5024 results:


Summary: The bill pertains to a Members' Day hearing held by the House Committee on Science, Space, and Technology, focusing on prioritizing diversity, equity, and inclusion in scientific research and representation.
Collection: Congressional Hearings
Status date: July 19, 2023
Status: Issued
Source: House of Representatives

Category:
Societal Impact (see reasoning)

The text pertains to a hearing conducted by the House Committee on Science, Space, and Technology, where discussions included topics related to Artificial Intelligence (AI). Although the overall focus may not be entirely on legislative measures temporarily, references to the disparate impacts of AI technologies on marginalized communities significantly highlight the social ramifications and ethical considerations surrounding AI usage. Specifically, these discussions address the importance of addressing fairness and bias in AI systems and the impact they have on equity and representation. Without a full enumeration of the AI systems addressed, the references are still substantial enough to categorize the relevance under Social Impact due to its focus on accountability and potential harms from AI systems and their decisions. Data Governance and System Integrity are less relevant as this text does not delve into specifics regarding data management or the security and transparency of AI systems. Robustness appears not to be directly addressed either. Overall, the text emphasizes a societal lens, thus scoring higher in the Social Impact category.


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

The text references the Congressional Committee's exploration of AI and its implications, particularly in relation to inclusion and equity, which aligns with multiple sectors. For instance, the mention of legislation that could address the participation of diverse communities in scientific advancements suggests connections to the Government Agencies and Public Services sector due to the Committee's oversight role. There is also relevance in terms of Private Enterprises, Labor, and Employment, given that fairness considerations in AI technologies may impact employment practices and corporate governance. Although AI discussions are present, the overall scope of the text does not delve deeply into regulatory frameworks that specify operational impacts on sectors such as Healthcare or Judicial Systems directly, thus scoring lower in those categories. The attention to marginalized groups in the AI context hints at broader societal concerns more so than direct impacts on sectors such as Politics and Elections. However, the intersectionality of AI with social justice issues reinforces strong relevance in the noted sectors.


Keywords (occurrence): machine learning (4) show keywords in context

Summary: The bill outlines General Approved Exclusions (GAEs) for certain steel articles under the Section 232 Exclusions Process, allowing importers to request varied validity periods based on specific factors affecting their needs.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily addresses the exclusion process for steel articles under Section 232, emphasizing factors for determining exclusion validity periods and the review process by the U.S. Department of Commerce. There are no explicit mentions of AI, algorithms, or related technologies. As such, the relevance of the four AI-related categories is minimal. Social Impact, Data Governance, System Integrity, and Robustness do not have any context or content related to AI systems, their governance, or their impact on society. Thus, all categories are rated as 1: Not relevant.


Sector: None (see reasoning)

The text predominantly deals with regulatory processes surrounding steel imports and has no content related to the sectors provided (politics, healthcare, etc.). There are no mentions or implications of AI application in any of the listed sectors. Therefore, each sector is evaluated as 1: Not relevant.


Keywords (occurrence): automated (2)

Summary: The "Securing Growth and Robust Leadership in American Aviation Act" aims to amend federal aviation laws, reauthorize the FAA, enhance workforce development, and promote collaboration with educational institutions, while modernizing aviation systems and ensuring national security.
Collection: Congressional Record
Status date: July 20, 2023
Status: Issued
Source: Congress

Category:
System Integrity
Data Robustness (see reasoning)

The text primarily discusses amendments related to the Federal Aviation Administration and improvements in aviation management. There is a mention of 'automation' in the context of enhancing operational efficiencies for airspace management, which could be linked to AI technologies. However, the discussion is not extensive regarding the broader societal implications of AI, specific data governance issues, or system integrity aspects. The automation mentioned relates to operational processes rather than addressing general issues of AI systems or their robustness. Therefore, the relevance of this text to the categories is restricted primarily to operational context rather than a direct focus on AI's societal, governance, or robust integrity implications.


Sector:
Government Agencies and Public Services (see reasoning)

The text references the Federal Aviation Administration and the use of technology in aviation, including automation and process improvements related to airspace management. However, it does not engage deeply with how AI intersects with political processes, healthcare, employment, or other sectors. The automation initiatives mentioned are more about administrative efficiency in air traffic control rather than a direct application of AI across multiple sectors. Thus, the scores reflect the limited nature of the application of AI within the context provided.


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

Summary: The bill outlines general terms and conditions for the Supplemental Nutrition Assistance Program (SNAP), detailing eligibility, tax exemptions on SNAP purchases, confidentiality of recipient information, and requirements for participating state agencies.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text provided is a detailed description of requirements and regulations related to the food assistance program but does not mention Artificial Intelligence (AI) or related terms such as algorithms, machine learning, or automated decision-making. As such, the text seems to focus primarily on administrative and operational aspects of the food and nutrition service without addressing any AI implications. Therefore, its relevance to the specified categories related to AI is minimal.


Sector: None (see reasoning)

The text outlines various provisions and operational guidelines under the USDA's Food and Nutrition Service related to SNAP (Supplemental Nutrition Assistance Program). While it addresses certain administrative and procedural requirements, there is no content that directly relates to the use of AI in political campaigns, public services, judicial systems, healthcare, or any other sector definitions as categorized. Thus, the overall relevance of the text to the specific sectors listed is very low.


Keywords (occurrence): automated (1)

Summary: This bill establishes rules for proxy statements under the Securities Exchange Act, outlining requirements for disclosing executive compensation, shareholder voting, and the obligations of registrants, including smaller companies.
Collection: Code of Federal Regulations
Status date: April 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text focuses on disclosures and regulations related to proxy statements and executive compensation that do not mention or involve any AI-specific aspects, such as automated decision-making, algorithms, or any other referenced AI terms. Therefore, it lacks relevance to the Social Impact, Data Governance, System Integrity, or Robustness categories. It does not address societal impacts of AI, data management for AI, security and transparency of AI systems, or performance benchmarks for AI systems.


Sector: None (see reasoning)

The text concerns proxy statement requirements for registrants, particularly regarding the compensation of executives and their disclosure practices. No AI-related applications or regulations affecting specific sectors such as Politics, Government, Healthcare, etc., are mentioned, meaning the text does not fit neatly into any of the provided sectors. Hence, it is rated low across all sectors.


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

Summary: This bill establishes regulations for the importation of merchandise subject to quotas, detailing entry limits, the handling of excess imports, and prioritization for quota status based on proper documentation.
Collection: Code of Federal Regulations
Status date: April 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily pertains to customs regulations, addressing import quotas and procedures related to merchandise entry. There are no explicit references to AI or related technologies, making it clear that the legislation does not involve any categories related to AI social impact, data governance, system integrity, or robustness. The content is strictly administrative and does not touch on any AI-related matters such as ethical implications, data management, system reliability, or performance metrics in the context of AI. Therefore, all categories would receive a score of 1, indicating no relevance to the content at hand.


Sector: None (see reasoning)

Similarly, the text does not pertain to any of the nine sectors relating to AI usage or regulation. It discusses customs and border protection, specifically focusing on the administration of import quotas, which does not involve sectors such as politics and elections, government services, or healthcare. There are no implications or applications that relate to each sector's definitions, leading to an assessment of 1 across all sectors, as they are entirely irrelevant to the content provided.


Keywords (occurrence): automated (1)

Summary: The bill mandates electronic registration for specific activities regulated by the Federal Energy Regulatory Commission, ensuring streamlined compliance and information submission, while allowing waiver requests under certain conditions.
Collection: Code of Federal Regulations
Status date: April 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

This text primarily addresses regulatory procedures for electronic registration with the Federal Energy Regulatory Commission and does not explicitly mention artificial intelligence or its related technologies. As the legislation does not discuss the social impact of AI, data governance in terms of AI datasets, system integrity with respect to AI, or benchmarks for robustness in AI systems, it does not fit into any of the predefined categories.


Sector: None (see reasoning)

The text focuses on electronic registration processes and does not mention the use or regulation of AI across any sectors like politics, government agencies, healthcare, or business. Therefore, it is not relevant to any of the specified sectors.


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

Summary: The bill classifies various ophthalmic devices, such as AC-powered slitlamp biomicroscopes and stereoscopes, outlining their usage, regulatory exemptions, and intended purposes for eye examination and testing.
Collection: Code of Federal Regulations
Status date: April 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

This text focuses predominantly on medical devices and their regulatory classifications, particularly highlighting the technical specifications and classifications of various ophthalmic devices such as the slitlamp biomicroscope and stereoscope. There are no mentions of AI technologies or practices such as algorithms, machine learning, automated decision-making, or any related concepts. Consequently, all categories pertaining to social impact, data governance, system integrity, and robustness are deemed not relevant, as the text does not engage with considerations around AI's societal implications, data management, system security, or performance benchmarks.


Sector: None (see reasoning)

The text primarily describes medical devices and their classifications without addressing the use of AI within healthcare or any of the other specified sectors. The absence of AI-related language renders all sector categorizations irrelevant. There are no indications that AI is employed in the regulatory framework or operational context of these devices.


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

Summary: The bill outlines the rules and procedures USAID follows in processing Freedom of Information Act requests, balancing public access to information with confidentiality and privacy protections.
Collection: Code of Federal Regulations
Status date: April 1, 2023
Status: Issued
Source: Office of the Federal Register

Category:
Data Governance (see reasoning)

The text primarily revolves around the procedural aspects governing information requests from the USAID as stipulated under the Freedom of Information Act (FOIA) and the Privacy Act, with a focus on records management and confidentiality. There are no explicit references to AI within the text. However, automated information systems are mentioned briefly, which could imply some interaction with AI technologies in a very limited context. Given the lack of a direct focus on AI, this has less impact on societal issues or governance. Therefore, I find the relevance to the categories as follows: Social Impact - very limited regarding societal aspects, Data Governance - moderate relevance attributed to privacy concerns but not directly AI-focused, System Integrity - slightly relevant because it does address governance of information systems, and Robustness - not applicable as there are no mentions of AI performance benchmarks or compliance standards related to AI.


Sector:
Government Agencies and Public Services (see reasoning)

The text is primarily about procedural policies related to government information requests and does not pertain to the sectors in a direct manner. Politics and Elections may have vaguer ties due to normal government operations but lacks AI relevance. Government Agencies and Public Services is more applicable since it is about USAID functions, yet does not mention specific AI applications directly. The other sectors, such as Judicial System, Healthcare, Private Enterprises, Academic Institutions, etc., have no ties to the provided text, hence they receive low scores. Overall, the most relevant sector appears to be Government Agencies and Public Services, but still remains low due to vague interactions with AI.


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

Summary: The Line Release bill establishes an automated system for expedited processing of repetitive import shipments. It outlines procedures for application, approval, and conditions affecting delivery privileges based on Customs compliance.
Collection: Code of Federal Regulations
Status date: April 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily deals with Customs regulations and procedures for an automated system known as Line Release. There are mentions of 'automated' and 'system,' indicating a technological system at work, but no explicit discussion of AI-related technologies such as algorithms or machine learning. As such, its relevance to the predefined categories appears limited. It does not address social impacts, data governance, system integrity or robustness in the context of AI-related legislation. Rather, it focuses on procedural aspects without delving into the implications that AI might have, such as fairness, bias, or accountability. Therefore, all categories score very low in terms of relevance.


Sector: None (see reasoning)

The text is focused strictly on Customs and Border Protection regulations regarding the Line Release process for importers. It does not touch on any sectors such as politics, healthcare, or public services in a way that involves AI or automated systems. Consequently, none of the sectors applied here are relevant to this excerpt, earning it a score of 1 across the board for sector relevance.


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

Summary: The bill establishes criteria for modernization and restructuring within the National Weather Service, ensuring no degradation of service during transitions while involving public input and operational oversight.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category:
System Integrity
Data Robustness (see reasoning)

The text provides extensive information about modernization criteria for the National Weather Service, specifically addressing automated surface observation systems (ASOS) and other automation-related elements. However, the focus is primarily on operational standards, training, and procedural requirements rather than examining the social impacts, data governance, system integrity, or robustness of AI systems. Given that much of the text deals with procedural and operational certifications rather than direct impacts or governance related to AI, it does not lend itself strongly to the categories defined. Thus, the relevance varies individually in each category, but none emerge as extremely relevant.


Sector:
Government Agencies and Public Services (see reasoning)

The document relates to the Government Agencies and Public Services sector, as it outlines the operational standards and criteria related to the National Weather Service, which is a government agency involved in public service. It emphasizes modernization efforts that pertain directly to weather forecasting and public safety. However, the references to automation and system integration do not explicitly tie into the other sectors well, particularly areas like Healthcare or Judicial Systems, leading to lower relevance scores for those categories.


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

Summary: The bill specifies requirements for timely claims payment under Medicaid, mandating processing deadlines and conditions for waivers, aiming to enhance efficiency and accountability in healthcare reimbursement.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The provided text mainly discusses the timely processing of claims within the context of Medicaid regulations and does not explicitly mention Artificial Intelligence, algorithms, or machine learning. However, it does reference 'automated claims processing and information retrieval systems' in relation to waivers, which could relate to the automation aspect of AI. The references are general and do not deeply engage with AI's implications or governance, making the connection to AI very limited. Thus the categories will score lower due to a lack of relevance directly towards AI. Overall, it could be argued that there is an understanding of automation, but it does not delve into AI specifics. Therefore, Social Impact receives a slightly elevated score due to the implications of automation in services, though it is still overall low for all categories.


Sector:
Government Agencies and Public Services (see reasoning)

The text does not predominantly address any specific sector in a detailed manner either. There is mention of healthcare-related claims, which ties it tangentially to the Healthcare sector; however, it does not engage with AI systems within this sector in any meaningful way. Other sectors such as Government Agencies and Public Services may have some relevance given that it relates to Medicaid and claims processing, but the text lacks a clear exploration of AI's impact on any of the defined sectors. Hence, scores are low across the board.


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

Summary: The bill mandates clear disclosures at automated teller machines (ATMs) regarding fees, error resolution rights, and consumer liabilities for unauthorized transactions, aiming to enhance transparency and consumer protection.
Collection: Code of Federal Regulations
Status date: Jan. 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text primarily addresses regulations concerning automated teller machines (ATMs) and consumer transactions related to financial services, specifically focusing on disclosures, error resolution, and liabilities connected to electronic fund transfers. The content does not reference any AI-specific terms or technologies; instead, it revolves around operational standards for ATMs and financial institution practices. Therefore, the relevance to the AI-related categories is minimal as there are no discussions about AI's role, impact, or governance within the financial system described.


Sector: None (see reasoning)

The text discusses regulations related to automated teller machines, which relates primarily to the financial sector, specifically concerning disclosures and transaction processes. However, it does not touch upon AI applications or regulations in the context of AI's influence on these processes. There is no mention of AI utilization in government operations or public services, nor any incorporation of AI in monetary transactions, which might typically link it to the Government Agencies and Public Services sector. Overall, the absence of AI relevancy results in low categorization scores across sectors.


Keywords (occurrence): automated (7) show keywords in context

Summary: The bill formalizes a system for scheduling Senate committee meetings and hearings, requiring notifications to a designated office for publication in the Congressional Record to enhance transparency.
Collection: Congressional Record
Status date: Sept. 13, 2023
Status: Issued
Source: Congress

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

The text outlines upcoming Senate committee meetings, the scheduling of which includes a specific focus on artificial intelligence in financial services. This indicates a legislative interest in the implications of AI, thus connecting to the categories defined. Social Impact is relevant due to the implications AI could have on society, economy, and ethical considerations. Data Governance is relevant for the use of data in AI systems, especially in a financial context. System Integrity is touched upon by the emphasis on ensuring secure and transparent governance in the use of AI within financial services. Robustness could be considered relevant as it pertains to performance benchmarks yet the main focus here is not directly on performance metrics. Overall, the upcoming hearings suggest significant legislative intent regarding AI, providing relevancy across categories, particularly Social Impact and Data Governance which directly deal with societal implications and data management in AI systems.


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

The text explicitly mentions an upcoming hearing on artificial intelligence in financial services, which directly links to the sector of Private Enterprises, Labor, and Employment. This sector encompasses legislation that looks at the effects of AI on businesses and the economy. Although there's also a mention of AI's implications for national security and emerging threats under Homeland Security, the primary relevance remains within the financial services sector. The Government Agencies and Public Services is also relevant due to the broad potential use of AI in government functions articulated here, although it is less specific. The other sectors are not addressed by the text, particularly not touching on Politics and Elections, Judicial System, Healthcare, Academic and Research Institutions, International Cooperation, Nonprofits or Hybrid sectors.


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

Summary: The bill is the National Defense Authorization Act for Fiscal Year 2024, which authorizes funding for military activities, personnel, and defense initiatives across various branches of the U.S. Armed Forces.
Collection: Congressional Record
Status date: July 19, 2023
Status: Issued
Source: Congress

Category:
System Integrity
Data Robustness (see reasoning)

The text discusses various aspects of military activities and appropriations related to artificial intelligence, particularly in Subtitle D where it mentions the use of automation and artificial intelligence for shipyard optimization, and in Subtitle B of Title II where it includes an update plan for artificial intelligence. Given the mention of these AI-related initiatives, the text is especially relevant to System Integrity and Robustness, focusing on the implementation and development of AI technologies for military purposes. However, it does not explicitly deal with social impacts or data governance strategies associated with these technologies, which makes those categories less relevant.


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

The text is explicitly related to Government Agencies and Public Services considering it details appropriations and strategic plans regarding the Department of Defense and its operations, including the integration of AI technologies. It has moderate relevance to the Judicial System for its mention of compliance, as decisions may involve legal frameworks, but they are implicit throughout the military domain. There is no mention of healthcare or direct implications for nonprofits, labor issues, or academic institutions, making those sectors less relevant.


Keywords (occurrence): artificial intelligence (101) machine learning (14) automated (21) show keywords in context

Summary: The DOE and USDA Interagency Research Act promotes collaborative research between the Department of Energy and the Department of Agriculture to enhance agricultural practices, carbon storage, and technology development.
Collection: Congressional Record
Status date: Dec. 4, 2023
Status: Issued
Source: Congress

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

The portions of the text that discuss machine learning and artificial intelligence within the context of agricultural and energy research demonstrate their potential to optimize various processes. Such integration indicates a relevance to the societal impacts of these technologies on agriculture and energy sectors, particularly in enhancing efficiency and sustainability. Additionally, data integration methods and initiatives aimed at interagency cooperation suggest considerations for data governance, particularly when it comes to managing and sharing agricultural, environmental, and economic datasets. System integrity is relevant due to mentions of security and compliance with Federal rules in accessing data, while robustness appears to align with the research and development aspects that may set benchmarks for AI applications in the respective fields. Overall, the text highlights a multifaceted integration of AI, algorithmic processes, and cross-agency collaboration, justifying scores across all categories.


Sector:
Government Agencies and Public Services
Academic and Research Institutions
Hybrid, Emerging, and Unclassified (see reasoning)

The text pertains specifically to the intersection of AI technologies with agriculture and energy through departments and agencies involved in these sectors. The use of machine learning and AI for precision agriculture, carbon storage, and energy optimization align directly with the goals of enhancing public services in agriculture and energy sectors. Therefore, it deserves high scores in these relevant sectors. Additionally, because the bill provides a framework for interagency collaboration and research development, it also identifies a link to government agencies that could leverage AI more effectively. Legislative efforts in maximizing technology usages within agriculture positions it as highly relevant to that sector as well. The text does not specifically address other sectors such as healthcare or judicial, which would receive lower scores.


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

Summary: H.R. 6391 mandates the Department of Homeland Security to report to Congress on emerging technologies for enhancing situational awareness at U.S. borders, assessing current use, capability gaps, and costs.
Collection: Congressional Record
Status date: Nov. 13, 2023
Status: Issued
Source: Congress

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

The text explicitly mentions 'artificial intelligence' and 'automation', indicating a legislative focus on technologies that can enhance border security. This touches on societal implications (Social Impact), data handling protocols (Data Governance), and the integrity of these systems (System Integrity). However, there is no direct emphasis on performance evaluation benchmarks (Robustness). Therefore, the highest relevance is to Social Impact, with moderate relevance to Data Governance and System Integrity due to the implications of using AI and automation technologies in a security context.


Sector:
Government Agencies and Public Services (see reasoning)

The mention of the Department of Homeland Security and technologies for border security primarily relates to Government Agencies and Public Services as it involves the application of AI in governmental operations aimed at enhancing overall public service effectiveness. While there are aspects that could pertain to Law Enforcement, the text does not directly deal with judicial or healthcare contexts, nor does it pertain to the academic or nonprofit sectors. Therefore, the highest relevance is assigned to Government Agencies and Public Services, with minimal relevance to other sectors.


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

Summary: The bill establishes guidelines for assessing and mitigating penalties for Customs violations, detailing amounts and procedures based on the severity of violations and providing considerations for small businesses and non-commercial conduct.
Collection: Code of Federal Regulations
Status date: April 1, 2023
Status: Issued
Source: Office of the Federal Register

Category: None (see reasoning)

The text discusses customs regulations and penalty assessments corresponding to violations relating to customs business and does not explicitly address any AI concepts such as Artificial Intelligence, algorithms, or any related terminology. Thus, it does not relate to the social impact or governance of AI. The focus on penalties for fraud, negligence, and ensuring compliance with business regulations indicates it may have implications for system integrity and robustness in terms of data handling, but these concepts are generally tied to customs laws. However, there are no direct mentions or connections to how AI systems manifest in customs or regulatory practices, so the relevance remains low across all categories. Overall, considering the legislative intent concerning customs oversight without AI influence, I score all categories equally low.


Sector: None (see reasoning)

The text pertains primarily to customs regulations rather than the strategic deployment of AI in governmental operations, judicial systems, or other defined sectors such as healthcare or employment. While customs practices may interact with certain sectors, none are directly focused on the nuances of AI usage or implications for sectors defined here. The absence of any context in the text concerning politics, public services, or the criminal justice framework means that relevance to the specified sectors is minimal. Thus, the categorization yields a score of 1 across all sectors.


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

Summary: The bill addresses concerns about the impact of artificial intelligence on election security, urging immediate discussions and measures to prevent AI from undermining democratic processes and elections.
Collection: Congressional Record
Status date: Nov. 8, 2023
Status: Issued
Source: Congress

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

The text discusses the impact of Artificial Intelligence (AI) on elections, emphasizing the need for guardrails to prevent misinformation and manipulation through AI technologies. This makes it highly relevant to the Social Impact category, as it addresses consequential issues such as the impact on democracy, the potential for bias in political communication, and consumer protections against AI-generated misinformation. The Data Governance category is also relevant since the management of data used in AI systems for political ads aligns with the need for accountability and transparency. System Integrity is relevant due to the importance of ensuring that AI systems operate securely and transparently in the electoral process. Robustness is of moderate relevance since the need for benchmarks and standards for AI performance in political scenarios is alluded to but not explicitly detailed in the text.


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

The text is primarily focused on the implications of AI within the context of Politics and Elections, making that sector highly relevant due to the direct discussion about safeguarding electoral integrity against AI's potential misuses. While other sectors like Government Agencies and Public Services may have implications, the primary focus remains on the electoral process, thus receiving lower scores. The Judicial System, Healthcare, Private Enterprises, Academic Institutions, International Standards, Nonprofits, and Hybrid sectors do not have explicit mentions in the text, making them less relevant.


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

Summary: The bill establishes a cost recovery fee program for fishing Aleutian Islands pollock. It mandates fee submissions, payment methods, and standard pricing while outlining penalties for non-compliance.
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 revolves around the cost recovery program related to Aleutian Islands pollock, detailing responsibilities and operational procedures for fee submission and value determination. It lacks any mention of AI-specific topics such as algorithms, automation, or machine learning. While certain components could indirectly involve technology, there is no explicit link to AI or its impact or governance. Therefore, all categories related to AI are assessed as not relevant.


Sector: None (see reasoning)

The text is focused on fisheries management and cost recovery related to the Aleutian Islands pollock, with no discussion of AI applications in any sector such as politics, government services, or healthcare. There are no provisions relating to the use of AI by government agencies, nor implications regarding its use in public services or regulatory contexts. Consequently, all sectors are rated as not relevant.


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