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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.

Clear All

5017 results:


U.S. Military Posture and National Security Challenges in North and South America

Summary: The bill addresses U.S. military posture and national security challenges in North and South America, focusing on countering adversarial influences from China, Russia, and criminal organizations, while enhancing regional partnerships and defense readiness.
Collection: Congressional Hearings
Status date: March 8, 2023
Status: Issued
Source: House of Representatives

Category: None (see reasoning)

The document focuses primarily on military posture and national security challenges, with little explicit mention of artificial intelligence or the concepts related to automation, algorithms, or machine learning. Although there are references to cyber threats and advanced technologies, these are mentioned in the broader context of military strategy rather than specific applications or governance of AI. As such, the legislation's relevance to the categories is minimal.


Sector: None (see reasoning)

The text discusses U.S. military and national security strategies, which could tangentially relate to Government Agencies and Public Services in the context of the military's role in domestic stability and security. However, there is no direct mention of AI within these sectors either. The other sectors—such as Healthcare, Judicial System, or Private Enterprises—have no relevance as they are not addressed within the scope of military or national security. Therefore, even if some themes overlap, the document remains largely outside the specific contexts of regulation and legislation pertaining to AI in these sectors.


Keywords (occurrence): artificial intelligence (3) machine learning (3) automated (2) show keywords in context

Procedures-overseas credit unions.

Summary: The bill establishes procedures for overseas credit unions operating on Department of Defense installations, outlining requirements for service provision, staffing, logistical support, and compliance with host-country laws. It aims to enhance access to financial services for military personnel stationed abroad.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text does not address artificial intelligence or related technologies directly or indirectly. The primary focus is on the procedures and regulations governing credit unions, particularly in overseas settings. Since there are no mentions of AI, algorithms, or any related concepts, all categories would receive a score of 1 for not being relevant at all.


Sector: None (see reasoning)

The text primarily deals with credit unions and their operational procedures within the military context, without reference to the use of AI in any sector described. Consequently, none of the sectors are applicable as AI is not mentioned or implied within the text, leading to a uniform score of 1 for all sectors.


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

PUBLIC BILLS AND RESOLUTIONS

Summary: The bill includes various public resolutions addressing issues like slavery remembrance, amending tax codes, education, defense, and anti-racism initiatives, aiming to advance social justice and improve public services.
Collection: Congressional Record
Status date: Aug. 18, 2023
Status: Issued
Source: Congress

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

In the given text, there is a mention of legislation that directs the Secretary of Defense to utilize machine learning and artificial intelligence algorithms for calculating housing rates. This indicates a clear relevance to the categories of Social Impact and System Integrity, primarily due to the implications of machine learning (ML) in governance and the potential concerns regarding accuracy and fairness in such automated decisions. However, the text lacks comprehensive discussions on ethical issues, bias, or broader societal consequences that would typically warrant a high score in Social Impact. Data Governance is relevant due to the mention of using 'algorithms,' though there is no detailed discussion on data ethics, integrity, or privacy concerns. Robustness is less applicable as there is no explicit reference to AI performance benchmarks or systematic auditing processes mentioned in the text. Overall, the AI-related content highlighted in the text warrants consideration across a few relevant categories rather than extensive involvement in all.


Sector:
Government Agencies and Public Services (see reasoning)

The text describes several legislative bills, but only one specifically refers to the use of AI in a government context (H.R. 5230 regarding the Department of Defense). This suggests relevance to the Government Agencies and Public Services sector, showing how AI is used in governmental operations. Other sectors, such as Healthcare, Private Enterprises, or others, are not mentioned at all, making them irrelevant to this text. The legislative focus on defense-related applications suggests moderate relevance regarding the Government sector, but not enough to categorize it under Politics and Elections or other sectors. The nature of the contents correlates more closely with government use rather than any other sector, which leads to a moderately high score in that aspect.


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

Text of Senate Amendment 829

Summary: Senate Amendment 829 mandates Federal financial regulators to report on artificial intelligence use and governance, establishes a bug bounty program for the Department of Defense's AI, and requires vulnerability studies for military AI applications.
Collection: Congressional Record
Status date: July 18, 2023
Status: Issued
Source: Congress

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

The text pertains directly to the regulation and development of Artificial Intelligence (AI) specifically in the context of military and financial services industries. It discusses the need for reports and studies examining the impact of AI, its governance, and security implications in military applications. Therefore, the legislation is very relevant to the Social Impact category as it addresses potential risks that AI poses to privacy, security, and the overall integrity of military operations and governance in financial services. The Data Governance category is also very relevant as it involves ensuring data sharing and management practices that support effective AI applications. The System Integrity category scores highly as there are mandates for oversight and analysis on vulnerabilities in AI systems, indicating a focus on the security and transparency of AI implementations. Robustness is relevant as the text mentions ongoing assessments and studies related to the capabilities and standards required for AI in military contexts. Overall, the text covers important aspects of all four categories, but especially emphasizes the governance and impact of AI on society and data management.


Sector:
Government Agencies and Public Services
Judicial system
Hybrid, Emerging, and Unclassified (see reasoning)

The text has a clear focus on the application of AI in government operations, particularly regarding the Department of Defense and financial regulatory agencies. It is relevant to the Government Agencies and Public Services sector because it involves implementing AI in government functions and oversight. The text implies potential impacts on the Judicial System due to financial regulations related to AI, but it is not as direct or profound, resulting in a moderate relevance. Regarding the Healthcare sector, there are no references or implications related to AI in healthcare settings, leading to a score of 1 for that sector. The Private Enterprises, Labor, and Employment sector is somewhat relevant as it mentions the financial services industry but does not expand on employment issues directly related to AI. Therefore, it doesn't score highly in that context. There is no mention of Academic and Research Institutions specifically, nor any information on International Cooperation and Standards, which justifies scores of 1 for both those sectors as well. Lastly, the sector of Hybrid, Emerging, and Unclassified may apply since the overarching theme of AI integration into diverse government functions contains elements of innovation and evolving regulatory frameworks.


Keywords (occurrence): artificial intelligence (30) show keywords in context

United States HB1718: AI for National Security Act

Description: To make certain improvements to the enterprise-wide procurement of cyber data products and services by the Department of Defense, and for other purposes.
Summary: The AI for National Security Act aims to enhance the Department of Defense's procurement of cyber data products and services, focusing on AI-based security measures and software supply chain protection.
Collection: Legislation
Status date: March 22, 2023
Status: Introduced
Primary sponsor: Jay Obernolte (3 total sponsors)
Last action: Referred to the House Committee on Armed Services. (March 22, 2023)

Category:
System Integrity
Data Robustness (see reasoning)

The relevance of the AI for National Security Act primarily lies in its emphasis on artificial intelligence-based solutions for cybersecurity, specifically within the procurement of cyber data products and services. This points to a direct interaction with AI applications aimed at improving national security. While there are implications for how this impacts society and governance, the focus is more on security and procurement rather than broader societal impacts or data governance intricacies. Thus the relevance to robustness and system integrity can be asserted due to the need for secure AI systems, whereas social impact and data governance are less pertinent as the legislation does not primarily assess societal or data management issues arising from AI.


Sector:
Government Agencies and Public Services (see reasoning)

The AI for National Security Act pertains to the defense sector, particularly in the use of AI technologies by the Department of Defense to enhance national security measures. The bill directly mentions artificial intelligence in terms of endpoint security and enhancing software supply chain security, which ties closely with the government agencies' use of AI to secure their operations. Considering the military and defense application of AI, the relevance to government agencies and public services is notably high, while other sectors such as healthcare, the judicial system, and nonprofits do not have direct relevance in this context.


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

Federal Pandemic Spending: A Prescription for Waste, Fraud and Abuse

Summary: The bill addresses oversight of federal pandemic spending, focusing on exposing and preventing waste, fraud, and abuse in relief programs established during COVID-19, notably the CARES Act.
Collection: Congressional Hearings
Status date: Feb. 1, 2023
Status: Issued
Source: House of Representatives

Category: None (see reasoning)

The text focuses on pandemic spending oversight, fraud, and waste, but contains no references to AI or related concepts. While the oversight and accountability aspects could have connections to data governance in terms of managing data and ensuring accurate use of funds, there is no explicit mention of AI systems or their management, hence the relevance to AI-related categories is low.


Sector:
Government Agencies and Public Services (see reasoning)

The text discusses federal pandemic spending, oversight procedures, and efforts to prevent fraud. There is a focus on government accountability which might lightly align with traditional government operations, but not explicitly with the other sectors like healthcare or judicial systems. Consequently, its focus largely falls under government agencies, but the connection isn't robust.


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

Uniform Test Method for Measuring the Energy Consumption of Refrigerators, Refrigerator-Freezers, and Miscellaneous Refrigeration Products

Summary: The bill establishes a uniform test method for measuring energy consumption and volume of refrigerators and similar appliances, aiming to standardize regulations and ensure compliance with energy conservation standards.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The document primarily discusses testing methods for measuring energy consumption of refrigeration products and does not have any explicit references or implications regarding artificial intelligence (AI) or related technologies. Therefore, it does not fit well within the categories focusing on the social impact, data governance, system integrity, or robustness of AI systems.


Sector: None (see reasoning)

The text does not address AI applications in any specific sectors like politics, government, healthcare, or private enterprises. It solely pertains to energy consumption measurement for refrigeration products, which is outside the scope of AI-related sectors.


Keywords (occurrence): algorithm (6) show keywords in context

Department of the Interior, Environment, and Related Agencies Appropriations for 2024

Summary: The bill allocates appropriations for the Department of the Interior, Environment, and related agencies for fiscal year 2024, addressing budget requests for various environmental and conservation initiatives.
Collection: Congressional Hearings
Status date: March 23, 2023
Status: Issued
Source: House of Representatives

Category: None (see reasoning)

The text does not explicitly mention any AI-related concepts or technologies. It focuses on appropriations for the Department of the Interior and environmental conservation efforts, which are important but do not appear to involve Artificial Intelligence or related technologies. As such, it lacks direct relevance to any of the established categories concerning AI legislation.


Sector: None (see reasoning)

The text centers around budget hearings and appropriations for government agencies rather than the application or regulation of AI across different sectors. The discussions involve environmental issues, conservation, and the operation of government services but do not address AI within any of the listed sectors, indicating a lack of relevance.


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

Exploitation and Enforcement: Evaluating the Department of Homeland Security's Efforts to Counter Uyghur Forced Labor

Summary: This bill assesses the Department of Homeland Security's efforts to enforce the Uyghur Forced Labor Prevention Act, aiming to prevent goods made with forced labor in Xinjiang from entering the U.S. market.
Collection: Congressional Hearings
Status date: Oct. 19, 2023
Status: Issued
Source: House of Representatives

Category: None (see reasoning)

The text primarily discusses the enforcement of the Uyghur Forced Labor Prevention Act (UFLPA) by the Department of Homeland Security, which ties to a number of critical issues, particularly around social implications and system integrity. However, there is no mention of AI or any associated technologies, which would fall under the categories of Social Impact, Data Governance, System Integrity, or Robustness associated with AI specifically. The focus is on legislative oversight and human rights, rather than algorithmic processes or AI applications that could be governed or regulated. Therefore, the relevance of AI-related categories is minimal.


Sector: None (see reasoning)

The text revolves around the government's approach to combat forced labor, particularly concerning Uyghur rights and enforcement measures associated with that legislation. Despite its significant social implications, it does not significantly address or regulate the use of AI in any sector. Thus, while it has sociopolitical implications, its relevance to specific sectors is absent as the text fails to mention or correlate with issues directly related to the legislative functions in the mentioned sectors. The discussion is unanchored from AI applications, making its relevance to these sectors negligible.


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

STATEMENTS ON INTRODUCED BILLS AND JOINT RESOLUTIONS

Summary: The "Investing in Tomorrow's Workforce Act of 2023" aims to enhance training initiatives for workers at risk of job loss due to automation, promoting workforce adaptability and economic growth.
Collection: Congressional Record
Status date: Sept. 5, 2023
Status: Issued
Source: Congress

Category:
Societal Impact
Data Governance (see reasoning)

The text addresses the impacts of automation on the workforce, particularly emphasizing the need for training workers whose jobs may be affected. The legislation seeks grants to improve training for dislocated workers due to automation. This places it primarily within the realm of 'Social Impact' due to its focus on the effects of technology on employment and economic well-being. It is also relevant to 'Data Governance' in the context of ensuring trainings may require the use of data for identifying skill gaps, though this is only implied. For 'System Integrity', while there may be implications concerning the security of data used in training programs, it is not directly addressed in the text. 'Robustness' refers to benchmarks for AI that are not explicitly mentioned, leading to lesser relevance. Overall, the most significant ties are to social impact measures and adjustments to workforce training in response to automation and technology. Hence it receives a score of 5 in Social Impact, while it is less relevant to the other categories.


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

The text primarily addresses issues impacting workers due to automation, which aligns heavily with the sector of 'Private Enterprises, Labor, and Employment'. It aims to provide training for those likely to be displaced by technology, especially automation-related jobs. There are also indirect references to impacts on 'Government Agencies and Public Services' in terms of how training and workforce programs may be managed. However, it does not delve into how these technologies apply specifically to health, politics, or other sectors like legal systems or educational institutions which reduces the relevance there. 'Nonprofits and NGOs' may have some interest in the training aspect, but it is not the primary focus. Given these factors, the strongest sector relevance is to Private Enterprises, Labor, and Employment (score of 5) and some minor indication for Government Agencies and Public Services (score 3), with scores of 1 or 2 for the rest.


Keywords (occurrence): autonomous vehicle (1) show keywords in context

United States SB1080: Cooper Davis Act

Description: A bill to amend the Controlled Substances Act to require electronic communication service providers and remote computing services to report to the Attorney General certain controlled substances violations.
Summary: The Cooper Davis Act mandates that electronic communication service providers report specific controlled substance violations to the Attorney General, aiming to curtail illegal drug sales, particularly counterfeit substances.
Collection: Legislation
Status date: March 30, 2023
Status: Introduced
Primary sponsor: Roger Marshall (6 total sponsors)
Last action: Placed on Senate Legislative Calendar under General Orders. Calendar No. 200. (Sept. 5, 2023)

Category: None (see reasoning)

The Cooper Davis Act does not explicitly address Artificial Intelligence or algorithms, nor does it delve into the social impacts of AI technologies. Although it involves electronic communication service providers and remote computing services, the legislation focuses primarily on compliance and reporting requirements related to controlled substances violations rather than AI-related governance or accountability measures in relation to social impact, data governance, system integrity, or robustness. As a result, the categories are deemed not applicable to the text.


Sector: None (see reasoning)

The content of the Cooper Davis Act does not pertain to any specific sector associated with the predefined categories. It is primarily a legislative effort to strengthen laws regarding the reporting of controlled substances by electronic communications and computing services, rather than addressing AI applications within any specific sector such as politics, healthcare, or public services. Therefore, it is considered not relevant to any of the defined sectors.


Keywords (occurrence): machine learning (2) algorithm (2) show keywords in context

Departments of Labor, Health and Human Services, and Education, and Related Agencies Appropriations for Fiscal Year 2024

Summary: The bill provides appropriations for the Departments of Labor, Health and Human Services, and Education for fiscal year 2024, focusing on funding critical biomedical research and services to improve health outcomes.
Collection: Congressional Hearings
Status date: May 4, 2023
Status: Issued
Source: Senate

Category: None (see reasoning)

The text discusses the budget appropriations for fiscal year 2024 that heavily involve biomedical research, specifically addressing various health-related topics and the role of the National Institutes of Health (NIH). However, there’s little explicit mention of AI-related technology or its implications for society directly. The focus is more on funding and legislative concerns rather than the broader social impacts of AI, data governance, system integrity, or benchmarks for AI performance. There's potential for AI applications in healthcare, but the text does not delve into those aspects significantly enough to categorize it in those terms.


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

This text primarily pertains to the healthcare sector as it discusses funding and research initiatives related to the NIH, which directly impacts health-related inquiries. While AI is relevant in health contexts, the text itself does not mention AI applications in healthcare specifically. Given this, it may receive a score for potential relevance to healthcare but falls short of being explicitly pertinent to any other sector.


Keywords (occurrence): artificial intelligence (1) algorithm (4) show keywords in context

Compliance and performance testing.

Summary: The bill establishes compliance and performance testing standards for certain facilities to ensure adherence to emissions limits, detailing testing methods and performance requirements for environmental protection.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text provided contains no explicit references to artificial intelligence, algorithms, or similar technologies. Its focus is solely on compliance and performance testing related to emissions management, which does not intersect with AI concerns such as ethical implications, data governance practices, or system integrity measures related to AI algorithms and models. Therefore, the relevance of this text to the categories of Social Impact, Data Governance, System Integrity, and Robustness is notably minimal.


Sector: None (see reasoning)

The text pertains to environmental compliance measures and performance testing protocols which do not involve artificial intelligence or relevant sectors such as politics, healthcare, or judicial systems. There are no references to the application of AI in any sector as discussed in the categories provided. The absence of AI-related content renders this text irrelevant to any of the sectors outlined here, including government operations or private enterprises.


Keywords (occurrence): automated (13) show keywords in context

Oversight of the Securities and Exchange Commission

Summary: The bill involves oversight of the Securities and Exchange Commission (SEC) with a focus on its regulatory practices, particularly concerning digital assets and market rules. The aim is to ensure more clarity and accountability in SEC actions and rulemaking.
Collection: Congressional Hearings
Status date: April 18, 2023
Status: Issued
Source: House of Representatives

Category: None (see reasoning)

The text primarily discusses the oversight of the Securities and Exchange Commission (SEC) and addresses regulatory matters regarding digital assets, market structure reforms, and investor protection. However, it does not explicitly mention or discuss AI technologies or their implications in any capacity. Therefore, the relevance of the provided categories to the content of this text is minimal. For Social Impact, while the text touches on investor protection and market integrity, it does not specifically address the impact of AI on society. Data Governance is similarly irrelevant since there is no discussion on the management or security of data related to AI systems. System Integrity and Robustness are also irrelevant, as the text does not involve legislation pertaining to AI system security, transparency, or performance benchmarks. Overall, the text's lack of AI-related content leads to low scores across all categories.


Sector: None (see reasoning)

The text focuses on the SEC and its operational oversight, with discussions centered around financial regulation, digital assets, and market reforms. It does not specifically address the use of AI in any sector, whether it be politics, government, healthcare, or any others. Instead, it primarily concerns itself with the rules and regulations surrounding financial markets and investor protections. As such, all sector categories receive scores indicative of their non-relevance to the content discussed in the text.


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

New York S05641: Establishes criteria for the use of automated employment decision tools; provides for enforcement for violations of such criteria.

Description: Establishes criteria for the use of automated employment decision tools; provides for enforcement for violations of such criteria.
Summary: The bill establishes criteria for the use of automated employment decision tools in New York, emphasizing anti-discrimination, transparency, and compliance requirements for developers and deployers. Its purpose is to ensure fair employment practices and mitigate discriminatory risks associated with these tools.
Collection: Legislation
Status date: March 10, 2023
Status: Introduced
Primary sponsor: Leroy Comrie (sole sponsor)
Last action: PRINT NUMBER 5641A (Jan. 8, 2024)

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

The text focuses heavily on the use of automated employment decision tools and the implications of AI in the employment context. Given the defined categories, 'Social Impact' is highly relevant as it addresses potential issues of discrimination through AI, requiring transparency and accountability measures to safeguard against misuse. 'Data Governance' is also very relevant since the legislation emphasizes data collection, accuracy, and fairness in AI systems, particularly in employment. 'System Integrity' is potentially relevant as it discusses the need for oversight and governance concerning the deployment of AI tools, though it may not be as central as the previous two. 'Robustness,' while important in AI context, seems less pertinent here since the text does not primarily discuss performance benchmarks or certification but rather focuses on compliance, transparency, and anti-discrimination related to employment decisions made using AI tools. Thus, the emphasis is on ethics, fairness, and governance rather than technical performance metrics.


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

This legislative text primarily pertains to 'Private Enterprises, Labor, and Employment' because it explicitly outlines criteria for the use of automated decision-making tools in employment scenarios, which can profoundly affect hiring, promoting, and termination processes. There are implications for 'Government Agencies and Public Services,' as the enforcement aspects and compliance with laws also involve public institutions, but the main focus remains on the workplace context. It does not directly address 'Politics and Elections' or any other sector provided, making 'Private Enterprises, Labor, and Employment' the most relevant sector for this document.


Keywords (occurrence): artificial intelligence (2) automated (41) show keywords in context

Contents of employee performance files.

Summary: The bill establishes guidelines for maintaining employee performance files, ensuring employees access their performance records, outlines record retention, and delineates the types of documents included in these files.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text outlines regulations regarding the contents and access management of employee performance files, particularly in relation to automated systems. However, it does not directly mention AI or related technologies such as algorithms, machine learning, or automated decision-making systems. While AI may play a role in automation and management of these performance files, there is insufficient direct mention or focus on AI to make it highly relevant to the predefined categories of Social Impact, Data Governance, System Integrity, or Robustness. As such, this text is more administrative in nature without explicit connection to AI-driven issues, leading to low scores across all categories.


Sector: None (see reasoning)

The text does not specifically address any sector that utilizes or regulates AI directly. It focuses more on administrative procedures for employee performance files within governmental and agency contexts rather than the implications of AI use in any context. Therefore, the relevance to the predefined sectors (such as Government Agencies and Public Services, Private Enterprises, or Academic Institutions) is minimal. It does touch on potential data governance aspects but lacks the direct applicability needed for a higher score.


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

United States SB2226: National Defense Authorization Act for Fiscal Year 2024 Military Construction Authorization Act for Fiscal Year 2024 Securing Maritime Data from China Act of 2023 Military Service Promotion Act of 2023 Space Force Personnel Management Act Department of Defense Overdose Data Act of 2023

Description: An original bill to authorize appropriations for fiscal year 2024 for military activities of the Department of Defense, for military construction, and for defense activities of the Department of Energy, to prescribe military personnel strengths for such fiscal year, and for other purposes.
Summary: The bill authorizes appropriations for military activities and construction for fiscal year 2024, addressing personnel strengths, procurement, and various defense-related programs to enhance national security and military readiness.
Collection: Legislation
Status date: July 11, 2023
Status: Introduced
Primary sponsor: Jack Reed (sole sponsor)
Last action: Senate ordered measure printed as passed. (July 27, 2023)

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

The National Defense Authorization Act for Fiscal Year 2024 includes several mentions of artificial intelligence technologies and their applications within the military context. The text highlights AI-related activities such as the development of AI strategies, automation in shipyard operations, and competitive technology developments that include aspects of generative artificial intelligence. Due to the emphasis on the implications of AI strategies in defense operations and technological advancements, it is particularly relevant to the categories of Social Impact, Data Governance, System Integrity, and Robustness, even though the extent and implication in some areas may vary. Overall, the connections to AI in this legislation reflect significant considerations about the impact, governance, integrity, and robustness of AI technologies in military settings.


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

This legislation clearly relates to multiple sectors as outlined. The most relevant sectors include Government Agencies and Public Services, as it directly addresses the military and defense capabilities of government agencies. Additionally, aspects pertaining to Private Enterprises, Labor, and Employment are relevant due to the focus on technology and workforce implications around military service and contracting. The references to the integration of AI in public service operations suggest wider implications for governmental applications. Therefore, the scores reflect a robust association with sectors impacted by AI, especially within government operations and military contexts.


Keywords (occurrence): artificial intelligence (108) machine learning (17) neural network (1) deep learning (1) automated (20) algorithm (1) show keywords in context

Summary of Applicable Requirements for Reference and Equivalent Methods for Air Monitoring of Criteria Pollutants

Summary: The bill outlines procedures for the review and revision of air monitoring methods for criteria pollutants, allowing the EPA to cancel and modify method designations based on public comments and new standards.
Collection: Code of Federal Regulations
Status date: July 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text does not specifically mention AI or any of its related terms such as Algorithm, Automated Decision, or Machine Learning. It primarily discusses the requirements and regulations for reference and equivalent methods for air monitoring of criteria pollutants, focusing on methods' performance characteristics and cancellation procedures. The lack of direct association with the specified AI-related topics leads to the conclusion that this text is largely irrelevant to the categories defined.


Sector: None (see reasoning)

The text does not pertain to any specific sector that explicitly involves AI applications. Although it deals with scientific methods for air monitoring, it does not reference the use of AI in political campaigns, public services, healthcare, or any other specific sectors as defined. Given the absence of AI terminology in a context relevant to these sectors, the text does not meet the criteria for categorization in any of the defined sectors.


Keywords (occurrence): automated (16) show keywords in context

Text of Senate Amendment 933

Summary: This bill authorizes the transfer of Virginia class submarines to Australia under the AUKUS partnership, enhancing trilateral defense cooperation among the U.S., Australia, and the UK for Indo-Pacific security.
Collection: Congressional Record
Status date: July 18, 2023
Status: Issued
Source: Congress

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

The text explicitly references artificial intelligence within the context of military capabilities, particularly under the AUKUS partnership, where it states the importance of developing advanced defense capabilities, including AI. This implies considerations around the social impact that AI technologies may have in military applications, aligning closely with the Social Impact category. The discussion around advanced military capabilities also implies a need for oversight and standards that would reflect on system integrity and robustness, thus garnering relevance towards the System Integrity and Robustness categories. However, the text lacks direct mention or detailed discussions on data governance, which would address concerns such as data security within AI systems. Hence, while there are connections to multiple categories, a certain focus emerges on social impact, system integrity, and robustness as more notable areas of relevance.


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

The text primarily deals with military defense aspects, specifying the AUKUS partnership. While it hints at the integration of artificial intelligence in defense systems, it does not directly pertain to sectors such as Politics and Elections, Government Agencies, Judicial Systems, Healthcare, or NGOs. The discussion is more relevant to private enterprises involved in military technologies and funding, suggesting a moderate alignment with Private Enterprises, Labor, and Employment. Moreover, the mention of collaborative defense technologies implies aspects of international cooperation, accentuating relevance to the International Cooperation and Standards sector. Thus, the text is inadequately broad to fit squarely into a single sector but indicates reasonable closeness to Private Enterprises and International Cooperation.


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

Scope of Covered ICTS Transactions.

Summary: This bill outlines the scope of Covered ICTS Transactions involving U.S. jurisdiction, emphasizing security in critical sectors and delineating exemptions, particularly concerning foreign adversaries' involvement in such transactions.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register

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

The text explicitly addresses ICTS (Information and Communication Technology Supply Chain) transactions that involve AI and machine learning technologies. This section 7.3 of the document mentions that ICTS integral to Artificial Intelligence and Machine Learning is a scope covered under the legislative framework. The considerations around critical infrastructures and sensitive data are also promoted, indicating potential social impacts and issues of robustness for AI implementations. While other categories such as data governance and system integrity may also be relevant, they are not explicitly referenced, which could affect their scoring. This leads to a notable relevance for the Social Impact and Robustness categories.


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

The scope outlined in this regulation covers various sectors, including critical infrastructure and integrates AI technologies that are highly relevant across multiple domains. However, it does not provide specific applications or mention regulations directly tied to the political sphere, healthcare, or judicial considerations. The mention of AI and machine learning hints at impacts on a broad spectrum of sectors, but specific connections to agriculture, education, or non-profits aren't sufficiently present, making it less applicable to sectors outside a generalized governmental framework, especially immediate applications under private enterprises or public services. Thus, the scoring reflects relevant insights primarily in government-related contexts.


Keywords (occurrence): artificial intelligence (1)
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