4840 results:


Summary: The bill addresses concerns regarding the quality and management of VA disability exams, emphasizing the need for effective oversight to ensure veterans receive timely and accurate evaluations for their disability claims.
Collection: Congressional Hearings
Status date: July 27, 2023
Status: Issued
Source: House of Representatives

Category: None (see reasoning)

The document primarily discusses the oversight and quality of disability exams conducted by the Department of Veterans Affairs (VA) and potential improvements. However, it does not explicitly mention AI technologies that would apply to the categories of Social Impact, Data Governance, System Integrity, or Robustness. Since the content does not focus on AI's societal effects, governance of data, security, or performance benchmarks related to AI systems, the relevance to these categories is minimal, yielding low scores for each. Therefore, none of these categories will be applicable to the text.


Sector: None (see reasoning)

The text largely involves legislative oversight centered on the quality and efficiency of VA disability exams for veterans. While it may tangentially relate to Government Agencies and Public Services, the absence of explicit references to AI applications means this relevance is weak. Other sectors related to AI utilization—politics, judicial, healthcare, etc.—are not directly applicable here as the focus remains on an administrative hearing without AI technology integration. Consequently, it doesn't meet the threshold for higher relevance in these contexts.


Keywords (occurrence): automated (3) show keywords in context

Summary: The bill examines the U.S. Coast Guard's efforts in combating drug trafficking, illegal migration, and illegal, unreported, and unregulated fishing, highlighting its critical maritime law enforcement role.
Collection: Congressional Hearings
Status date: Nov. 14, 2023
Status: Issued
Source: House of Representatives

Category: None (see reasoning)

The text primarily focuses on the operations and functions of the U.S. Coast Guard in relation to drug enforcement, illegal migration, and illegal fishing, emphasizing law enforcement, interdiction efficiency, and international cooperation. There is little to no discussion about Artificial Intelligence (AI) or related technologies that would tie into the categories directly. While concepts related to monitoring technologies are mentioned, they are not elaborated as AI technologies specifically. Therefore, the relevance of each category is minimal.


Sector: None (see reasoning)

The text discusses the operational framework of the U.S. Coast Guard and the legislative context of its missions, which could have implications across various sectors, particularly Government Agencies and Public Services, due to the enforcement of laws relating to illegal activities. However, there is no specific mention or detailed discussion regarding the effect of AI within these contexts, nor does the text address issues pertinent to other sectors. Hence, the relevance scores are low across all sectors.


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

Description: An act to amend Sections 1798.99.31, 1798.145, and 1798.185 of the Civil Code, relating to privacy.
Summary: Assembly Bill 1194 amends the California Privacy Rights Act to allow businesses to retain personal information related to abortion services under specific conditions, ensuring consumer privacy while maintaining compliance with legal requirements.
Collection: Legislation
Status date: Oct. 8, 2023
Status: Passed
Primary sponsor: Wendy Carrillo (2 total sponsors)
Last action: Chaptered by Secretary of State - Chapter 567, Statutes of 2023. (Oct. 8, 2023)

Category:
Data Governance (see reasoning)

The text primarily discusses amendments to the California Privacy Rights Act, focusing on consumer rights regarding personal information and privacy concerns rather than directly addressing AI technologies or their implications. While AI could intersect with the data management practices mentioned in the context of protecting children's data, the specific keywords related to AI technologies (like algorithms) are not the main focus and are referenced in the context of children's online safety rather than AI regulation itself. Thus, the categories will receive low relevance scores due to the lack of direct engagement with AI issues as specified in the texts.


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

The text touches on data privacy concerns, particularly in online environments accessed by children, which can intersect with government regulations and frameworks for privacy rights. However, much of the focus relates to general consumer rights and protections rather than strictly AI applications or implications within specific sectors. It's relevant mostly to data management practices and privacy rights rather than a specific sector like healthcare or workplace. Thus, while the text addresses important privacy considerations, its direct relevance to particular sectors is moderate at best.


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

Summary: The bill oversees the implementation of the Infrastructure Investment and Jobs Act, analyzing various transportation modes under the Department of Transportation to ensure effective infrastructure funding and management.
Collection: Congressional Hearings
Status date: Dec. 13, 2023
Status: Issued
Source: House of Representatives

Category: None (see reasoning)

The text focuses on the oversight of the Infrastructure Investment and Jobs Act (IIJA) and primarily details its provisions, funding, and administrative structure within the Department of Transportation (DOT). While it discusses various transportation programs that may indirectly involve technological advancements, including AI for traffic management or safety enhancements, there are no explicit mentions or provisions related to AI systems or their social impact, data governance, system integrity, or robustness. Given the absence of AI-focused language, the relevance to AI categories is minimal.


Sector:
Government Agencies and Public Services (see reasoning)

The text discusses the Infrastructure Investment and Jobs Act's implications for various transportation programs administered by the DOT. Although the implications of legislation related to infrastructure could overlap with sector applications of AI, the document does not specifically address AI regulation or usage across the sectors listed. As such, it does not sufficiently cover any of the defined sectors, leading to low relevance scores.


Keywords (occurrence): automated (24) autonomous vehicle (2) show keywords in context

Summary: The bill emphasizes U.S. national security interests in Ukraine amid its conflict with Russia. It advocates for supplemental funding to strengthen Ukraine's defense and governance, enhancing global stability and countering adversaries like Iran and North Korea.
Collection: Congressional Hearings
Status date: Nov. 8, 2023
Status: Issued
Source: Senate

Category: None (see reasoning)

The text is focused primarily on the U.S. national security interests concerning Ukraine amidst conflict with Russia. While it may touch on technology and oversight related to military aid and security, there are no explicit references to AI, algorithms, or related topics that would tie directly to the categories of Social Impact, Data Governance, System Integrity, or Robustness. While there are discussions around technology and accountability, these do not specifically engage with the realms of AI-related legislation or regulation.


Sector: None (see reasoning)

The text deals with foreign relations and national security issues without specific engagement with sectors defined around AI applications. Discussions about international alliances, defense agreements, and military funding do not directly relate to the designated sectors, particularly those around AI utilization in Politics and Elections, Government Agencies and Public Services, Judicial Systems, Healthcare, Private Enterprises, Academic Institutions, International Cooperation, Nonprofits, or Emerging sectors. Thus, the text does not strongly tie into the specified sectors.


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

Description: A bill to require agencies that use, fund, or oversee algorithms to have an office of civil rights focused on bias, discrimination, and other harms of algorithms, and for other purposes.
Summary: The Eliminating Bias in Algorithmic Systems Act of 2023 mandates the establishment of offices of civil rights in agencies managing algorithms to address bias and discrimination, ensuring accountability and oversight.
Collection: Legislation
Status date: Dec. 12, 2023
Status: Introduced
Primary sponsor: Edward Markey (8 total sponsors)
Last action: Read twice and referred to the Committee on Homeland Security and Governmental Affairs. (Dec. 12, 2023)

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

The text explicitly addresses issues related to bias and discrimination in algorithmic systems, focusing on how these algorithms impact society, especially in contexts like civil rights. The bill mandates the establishment of an office of civil rights in agencies that oversee or use algorithms. This is closely aligned with the Social Impact category as it addresses the societal implications and potential harm caused by AI algorithms. The Data Governance category is also relevant due to the emphasis on managing and overseeing algorithmic processes to prevent discrimination and bias. System Integrity is relevant because it touches on ensuring careful oversight and control within AI systems and the need for reporting on algorithmic harms. Robustness is less relevant here since the focus is primarily on bias rather than performance metrics or standards for AI systems. Overall, the primary focus on societal impact and bias makes Social Impact particularly relevant, followed by Data Governance and System Integrity.


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

The legislation focuses on algorithms and AI in the context of agencies, suggesting a significant relevance to Government Agencies and Public Services. The text does not directly address political campaigns or elections, nor does it mention healthcare, cybersecurity in the judicial system, or private enterprises. While it could have implications for academic institutions being part of the discussions on civil rights and algorithmic fairness, this is not the primary focus of the legislation. The legislation's emphasis on civil rights and algorithmic oversight leads me to assign the highest relevance to Government Agencies and Public Services, while other sectors remain less relevant as they are not explicitly or significantly addressed in the text.


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

Summary: The bill focuses on enhancing aviation security through advanced technology. It addresses the slow implementation of technological systems by the TSA and seeks to ensure that funds from the Passenger Security Fee are utilized effectively for improving security measures.
Collection: Congressional Hearings
Status date: Oct. 19, 2023
Status: Issued
Source: House of Representatives

Category: None (see reasoning)

The text primarily addresses aviation security technology without explicitly focusing on AI-related topics. While it discusses technologies for screening passengers and identifying threats, it does not delve into AI-specific applications such as algorithms, machine learning, or automated decision-making related to security processes. As such, its relevance to the categories is limited, with only marginal connections to technology rather than a core focus on AI principles.


Sector:
Government Agencies and Public Services (see reasoning)

The text is focused on aviation security, particularly the role of technology utilized by the TSA, which falls under Government Agencies and Public Services. While the discussions involve technology's implications for consumer safety and efficiency, which might hint at broader operational impacts, they do not significantly touch upon other sectors like politics, healthcare, or labor. Overall, the text's core focus remains within aviation security technology as utilized by governmental entities.


Keywords (occurrence): artificial intelligence (1) automated (2) algorithm (12) show keywords in context

Summary: The bill involves a markup of several measures by the House Foreign Affairs Committee, including legislation aimed at restricting U.S. investments in critical technology sectors that could aid adversaries such as China, Russia, Iran, and North Korea.
Collection: Congressional Hearings
Status date: Nov. 29, 2023
Status: Issued
Source: House of Representatives

Category:
Societal Impact
Data Governance (see reasoning)

The text addresses the role of AI in national security, specifically related to how the Chinese Communist Party utilizes AI for surveillance and other military applications. It highlights concerns about U.S. investments in AI technologies that could potentially strengthen adversaries like China, which places a clear emphasis on the social implications of AI, especially regarding security and ethical treatment of minorities. This strongly aligns with the Social Impact category. The text also touches upon data and investment strategies related to AI development, hinting at accountability and transparency needed in those sectors, which connects to Data Governance. However, the primary focus on the consequences of AI use and investment biases this text more towards Social Impact than Data Governance. Other aspects like System Integrity and Robustness are less pertinent given the absence of focus on security measures for AI systems or performance benchmarks in AI developments.


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

The discussion revolves significantly around AI's relevance to national security, primarily through its use by the Chinese government, which ties it closely to the Politics and Elections sector. This includes concerns about investments in AI that could bolster adversarial capabilities. The mention of the Executive Order and its intentions implies regulatory considerations related to technologies that might influence not just the stability of the government but its operational capabilities in international contexts, which also reflects a strong connection to Government Agencies and Public Services. However, there is little emphasis on its application in the Judicial System, Healthcare, or Academic and Research Institutions, rendering those sectors less relevant. Overall, the text emphasizes regulatory and security dimensions that align well with Politics and Government Agencies.


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

Description: Creates the Safe Patient Limits Act. Provides the maximum number of patients that may be assigned to a registered nurse in specified situations. Provides that nothing shall preclude a facility from assigning fewer patients to a registered nurse than the limits provided in the Act. Provides that the maximum patient assignments may not be exceeded, regardless of the use and application of any patient acuity system. Requires the Department of Public Health to adopt rules governing the implementa...
Summary: The SAFE Patient Limits Act establishes maximum patient assignments for registered nurses in Illinois healthcare facilities, ensuring safe nurse-to-patient ratios and enhancing care quality and nurse protections. It mandates compliance with staffing standards without reducing overall workforce levels.
Collection: Legislation
Status date: Feb. 10, 2023
Status: Introduced
Primary sponsor: Celina Villanueva (8 total sponsors)
Last action: Added as Co-Sponsor Sen. Mattie Hunter (March 7, 2024)

Category: None (see reasoning)

The Safe Patient Limits Act primarily focuses on establishing maximum patient loads for registered nurses within healthcare facilities, which directly affects how patient care is administered and the overall healthcare workforce. However, it does not make significant reference to AI-related technology, such as automated decision-making processes or algorithmic assessments in patient care. As such, while the act is relevant to healthcare and the implications it carries for staff and patients, it does not engage deeply with the implications of AI in any capacity. Therefore, the scores reflect a recognition of healthcare impacts but a lack of specific AI relevance within the provided text.


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

The legislation is explicitly centered on healthcare and nursing practices, setting patient limits for registered nurses. Thus, while it does not address AI directly, it profoundly impacts the healthcare sector by outlining staffing requirements and responsibilities of healthcare professionals. Conversely, the legislation does not target other sectors such as public service functionalities, legal systems, or government functions. The scoring reflects a strong relevance to healthcare without extending to significant overlap with other sectors.


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

Description: Prohibits the knowing and reckless promotion of unlawful or false material; provides remedies for the violation of such prohibition.
Summary: This bill prohibits the promotion of unlawful or false material in New York, establishing penalties and allowing for private and public enforcement actions to protect public safety.
Collection: Legislation
Status date: Jan. 5, 2023
Status: Introduced
Primary sponsor: Brad Hoylman-Sigal (2 total sponsors)
Last action: REFERRED TO JUDICIARY (Jan. 3, 2024)

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

The text explicitly mentions the use of algorithms and automated systems in the context of promoting unlawful or false material. This directly relates to the 'Social Impact' category as it addresses the implications of AI-driven content promotion on public safety and health. The legislation is particularly concerned with the harmful promotion that could stem from AI technologies. In terms of 'Data Governance', while it doesn't focus primarily on data management and accuracy within AI systems, it implicitly raises considerations regarding the content that algorithms may promote and how data may be leveraged in these automated systems. For 'System Integrity', there's a concern regarding oversight of algorithms that can prioritize harmful content, potentially indicating a need for safeguards, while 'Robustness' does not appear to be directly relevant since the text does not discuss AI performance benchmarks or qualities. Thus, 'Social Impact' receives a high score while the other categories receive lower relevance scores.


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

The text is most relevant to 'Politics and Elections' as it inhibits the reckless promotion of harmful or false material, which could impact political campaigning and the dissemination of information in electoral processes. It also may have relevance for 'Government Agencies and Public Services' due to the implications for public safety and potential enforcement by governmental bodies. However, it is less relevant to the other sectors which do not explicitly feature AI or its application in a direct manner. Therefore, 'Politics and Elections' receives a high score, while other sectors receive lower scores reflecting their marginal relevance.


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

Summary: The bill addresses occupational safety by establishing regulations for employee exposure to hazardous chemicals in laboratories, aiming to protect workers from health risks, particularly cancer, and ensuring compliance with safety 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 focuses on occupational safety regulations concerning hazardous chemicals in laboratories and does not reference AI technologies or practices. Therefore, its relevance to the AI related categories is not significant. There is no mention of social impacts directly tied to AI, no governance of data relevant to AI systems, no discussion of integrity of systems related to AI, nor any evaluation of AI robustness or benchmarks.


Sector: None (see reasoning)

The text does not relate to the sectors in the predefined list as it is centered around laboratory safety concerning hazardous chemicals and compliance with OSH regulations. There is no mention of AI applications in politics, government, healthcare, or other relevant sectors, making it non-applicable to all suggested sectors.


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

Summary: The bill establishes requirements for swap data repositories to develop emergency procedures, risk analysis, and system safeguards to ensure operational reliability, security, and a rapid recovery from disruptions.
Collection: Code of Federal Regulations
Status date: April 1, 2023
Status: Issued
Source: Office of the Federal Register

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

The text discusses various aspects of system safeguards, particularly focusing on the risk analysis, oversight, and management of automated systems. Given the emphasis on 'automated systems' and the necessity for operational security in swap data repositories, there is a significant implication regarding the role of AI technologies in enhancing operational risk management. This relevance extends across categories as follows: Social Impact is slightly relevant, mainly due to the indirect implications on consumer protection and operation transparency. Data Governance scores moderately due to the focus on securing and managing data, which is crucial for AI systems. System Integrity is very relevant, as the text elaborates on ensuring reliable, secure automated systems, which is essential for maintaining trust and operational stability in AI systems. Robustness scores highly as it addresses the standards and practices for testing and ensuring system reliability, which are vital for any AI deployed initiatives.


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

This legislation is primarily related to financial systems, particularly swap data repositories, which use automated systems extensively in financial transactions and data management. Therefore, its relevance to different sectors is as follows: Politics and Elections score low as there is no mention of AI use in political campaigns or electoral processes. Government Agencies and Public Services is slightly relevant, given the regulatory nature of the document but lacks direct mention of AI applications in public services. The Judicial System scores low since the document does not address AI in legal context. Healthcare is not mentioned and receives a low score. Private Enterprises, Labor, and Employment are moderately relevant as it touches on automated system reliability which can impact enterprise operations. Academic and Research Institutions is not specifically mentioned, leading to a low score. International Cooperation and Standards is rated low for lack of international implications. Nonprofits and NGOs is also low as the focus is governmental. Finally, Hybrid, Emerging, and Unclassified scores low as the text primarily deals with financial data repositories rather than hybrid models.


Keywords (occurrence): automated (18) show keywords in context

Summary: This bill focuses on evaluating the impact of automated commercial motor vehicles on society, supply chains, and U.S. economic leadership, considering their potential for enhancing safety and efficiency in transportation.
Collection: Congressional Hearings
Status date: Sept. 13, 2023
Status: Issued
Source: House of Representatives

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

The text explicitly discusses automated commercial motor vehicles (AVs), which are a direct application of AI technologies. It highlights their potential impacts on society, the economy, and how these vehicles are changing the landscape of transportation and logistics. This aligns closely with the Social Impact category, particularly regarding the societal implications of deploying AI in transportation. The text also emphasizes the safety and regulatory considerations surrounding AVs, which relate to System Integrity by mentioning the automated driving systems' levels and their operational capabilities. Although it touches on aspects of data management in describing how AVs use sensors and GPS, it does not sufficiently address standards for data governance or security measures, thus limiting this category's relevance. The Robustness category is relevant here due to the mention of automation levels and their adherence to safety standards but lacks depth on performance benchmarks or audits. Overall, the strongest relevance lies in the Social Impact and System Integrity categories.


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

The text primarily revolves around the development and regulation of automated commercial vehicles. It discusses impacts on transportation and logistics, which directly pertains to the Government Agencies and Public Services sector. The mention of AVs’ potential to transform transportation systems indicates its relevance to public service delivery. There is no direct mention of AI within the Judicial System, Healthcare, or specific mentions within the framework of Private Enterprises, Labor, and Employment. Still, the mention of the trucking industry and related employment implications suggests a moderate connection to labor markets. While there are no explicit references to International Cooperation and Standards or Nonprofits and NGOs, the overall focus remains on how AVs influence governmental and public realms.


Keywords (occurrence): artificial intelligence (1) machine learning (4) automated (230) autonomous vehicle (50) show keywords in context

Summary: The bill outlines regulations to ensure telecommunications carriers obtain proper authorization from subscribers before changing their service providers, aiming to prevent unauthorized carrier changes and protect consumer rights.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily focuses on regulations regarding the verification of orders for telecommunications services. It emphasizes procedural requirements and consumer protections in the context of telecom carriers and does not explicitly or implicitly reference AI technologies or concepts. Thus, none of the categories regarding Social Impact, Data Governance, System Integrity, or Robustness are relevant here. Since the text deals with order verification specifics and does not include any references or implications of AI, it scores a 1 across all categories.


Sector: None (see reasoning)

The text outlines rules and procedures regarding telecommunications services but does not delve into the use or regulation of AI within any specific sectors such as politics, government, healthcare, or any other mentioned sectors. Given its focus solely on telecommunications processes, there is no relevance to Politics and Elections, Government Agencies and Public Services, Judicial System, Healthcare, Private Enterprises, Labor and Employment, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, or Hybrid, Emerging, and Unclassified. Consequently, all sectors receive a score of 1.


Keywords (occurrence): automated (3) show keywords in context

Summary: The bill mandates railroads to use third-party telephone services for reporting unsafe conditions at grade crossings, improving emergency response and communication protocols among multiple railroads.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily pertains to the practical use of a third-party telephone service by dispatching and maintaining railroads, focusing on protocols for reporting unsafe conditions at grade crossings. It does not directly address any societal concerns or impacts from AI technologies, nor does it mention specific data governance practices involving AI, the integrity of AI systems, or any benchmarks related to AI performance. The text mainly involves operational procedures rather than any legislative measures related to AI ethics, accountability, transparency, or robustness, leading to scores that reflect minimal relevance to the categories defined.


Sector: None (see reasoning)

The legislation outlined is focused on railroad operations and safety reporting practices rather than any sector directly related to the predefined sectors. Specifically, while the text discusses coordination among railroads and the use of telephone services, it does not directly address political uses of AI, governmental use, judicial applications, healthcare, private enterprise impacts, academic regulation, international standards, or the functions of nonprofits related to AI. Thus, all sectors receive a score indicating a lack of direct relevance.


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

Summary: The bill examines national security threats posed by advanced technologies, such as AI and biotechnology, and seeks to identify measures for risk mitigation while fostering innovation.
Collection: Congressional Hearings
Status date: Sept. 19, 2023
Status: Issued
Source: Senate

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

The text discusses the implications of AI and other emerging technologies on national security, specifically focusing on potential threats and the need for regulation and oversight. This aligns directly with the themes under Social Impact as it highlights public safety risks and the need for responsible AI development to prevent misuse by bad actors. Legislation aiming to mitigate these risks and encourage safe AI development reflects essential societal considerations that fall under this category. In terms of Data Governance, the document touches on the need for maintaining the integrity and safety of AI systems, indicating a level of relevance as it implies the necessity for proper data management to ensure that AI doesn't contribute to harmful activities. By examining national security threats from AI, there is also a strong connection to System Integrity, as ensuring the safety and control of AI systems against misuse is critical. The text presents no details on measuring performance metrics or standards for AI systems, which would relate more to Robustness; therefore, this category receives a lower score.


Sector:
Government Agencies and Public Services
Judicial system
International Cooperation and Standards (see reasoning)

The text heavily revolves around national security concerns relative to emerging technologies like AI, making it very relevant to the Government Agencies and Public Services sector, as it deals with how government can regulate and respond to these technologies. There are implications for the Judicial System as AI's integration raises questions about legal frameworks, but it's not explicitly mentioned, allowing for a moderate connection. Healthcare is indirectly mentioned in the context of technological benefits, indicating relevance, but less clear cut compared to national security. The discussion does not provide specific relevance to the other sectors, as they are not explicitly addressed in the text. The overarching theme is about national security and AI regulation, which falls prominently within Government Agencies and Public Services.


Keywords (occurrence): artificial intelligence (10) machine learning (6) deepfake (6) synthetic media (1) show keywords in context

Summary: The bill addresses the rise of deepfake technology, highlighting its potential dangers such as misinformation, privacy violations, and national security threats. It calls for collaborative efforts to develop detection standards and educate the public on combating abuse of deepfake content.
Collection: Congressional Hearings
Status date: Nov. 8, 2023
Status: Issued
Source: House of Representatives

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

This text discusses deepfake technology, which is a significant application of artificial intelligence. It addresses the social implications of deepfakes, such as misinformation, exploitation, and harms that can arise from AI-generated content. The text also touches upon preventative measures and the responsibilities of both the government and private sector, indicating a legislative concern about the societal impact of AI technologies. Thus, Social Impact is highly relevant. Data Governance also applies, as managing the implications and controls around data used to create deepfakes is crucial, especially regarding any legal and ethical frameworks needed to prevent misuse. System Integrity is moderately relevant due to the text's focus on the importance of secure and transparent operations regarding generative content. Robustness rates lower as it does not directly discuss performance benchmark standards or certification processes for AI systems, focusing instead on existing tools for detection and legal implications rather than system performance evaluation.


Sector:
Politics and Elections
Government Agencies and Public Services
Judicial system
International Cooperation and Standards (see reasoning)

The text primarily addresses issues related to societal harm caused by AI in the form of deepfakes, indicating its strong relevance to the Politics and Elections sector due to the implications for misinformation in political contexts. However, it also touches on broader concerns such as mental health impacts, legal implications, and societal trust. Government Agencies and Public Services are relevant as there is a clear discussion around governmental roles in addressing these technologies. Though private enterprises and law applications are mentioned, the direct implications pertain more to the societal and governmental responses rather than corporate governance or legal frameworks initially outlined in the legislation. Hence, Politically motivated responses are rated higher.


Keywords (occurrence): artificial intelligence (1) automated (2) deepfake (54) synthetic media (2) algorithm (2) show keywords in context

Summary: The bill emphasizes the need for bipartisan discussions on artificial intelligence, focusing on transparency, intellectual property protections, and maintaining innovation while ensuring creator rights in the AI landscape.
Collection: Congressional Record
Status date: Nov. 30, 2023
Status: Issued
Source: Congress

Category:
Societal Impact
Data Governance (see reasoning)

This text discusses critical issues related to AI, focusing on areas such as transparency, intellectual property, and copyright within the context of AI. This makes it relevant to two categories: 'Social Impact' due to the mention of protections for creators in the age of AI and accountability of AI systems, and 'Data Governance' because of the emphasis on IP protection, which ties into the governance of data generated through AI systems. The discussion also touches on transparency, which is critical to understanding and trust, linking to 'System Integrity' but it is not explicitly detailed. The category 'Robustness' is not directly addressed since performance benchmarks are not mentioned, so it is less relevant. Therefore, a moderate relevance score is assigned to 'Social Impact,' a moderate score to 'Data Governance,' and a lower score to 'System Integrity.' 'Robustness' is not relevant at all.


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

The text outlines discussions from a congressional record regarding AI Insight Forums held in the Senate. Given that these discussions involve transparency, intellectual property, and the regulatory environment for AI, they relate primarily to government agencies and public services as they are examining the role of legislation and governance in the use of AI. The mention of creators in the context of AI also relates to private enterprises, labor, and employment, but it does not explicate details on regulatory frameworks for political campaigns, the judicial system, healthcare, academic institutions, or international cooperation. Hence, the score for 'Government Agencies and Public Services' is high, while others receive lower relevance scores or none at all.


Keywords (occurrence): artificial intelligence (1)

Summary: The bill establishes a structure for prioritizing communication restoration during emergencies, creating four priority levels for government and commercial services essential for national security and public welfare. It aims to ensure effective communication access in crisis situations.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily deals with the restoration priorities for communication services in critical situations, specifically focusing on the management of circuit availability for various levels of priority during national emergencies. It does not mention AI explicitly nor does it address issues related to AI's societal impact, data management within AI systems, the integrity or transparency of AI systems, or the benchmarks for AI performance. Thus, all categories related to AI are not applicable.


Sector: None (see reasoning)

This text pertains to the communication priorities set by the government during emergencies but does not specifically address the use or regulation of AI in any sector. While it refers to government services and industrial participation, it does not discuss AI applications in political processes, public services, healthcare, employment, or any other fields listed. Therefore, it scores low relevance across all sectors.


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

Description: To reauthorize the National Quantum Initiative Act, and for other purposes.
Summary: The National Quantum Initiative Reauthorization Act seeks to renew and expand the National Quantum Initiative, emphasizing workforce development, research, and international cooperation in quantum technology while addressing national security concerns.
Collection: Legislation
Status date: Nov. 3, 2023
Status: Introduced
Primary sponsor: Frank Lucas (34 total sponsors)
Last action: Placed on the Union Calendar, Calendar No. 510. (July 25, 2024)

Category: None (see reasoning)

The text predominantly concerns the reauthorization of the National Quantum Initiative Act. While the text does mention artificial intelligence (AI) in the context of supporting technologies that may benefit from quantum technology, it does not deeply engage with the implications or impacts of AI on society, data governance, system integrity, or performance benchmarks. The reference to AI is minimal and mainly supportive rather than central, suggesting only a basic relevance to these categories. Therefore, the text does not directly address broader issues related to the social impact, data governance, system integrity, or robustness of AI, resulting in low scores across all four categories.


Sector: None (see reasoning)

The text is largely focused on advancements in quantum information science and technology and does not specifically discuss AI applications in the contexts of politics, government operations, judiciary matters, healthcare, business, academia, international standards, or nonprofit organizations. The mention of AI appears more incidental and does not justify categorization under any significant sector. Given that AI is mentioned but not explored in detail, it does not warrant high relevance scores for any sector. Thus, the scores are low across the board.


Keywords (occurrence): artificial intelligence (2) machine learning (2) algorithm (1) show keywords in context
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