of AI's role in managing critical healthcare systems, which can have direct implications for patient safety and data handling. The Private Enterprises, Labor, and Employment sector is relevant as well because the licensing process affects businesses developing or using advanced AI systems, guiding ethical labor practices and competition in AI innovation. Although it discusses AI's impact on the public and various industries, the other sectors like Judicial System, Politics and Elections, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, and Hybrid, Emerging, and Unclassified sectors are less directly addressed, resulting in lower relevance scores.
Keywords (occurrence): artificial intelligence (53) show keywords in context
Summary: The bill establishes safety protocols for electronic hardware and software in trainsets, requiring rigorous testing, maintenance, and preservation of data for accident analysis to enhance overall rail safety.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register
Data Governance
System Integrity (see reasoning)
The text addresses safety-critical electronic control systems, which may incorporate AI technologies for monitoring and control in trainsets. However, the document largely focuses on hardware and software safety protocols, certifications, and data preservation related to safety systems in trainsets rather than explicitly discussing AI implications. The relevance to social impact, data governance, system integrity, and robustness appear tangential, as the main emphasis is on safety and operational standards for trainsets without a direct link to AI principles or societal impacts of AI applications. Thus, it lacks significant relevance to the specified AI categories.
Sector:
Government Agencies and Public Services
Hybrid, Emerging, and Unclassified (see reasoning)
The content discusses the use and regulation of safety-critical electronic control systems in trainsets, which could intersect with government operations in public transportation. However, the text does not delve into specific applications or implications of AI technology but rather outlines compliance and procedural requirements for ensuring safety in trainset operations. The primary sectors affected include government agencies involved in transportation safety, though it lacks specificity in terms of how AI is directly involved in legislative measures related to these topics.
Keywords (occurrence): automated (3) show keywords in context
Description: To regulate law enforcement use of facial recognition technology, and for other purposes.
Summary: The Facial Recognition Act of 2023 regulates law enforcement's use of facial recognition technology, requiring court approval and imposing penalties for non-compliance to protect civil liberties and privacy rights.
Collection: Legislation
Status date: Oct. 26, 2023
Status: Introduced
Primary sponsor: Ted Lieu
(6 total sponsors)
Last action: Referred to the Committee on the Judiciary, and in addition to the Committee on Science, Space, and Technology, for a period to be subsequently determined by the Speaker, in each case for consideration of such provisions as fall within the jurisdiction of the committee concerned. (Oct. 26, 2023)
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The bill explicitly addresses the use of facial recognition technology, which is a subset of AI. This directly pertains to Social Impact because it explores the societal implications of such technologies, including potential invasions of privacy. It also relates to Data Governance as it covers the handling of arrest photo databases and guidelines for data accuracy and access. It speaks to System Integrity through mandates around the oversight of law enforcement applications of facial recognition, including procedural safeguards. Finally, it touches on Robustness by discussing operational testing and metrics to ensure accuracy and reduce errors with facial recognition systems.
Sector:
Government Agencies and Public Services
Judicial system (see reasoning)
Facial recognition technology is increasingly crucial in various sectors, especially related to Government Agencies and Public Services, where policing and public safety are concerned. By regulating the use of facial recognition technology in law enforcement, this bill likely impacts the Judicial System as well through its implications on how evidence is collected and used in legal contexts. While it indirectly connects to other sectors, the primary focus strongly aligns with law enforcement and governmental oversight.
Keywords (occurrence): automated (2) algorithm (1) show keywords in context
Summary: The bill, known as the National Defense Authorization Act for Fiscal Year 2024, authorizes appropriations for military activities, construction, and establishes personnel strengths for the upcoming fiscal year. Its aim is to ensure funding and support for defense initiatives.
Collection: Congressional Record
Status date: Dec. 6, 2023
Status: Issued
Source: Congress
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text primarily discusses the National Defense Authorization Act for Fiscal Year 2024, focusing on various aspects of military funding, personnel authorization, and procurement. There are explicit mentions of AI related to military systems, particularly in sections discussing the use of AI for shipyard optimization and automation in logistics. These references suggest that while the text is heavily geared toward defense authorizations, it includes significant implications for the development and use of AI technologies in military contexts, linking directly to considerations around AI’s social impact, data governance, system integrity, and robustness. The connections to system integrity are particularly pertinent to oversee AI systems used in military applications and ensure their transparency and security, while robustness relates to the performance standards expected from military AI systems. Therefore, several categories can be determined to be relevant based on these indications.
Sector:
Government Agencies and Public Services
International Cooperation and Standards (see reasoning)
The text discusses various aspects of military operations, specifically the use and regulation of AI in military applications, such as logistics optimization. These applications are significant in shaping how AI technologies are integrated within defense frameworks, impacting national security. Thus, sectors like Government Agencies and Public Services are highly relevant as the legislation addresses how military and defense agencies harness AI technologies. There's also relevance to International Cooperation and Standards due to the implications of military AI on international relations and security measures. However, direct implications for sectors such as Healthcare or the Judicial System are not present in this text. Overall, the focus is predominantly on military operations and how AI technologies are utilized within this framework.
Keywords (occurrence): artificial intelligence (188) machine learning (26) automated (43) algorithm (3) show keywords in context
Description: An act to amend Sections 22677 and 22945 of, and to add and repeal Sections 22945.7 and 22945.9 of, the Business and Professions Code, relating to social media platforms.
Summary: Assembly Bill 1027 mandates social media platforms to establish and publicize policies regarding controlled substance distribution, including data reporting to the Attorney General, aimed at enhancing drug safety practices online through stricter oversight.
Collection: Legislation
Status date: Oct. 13, 2023
Status: Passed
Primary sponsor: Cottie Petrie-Norris
(sole sponsor)
Last action: Chaptered by Secretary of State - Chapter 824, Statutes of 2023. (Oct. 13, 2023)
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text primarily concerns the regulation of social media platforms regarding the distribution of controlled substances and their accountability to consumers and regulatory bodies. AI is relevant to this context as the legislation mandates social media companies to describe how their automated content moderation systems operate, including how these systems identify and enforce terms of service violations. Therefore, the Social Impact and Data Governance categories are applicable due to user protection and data rights concerns, while System Integrity and Robustness are also relevant because they pertain to the enforcement of policies and the standards by which AI operates and audits these systems.
Sector:
Government Agencies and Public Services
Judicial system (see reasoning)
The legislation applies directly to Government Agencies and Public Services, particularly concerning the reporting obligations to the Attorney General and addressing the responsibilities of social media platforms. Given the broad implications of social media regulation on public health and safety, as well as potential concerns in the Judicial System regarding privacy and legal enforcement, the text is slightly relevant to these categories. However, other sectors such as Healthcare and Private Enterprises may also be indirectly related through the implications of health communication and the operation of businesses on social media.
Keywords (occurrence): artificial intelligence (2) automated (1) show keywords in context
Description: To improve technology and address human factors in aviation safety, and for other purposes.
Summary: The Safe Landings Act aims to enhance aviation safety by improving technology, addressing human factors, and implementing National Transportation Safety Board recommendations to minimize runway incidents and improve training protocols.
Collection: Legislation
Status date: Dec. 19, 2023
Status: Introduced
Primary sponsor: Mark DeSaulnier
(3 total sponsors)
Last action: Referred to the Subcommittee on Aviation. (Jan. 2, 2024)
System Integrity
Data Robustness (see reasoning)
The Safe Landings Act relates to AI primarily through its focus on improving aviation safety via technology enhancements. It discusses the use of algorithms and machine learning for analyzing aviation communication and incident data, thereby addressing points relevant to System Integrity and Robustness. The emphasis on human factors in conjunction with automated systems suggests an integration of AI that is crucial for aviation safety, particularly in operational settings where human oversight is necessary. However, it doesn't specifically address consumer protections, bias considerations, or broader societal impacts, limiting its relevance to Social Impact. Data governance concerns such as data management and protection are not deeply explored, resulting in lower relevance for that category.
Sector:
Government Agencies and Public Services
Academic and Research Institutions (see reasoning)
The text explicitly mentions the application of AI and machine learning in analyzing aviation safety data, which ties directly into technological advancements within the aviation sector. It reflects a significant focus on improving operations through better data analysis and human-computer integration. The bill does not clearly address the regulatory or operational use of AI in political contexts or frameworks governed by judicial standards, hence lower scores for those sectors. Its focus on safety and operational improvements in aviation positions it well within the Government Agencies and Public Services sector, but less so in others.
Keywords (occurrence): artificial intelligence (1) machine learning (1) automated (5) show keywords in context
Summary: Executive Order 14081 aims to enhance the U.S. bioeconomy by promoting biotechnology and biomanufacturing innovation, ensuring ethical practices, safety, and equity while boosting economic competitiveness and addressing health and environmental challenges.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register
Societal Impact
Data Governance
System Integrity (see reasoning)
The text primarily focuses on advancing biotechnology and biomanufacturing innovations. It mentions the integration of artificial intelligence as a tool to unlock biological data, indicating a moderate but specific focus on AI's role within the broader context of these initiatives. The references to enhance R&D, engage in responsible utilization, and secure biotechnological advancements imply considerations that could impact society (social aspects) and the governance of data involved (data aspects). Therefore, while the main emphasis is on biotechnology, there is a clear intersection with both Social Impact and Data Governance categories due to the societal implications, ethical standards proposed, and data management expectations outlined in the initiatives.
Sector:
Healthcare
Academic and Research Institutions
International Cooperation and Standards (see reasoning)
The Executive Order touches on multiple sectors, prominently highlighting health and agriculture. While it doesn't directly address government agencies or judicial systems, its implications for enhancing public health through advancements in biotechnology and biomanufacturing place it significantly within the Healthcare sector. The reference to securing the bioeconomy indirectly suggests relevance to International Cooperation as it encompasses global practices and security measures. Nevertheless, the other sectors show weaker connections or are only tangentially referenced, leading to moderate scores in relevant sectors such as Healthcare and International Cooperation.
Keywords (occurrence): artificial intelligence (2) machine learning (1) show keywords in context
Description: A BILL to be entitled an Act to amend Code Section 16-6-13 of the Official Code of Georgia Annotated, relating to penalties for violating Code Sections 16-6-9 through 16-6-12, so as to increase the penalty provisions relating to pimping and pandering; to provide for a definition; to provide for related matters; to repeal conflicting laws; and for other purposes.
Summary: The bill, titled "Colton-McNeill Act," increases penalties for crimes such as cruelty to children and pimping, updates definitions related to incest, and prohibits distributing AI-generated obscene material depicting minors.
Collection: Legislation
Status date: Feb. 7, 2023
Status: Engrossed
Primary sponsor: Randy Robertson
(20 total sponsors)
Last action: House Passed/Adopted By Substitute (March 28, 2024)
Societal Impact
Data Governance
System Integrity (see reasoning)
The AI-related portions of this text primarily discuss the definition of 'Artificial Intelligence system' and a specific crime involving the distribution of computer-generated obscene material depicting a child. This indicates a legislative concern about how AI technology can be used to produce harmful and illegal content, particularly in relation to children, which suggests significant societal implications. This relates closely to the Social Impact category due to concerns about safety and potential harm resulting from AI-generated content. The Data Governance category is relevant because it hints at the challenges of managing information and ensuring safety in digital content involving AI. System Integrity is somewhat relevant due to the necessity of ensuring that AI technology is used responsibly and not for illegal activities, and Robustness appears less relevant because the primary focus isn't on performance benchmarks or compliance standards for AI systems. Overall, the strongest connections are with Social Impact and Data Governance.
Sector:
Government Agencies and Public Services
Judicial system (see reasoning)
The text relates to potential applications and implications of AI in the criminal justice system, especially with respect to crimes involving minors and the regulation of obscene materials produced through AI. However, it lacks direct references to sectors like Politics and Elections, Healthcare, or Private Enterprises. Its most apparent connection is with the Judicial System, in terms of defining new legal standards concerning AI technology's role in producing harmful content, thus warranting a higher score. The Government Agencies and Public Services sector is of moderate relevance due to the consideration of law enforcement and their responses to crimes involving AI-generated materials. The other sectors (Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, and Hybrid, Emerging, and Unclassified) hold minimal to no relevance based solely on the text provided.
Keywords (occurrence): artificial intelligence (2) show keywords in context
Summary: The bill delegates authority to the Office of Management and Budget (OMB) and other federal agencies to review and approve information collection requests, while ensuring compliance with statutory standards and public participation in the process.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register
The text primarily addresses the mechanisms for information collection and review processes by federal agencies, supervised by the Office of Management and Budget (OMB). While it discusses procedural aspects of information collection, there is no explicit reference to AI-related topics such as automated decision-making, algorithms, or any of the specific AI technologies mentioned in the keywords. Given the lack of direct relevance to AI, the assessment concludes that this text does not fit well into any of the categories focused on AI impact or regulation.
Sector: None (see reasoning)
The legislation discusses the roles and responsibilities of OMB and certain federal agencies concerning information collection processes. While it touches on the need for public comment and some operational guidelines relevant to federal responsibilities, it does not specifically address any of the sectors listed such as AI in healthcare, government services, or academic institutions. The relevance to the sectors is minimal, as it doesn't focus on the legislative impact of AI or its applications in any particular sector context.
Keywords (occurrence): automated (1) show keywords in context
Summary: The Encryption Commodities, Software, and Technology (ENC) bill establishes guidelines for the export, reexport, and transfer of encryption-related items while restricting certain transactions with specific countries to enhance national security.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register
System Integrity (see reasoning)
The text primarily outlines regulations related to the export, reexport, and transfer of encryption commodities, software, and technology. While these regulations impact the integrity and security of data within AI systems due to the encryption aspect, the text does not explicitly address AI-related legislation's societal impacts, data governance practices, the integrity of AI systems in terms of oversight, or benchmarks for AI performance. As such, while some connections can be drawn with the System Integrity category due to the focus on security, overall relevance to Social Impact, Data Governance, and Robustness remains limited.
Sector:
Government Agencies and Public Services
International Cooperation and Standards (see reasoning)
The text discusses regulations concerning encryption and its implications for commodities and technology transfer, which could have indirect relevance to sectors like Government Agencies and Public Services due to potential applications of encrypted technology in such settings. However, there are limited references to how these regulations impact specific sectors such as Healthcare, Education, or Labor. The primary focus remains on the technicalities of export regulations rather than application within specified sectors. Therefore, while it has some relevance, it is overall quite limited.
Keywords (occurrence): automated (6) algorithm (1) show keywords in context