5057 results:


Summary: The bill sets minimum technical standards for money and credit handling in Class II gaming systems, ensuring secure credit acceptance, redemption, and compliance with financial reporting requirements.
Collection: Code of Federal Regulations
Status date: April 1, 2021
Status: Issued
Source: Office of the Federal Register

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

Summary: The bill outlines regulations for non-voice, non-geostationary satellite systems sharing spectrum with NOAA meteorological satellites, ensuring protection against interference in specified frequency bands. It aims to coordinate operations and prevent harmful interference.
Collection: Code of Federal Regulations
Status date: Oct. 1, 2021
Status: Issued
Source: Office of the Federal Register

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

Description: To provide for the future information technology needs of Massachusetts
Summary: The "FutureTech Act of 2024" allocates $1.23 billion for Massachusetts' information technology improvements, enhancing cybersecurity, healthcare, education, and municipal services to better serve residents and streamline state operations.
Collection: Legislation
Status date: Jan. 10, 2024
Status: Introduced
Last action: New draft substituted, see H4642 (May 15, 2024)

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

The text discusses the FutureTech Act, which encompasses various aspects of information technology development in Massachusetts. The AI-related sections specifically mention funding for AI projects and the implementation of AI and machine learning systems for state agencies. This clearly indicates a focus on the societal impacts of AI (e.g., enhancing public services and efficiency) and implies a need for oversight and governance regarding data usage in these systems. Thus, there is a significant relevance to both the Social Impact and Data Governance categories, suggesting strong considerations around the implications of AI on community dynamics and the responsibilities tied to managing information technology and data. The calls for security and efficiency also indicate a relevant connection to System Integrity, while benchmarks related to technology performance hint at potential relevance to Robustness, although possibly to a lesser extent. Overall, the legislation is deeply connected to the role and implications of AI in state governance and service provision.


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

The text addresses various sectors, including government operations and public services directly. It discusses the implementation of AI and machine learning within state agencies, enhances user experience across governmental services, and promotes transparency and efficiency in public service delivery. The work with municipal fiber broadband infrastructure also implicates government efficiency and citizen engagement. However, it does not strongly center on sectors like healthcare or judicial systems, which can lead to lower scores in those areas. The focus on AI applications broadly affects multiple facets of society, including economic aspects related to labor and employment, which could also connect to Private Enterprises. Given these observations, there are strong connections to Government Agencies and Public Services, with moderate to slight relevance to other sectors.


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

Description: A bill to establish protections for individual rights with respect to computational algorithms, and for other purposes.
Summary: The Artificial Intelligence Civil Rights Act of 2024 aims to protect individuals' rights against discrimination by computational algorithms, requiring evaluations and accountability for their deployment and use in various sectors.
Collection: Legislation
Status date: Sept. 24, 2024
Status: Introduced
Primary sponsor: Edward Markey (2 total sponsors)
Last action: Read twice and referred to the Committee on Commerce, Science, and Transportation. (Sept. 24, 2024)

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

This legislation explicitly addresses the impact of computational algorithms, especially in relation to civil rights and discrimination. AI, being heavily involved in algorithmic decision-making, is directly pertinent to concerns about fairness and bias. It helps protect individuals from algorithmic discrimination, thus making it highly relevant to the Social Impact category. In addition, it discusses pre-deployment evaluations of algorithms, which relates to System Integrity via the provisions ensuring oversight and control over the algorithms deployed. The mention of standards for algorithms and evaluations directly links to Robustness concerning performance and accountability of AI systems. Data Governance is also relevant as it encompasses the management of data used by algorithms with provisions for user rights and protections. Therefore, overall relevance is high across all categories, with explicit references to AI and algorithms necessitating further scrutiny and legislation.


Sector:
Politics and Elections
Government Agencies and Public Services
Judicial system
Healthcare
Private Enterprises, Labor, and Employment
Academic and Research Institutions
Nonprofits and NGOs (see reasoning)

The text is not limited to one sector but spans multiple contexts where AI and algorithms have significant influence. For Politics and Elections, it features provisions that directly relate to electoral processes, such as voting and voter registration, in connection with discriminatory practices. Similarly, the Healthcare section is relevant due to mentions of healthcare-related decisions influenced by algorithms. Regarding Government Agencies and Public Services, the bill discusses how algorithms affect access to government benefits and legal services. The impacts on Private Enterprises, Labor, and Employment are also clear with respect to algorithms' roles in hiring and employee management. Also touching on Judicial Systems, it considers the justice implications of algorithmic discrimination. Academic and Research Institutions may engage with this through algorithmic fairness studies and impact evaluations. Therefore, the text is broadly relevant across many sectors with significant implications for how AI is applied in various domains.


Keywords (occurrence): artificial intelligence (5) machine learning (1) algorithm (128) show keywords in context

Summary: The bill enhances Congressional notification requirements for arms sales under the Arms Export Control Act, ensuring transparency and oversight regarding military transactions, particularly involving Egypt's military modernization efforts.
Collection: Congressional Record
Status date: Sept. 17, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

The text primarily addresses the notification of arms sales, focusing on technological specifications and military agreements rather than any significant discussion on AI, automated systems, or related frameworks. The mention of 'Automated Communication Engineering Software' hints at automation, but it's not comprehensive enough to have a significant impact aligned with the category definitions. Overall, the text lacks relevance regarding the social implications of AI, data governance, system integrity, or any robustness associated with AI evaluations.


Sector: None (see reasoning)

The text does not delineate any aspects of AI related to the specified sectors such as politics, government, healthcare, etc. Its focus is primarily on defense sales and technological specifications for military equipment without addressing AI regulations or implications directly impacting any of the sectors mentioned. The only relevant mention is of automated communication software, which lacks context and significance to be categorized within any specific sector.


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

Description: An Act relating to artificial intelligence; requiring disclosure of deepfakes in campaign communications; relating to cybersecurity; and relating to data privacy.
Summary: SB0177B mandates disclosure of deepfakes in election communications, regulates AI use by state agencies, and restricts personal data transfer between agencies, ensuring transparency and accountability.
Collection: Legislation
Status date: Jan. 16, 2024
Status: Introduced
Primary sponsor: Shelley Hughes (sole sponsor)
Last action: FIN REFERRAL ADDED AFTER JUD (April 24, 2024)

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

The document is primarily focused on the regulation of deepfakes, the use of AI by state agencies, and data privacy. In this context, the legislation directly addresses various social impacts through the deepfake disclosure requirements, which aim to promote transparency in political communications and mitigate misinformation. It highlights accountability for AI-driven decisions, pointing towards potential biases in AI systems, especially in the context of election-related communications. Furthermore, the provisions concerning data transfer among state agencies touch on the implications for personal privacy, making the social impact very relevant. Data governance is also significantly involved due to the detailed provisions about the management and privacy of individual data. This includes frameworks for consent, impact assessments, and regulations regarding AI usage in state agencies, indicating a strong focus on ensuring data protection and addressing biases in data. System integrity pertains to the oversight and accountability of AI systems employed by state agencies, which is an inherent part of the Act's requirements. Robustness is relevant but less so than the other categories, as the emphasis is more on implementation and oversight without explicit mention of new performance benchmarks or standards for AI compliance. Overall, the legislation provides a comprehensive view of AI implications in multiple facets, particularly addressing social concerns, data accuracy, and system accountability.


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

The text has direct implications for multiple sectors. In the realm of Politics and Elections, the bill explicitly addresses the use of AI and the regulation of deepfakes in election communications, establishing regulatory measures for transparency. Government Agencies and Public Services are also heavily featured, with mandatories for state agencies to use generative AI responsibly, undergo impact assessments, and comply with data privacy protocols. The scope of AI in these agencies indicates a framework geared towards enhancing public services through responsible AI application. The Judicial System is indirectly referenced through the civil liability for harm caused by violations, suggesting potential legal implications and appeals processes. Healthcare does not apply, as there are no references to AI applications in this sector. Additionally, while there may be effects on Private Enterprises, Labor, and Employment due to the requirements of transparency in AI usage, this is not the primary focus of the legislation. The provisions do not specifically address the sector of Academic and Research Institutions. Therefore, the legislation can be scored as highly relevant to Politics and Elections, and Government Agencies and Public Services, with moderate relevance to the Judicial System.


Keywords (occurrence): artificial intelligence (12) machine learning (1) deepfake (7) algorithm (1) show keywords in context

Description: Requires certain disclosures by automobile insurers relating to the use of telematics systems in determining insurance rates and/or discounts.
Summary: This bill mandates transparency for automobile insurers using telematics systems in pricing, requiring disclosures on risk factors, testing for discrimination, and consumer access to collected data.
Collection: Legislation
Status date: May 1, 2024
Status: Introduced
Primary sponsor: Charles Lavine (sole sponsor)
Last action: referred to insurance (May 1, 2024)

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

The legislation focuses on the use of telematics systems, which involve monitoring, storing, and transmitting data related to driver behavior and vehicle performance. The text explicitly mentions 'algorithm' in the context of how insurers and third-party developers must disclose their scoring methodologies and algorithm connections to risk. Furthermore, it discusses ensuring that the algorithms do not lead to discrimination against protected classes. This highlights a societal impact (related to fairness and discrimination) as well as a concern for the integrity and performance of the systems being utilized. Therefore, both the Social Impact and System Integrity categories are highly relevant. Data Governance is moderately relevant due to data collection and access provisions, and Robustness is less relevant as it focuses less on performance benchmarking and standards for AI systems.


Sector:
Government Agencies and Public Services (see reasoning)

The text relates significantly to Government Agencies and Public Services, as it involves the regulation of insurance companies in their use of telematics systems, which are likely to be employed in public and privately illustrated insurance landscapes. The content does not directly pertain to Political and Elections, Judicial System, Healthcare, Private Enterprises, Labor and Employment, Academic and Research Institutions, International Cooperation and Standards, Nonprofits and NGOs, or Hybrid, Emerging, and Unclassified sectors, making this section of relevance quite limited.


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

Description: Enacts the legislative oversight of automated decision-making in government act (LOADinG Act) to regulate the use of automated decision-making systems and artificial intelligence techniques by state agencies.
Summary: The LOADinG Act regulates automated decision-making systems in New York State agencies, ensuring human oversight and impact assessments to protect individual rights and prevent discrimination.
Collection: Legislation
Status date: Dec. 21, 2024
Status: Passed
Primary sponsor: Kristen Gonzalez (16 total sponsors)
Last action: APPROVAL MEMO.97 (Dec. 21, 2024)

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

The LOADinG Act primarily focuses on the oversight of automated decision-making systems and AI techniques utilized by state agencies, emphasizing accountability and ethical considerations in their application. The act ensures that these systems, particularly those affecting individual rights and public welfare, undergo impact assessments regarding potential biases and discrimination. This directly relates to the Social Impact category, as it mandates frameworks to assess and mitigate negative consequences of AI applications on society. The relevance to Data Governance is also significant because it outlines requirements for data handling, including impact assessments that consider biases and privacy. Further, the act prescribes methods for maintaining system integrity through mandated human review and oversight, making it relevant to System Integrity as well. Robustness is less explicitly covered, but the emphasis on audits and impact assessments contributes to a general framework of performance validation in automated systems. Overall, the act’s focus on ethical oversight and the protection of civil liberties makes it significantly relevant to these categories.


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

The LOADinG Act specifically addresses the use of automated decision-making systems within state government agencies, making it very relevant to the Government Agencies and Public Services sector. It details regulations for their application, which directly impacts public service delivery and oversight mechanisms. While there could be connections to other sectors such as Healthcare or Private Enterprises, they are less explicitly addressed in the text. The act's focus remains largely on state responsibilities, decision-making impacts on individuals, and ethical concerns around AI use in government operations. Thus, the strongest relevance is to the Government Agencies and Public Services sector.


Keywords (occurrence): artificial intelligence (2) machine learning (1) automated (43) show keywords in context

Summary: The bill mandates Congressional notification for specific arms sales, ensuring transparency and oversight, particularly regarding military support to allies like Saudi Arabia.
Collection: Congressional Record
Status date: Nov. 20, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

The text does not explicitly mention any aspects of Artificial Intelligence such as algorithms, machine learning, or automated decision-making. It primarily focuses on arms sales notifications under the Arms Export Control Act, detailing the specifics of military equipment being sold to Saudi Arabia. Since the content revolves around traditional defense materials and notifications without any AI-related implications, it is determined that the legislation does not relate to AI, and thus, there is no relevance to any of the four categories.


Sector: None (see reasoning)

The text concerns arms sales and notifications related to military enhancements and does not pertain to the use of AI in any of the specified sectors. There are no references to political campaigning, government agency operations, judicial matters, healthcare technology, private business regulations, academic research, international standards, or nonprofit activities. Therefore, it is concluded that this text is irrelevant to all nine sectors.


Keywords (occurrence): automated (1)

Summary: The Equal Treatment of Public Servants Act of 2023 aims to amend Social Security by replacing the windfall elimination provision, ensuring fairer benefit calculations for public servants with noncovered employment, addressing longstanding inequities for these workers.
Collection: Congressional Record
Status date: Nov. 12, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

The text primarily discusses changes to social security benefits and adjustments impacting public servants; however, it does not contain explicit references or implications related to artificial intelligence and its effects on society, data governance, system integrity, or robustness. As a result, it is not significantly relevant to any of these categories.


Sector: None (see reasoning)

The text focuses on social security legislation and public service employment rather than specific applications of AI in any of the identified sectors. Therefore, it is not relevant to politics, government services, healthcare, or any other of the specified sectors concerning AI regulation and use.


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

Summary: The "Bring Our Heroes Home Act" aims to expedite the identification, declassification, and public disclosure of records related to missing Armed Forces and civilian personnel, enhancing transparency and historical preservation.
Collection: Congressional Record
Status date: Sept. 17, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

The text does not contain any explicit references to AI, its applications, or its ethical impacts on society. It focuses on issues related to military personnel records and the processes to ensure their declassification and public access. The legislation discusses oversight and transparency mechanisms but does not pertain to AI technologies, thus making it irrelevant for all categories related to AI.


Sector: None (see reasoning)

The text primarily concerns military records and their management, with no mention of AI-related sectors or technologies. Therefore, it holds no relevance to any of the nine sectors such as Politics and Elections or Government Agencies and Public Services, as it focuses instead on archival practices and legislative oversight.


Keywords (occurrence): artificial intelligence (1)

Description: To provide for the future information technology needs of Massachusetts.
Summary: The bill allocates $1.235 billion in bonds for enhancing Massachusetts' information technology infrastructure and cybersecurity, aiming to improve state services, broadband access, and government efficiency.
Collection: Legislation
Status date: May 15, 2024
Status: Introduced
Primary sponsor: House Committee on Ways and Means (sole sponsor)
Last action: Published as amended, see H4648 (May 15, 2024)

Category:
Societal Impact
Data Governance (see reasoning)

The text discusses legislation related to future information technology needs in Massachusetts, specifically mentioning initiatives that include 'artificial intelligence and machine learning systems' aimed at improving the efficiency and delivery of state services. In this context, it is essential to assess how this legislation is connected to the various categories. 1. **Social Impact** - This category is somewhat relevant because the bill addresses the use of AI in improving public services, which can have a direct impact on citizens. However, it does not delve into issues like discrimination, misinformation, or consumer protections in AI applications. Therefore, I assign it a score of 3. 2. **Data Governance** - The legislation mentions data security improvements and the need for accurate data management in relation to AI systems, indicating some relevance to data governance concerns. However, it does not provide extensive detail on addressing biases or inaccuracies in data sets, thus receiving a score of 3 for moderate relevance. 3. **System Integrity** - The text refers to 'data and cyber-security improvements,' which relate to the integrity of systems on which AI operates. Although it touches on these aspects, there is limited mention of transparency and oversight for AI processes, leading to a score of 2 for slightly relevant. 4. **Robustness** - There is no explicit mention of developing benchmarks for AI performance or regulatory compliance measures in the text, making this category not relevant at all and scoring a 1.


Sector:
Government Agencies and Public Services (see reasoning)

The text addresses the application of AI within the state's administrative processes and public service improvements. Each sector will be evaluated for specific phrases or implications of AI's role within that context. 1. **Politics and Elections** - The text does not address AI in the context of political campaigns or electoral processes, resulting in a score of 1 for no relevance. 2. **Government Agencies and Public Services** - The bill is focused explicitly on how AI systems will enhance public services and improve interactions between citizens and state agencies. This directly aligns with this sector and merits a score of 5, indicating extreme relevance. 3. **Judicial System** - There is no mention of AI's role in legal contexts or the judicial system, hence a score of 1 for no relevance. 4. **Healthcare** - The text does not touch on AI applications in healthcare, leading to a score of 1 for no relevance. 5. **Private Enterprises, Labor, and Employment** - The legislation does not discuss AI's impact on the business sector or labor markets, resulting in a score of 1 for no relevance. 6. **Academic and Research Institutions** - The text provides no reference to academic usage or regulation of AI, hence a score of 1 for no relevance. 7. **International Cooperation and Standards** - There is no indication of international dialogue or standards regarding AI within the text; thus, it scores a 1. 8. **Nonprofits and NGOs** - This sector is not referenced in relation to AI, leading to a score of 1. 9. **Hybrid, Emerging, and Unclassified** - The bill does not fit into a hybrid or unclassified sector regarding AI adoption, resulting in a score of 1.


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

Summary: The bill primarily involves various executive communications to the Senate, including reports from federal agencies on regulations related to agriculture, the environment, cybersecurity, and national emergencies.
Collection: Congressional Record
Status date: Nov. 12, 2024
Status: Issued
Source: Congress

Category: None (see reasoning)

The text does not contain any explicit references to AI or its related terminology such as Artificial Intelligence, Algorithms, Machine Learning, etc. It primarily discusses communications from various governmental agencies concerning regulations and policies related to agriculture, environmental protection, cybersecurity, and national emergencies. Therefore, it has no relevance to any category.


Sector: None (see reasoning)

Similarly, there are no references to AI in the context of politics, government operations, or any other specific sector that would indicate an application or regulation of AI within this text. The communications mainly focus on procedural reports, regulatory updates, and the status of various ongoing governmental activities relevant to the listed agencies. Thus, no sector is relevant.


Keywords (occurrence): artificial intelligence (1)

Summary: The bill recognizes ITA International LLC for their innovative use of SBIR-developed technology, enhancing government and industry solutions, particularly in the Department of Defense, and improving efficiency through data analytics.
Collection: Congressional Record
Status date: Nov. 12, 2024
Status: Issued
Source: Congress

Category:
Societal Impact
Data Governance (see reasoning)

The text discusses the contributions of ITA International in developing analytic algorithms and AI techniques, specifically in their work with decision support tools for the Navy and the implications for government operations. As it highlights the benefits of AI in decision making and efficiency within defense operations, this ties significantly to the category of Social Impact as it demonstrates how AI can improve outcomes within the military context, impacting readiness and resource allocation. Data Governance is also relevant as it addresses the management of data through analytic algorithms, though less focused on regulatory aspects. System Integrity is touched upon through mentions of security and operational effectiveness, but less explicitly. Robustness is less applicable as it does not cover benchmarking or audits. The strongest relevance is with Social Impact due to the direct mention of AI applications in government.


Sector:
Government Agencies and Public Services (see reasoning)

The text centers around ITA International's application of AI in government, specifically within the Department of Defense. This strong focus on the transition of technology to government use directly aligns with the sector of Government Agencies and Public Services, highlighting how AI can improve efficiency and decision making in governmental operations. While there is a broad discussion of private enterprise methods, the primary emphasis remains on government applications, thus less relevance to sectors like Healthcare, Private Enterprises, or Academic Institutions. Therefore, Government Agencies and Public Services is rated the highest, with minor relevance to others only noted indirectly.


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

Description: Requires artificial intelligence companies to conduct safety tests and report results to Office of Information Technology.
Summary: The bill mandates artificial intelligence companies in New Jersey to conduct annual safety tests on their technologies and report the findings to the Office of Information Technology, ensuring compliance with safety standards and bias assessments.
Collection: Legislation
Status date: Oct. 7, 2024
Status: Introduced
Primary sponsor: Troy Singleton (sole sponsor)
Last action: Introduced in the Senate, Referred to Senate Commerce Committee (Oct. 7, 2024)

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

This text emphasizes the need for safety tests to assess AI technologies, which aligns with multiple aspects of AI's societal impact, data governance, system integrity, and robustness. The expectation of annual reporting and establishing minimum requirements suggests a strong focus on not only the social implications of AI (such as biases and cybersecurity threats) but also the effectiveness and safety of AI systems in general. Consequently, the relevance to 'Social Impact' is significant due to its implications on fairness, safety, and accountability. 'Data Governance' faces high relevance because it requires scrutiny over data sources, biases, and legal compliance, crucial for maintaining the integrity of AI data. Furthermore, the legislation directly addresses the safety and integrity of AI systems, suitable for 'System Integrity.' Lastly, the structured testing and reporting measures align highly with 'Robustness,' aimed at developing benchmarks for AI performance and safety. Therefore, the text resonates with all four categories, particularly emphasizing the necessity of regulated AI development and deployment.


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

The text lays out regulations concerning AI technologies, which indicates relevance across several sectors. In 'Politics and Elections,' it doesn't directly address issues related to political processes, thus scoring lower. 'Government Agencies and Public Services' stands relevant because it involves oversight from state authorities, suggesting implications for public sector technology management. 'Judicial System' is moderate as compliance testing may be indirectly related to legal review but not explicitly stated. 'Healthcare' makes no direct mention, resulting in a low score. 'Private Enterprises, Labor, and Employment' applies because the legislation affects business practices among AI firms; hence, some relevance persists. For 'Academic and Research Institutions,' although AI research might be influenced, it's not central in this text, leading to lower relevance. 'International Cooperation and Standards' doesn’t apply as there's no mention of international collaboration. 'Nonprofits and NGOs' is also not relevant due to a lack of specific mention. Lastly, 'Hybrid, Emerging, and Unclassified' holds a degree of relevance due to the evolving nature of AI applicability, but it ranks lower than the others. Ultimately, significant importance is placed on government oversight of AI usage in public services, impacting 'Government Agencies and Public Services' and 'Private Enterprises, Labor, and Employment' significantly.


Keywords (occurrence): artificial intelligence (23) machine learning (1) show keywords in context

Summary: The bill outlines the committee meetings scheduled for September 18, 2024, addressing various issues like food programs, tax reforms, cybersecurity, and public safety, among others.
Collection: Congressional Record
Status date: Sept. 17, 2024
Status: Issued
Source: Congress

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

This text discusses several legislative items in Congress that include provisions related to the use of artificial intelligence (AI) by the Federal Government. Given that AI is mentioned in the context of procurement, development, and use by government entities, it directly relates to questions of social impact, data governance, system integrity, and robustness of AI systems. The legislative focus seems to imply efforts to ensure AI systems are safe, responsible, and agile. Consequently, this would apply broadly across multiple AIrelated categories.


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

The presence of provisions related to the use of AI by the Federal Government inherently links this text to the sector of Government Agencies and Public Services. Additionally, there are mentions of implications for cybersecurity, which connect to Judicial System concerns due to the nature of security and law enforcement. The discussions on AI suggest potential applications across various sectors, but the most direct relevance is to government services and operations.


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

Summary: The bill honors Aditi Muthukumar for winning Rookie of the Year in the 2024 Congressional App Challenge for her app, SafeSpace, which supports youth mental health.
Collection: Congressional Record
Status date: Nov. 20, 2024
Status: Issued
Source: Congress

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

The text mentions a trained machine learning model used in Aditi Muthukumar's app, which pertains to AI. Therefore, the relevance of the categories can be assessed based on how they relate to this application of AI. Social Impact is relevant because the app addresses mental health resources for young people, which affects societal well-being. Data Governance is also relevant due to the use of machine learning, which typically involves data management practices to ensure the accuracy and safety of the information being processed. System Integrity may have some relevance as the app must maintain security regarding user data, but it’s not explicitly mentioned. Robustness is less relevant here as the text does not discuss performance benchmarks or compliance standards concerning the app. Hence, Social Impact and Data Governance score higher while System Integrity scores moderately and Robustness scores lower due to lack of mention of relevant points.


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

The text does not refer directly to any of the specified sectors such as politics, health care, or education systems but the app has implications for mental health support in a general sense. However, the mention of an app designed for mental health resources suggests a relevance to Government Agencies and Public Services due to public health implications. There's a relationship to Academic and Research Institutions given the context of the app being developed for a STEM-focused competition, although it is less direct. Therefore, Government Agencies and Public Services may score higher, while Academic and Research Institutions receive a moderate score. All other sectors do not have enough relevance to score.


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

Description: An Act providing for civil liability for fraudulent misrepresentation of candidates; and imposing penalties.
Summary: The bill establishes civil liability and penalties for fraudulent misrepresentation of political candidates, particularly through artificially generated content. It aims to protect electoral integrity by regulating deceptive campaign advertisements.
Collection: Legislation
Status date: May 29, 2024
Status: Introduced
Primary sponsor: Tarik Khan (28 total sponsors)
Last action: Laid on the table (Sept. 23, 2024)

Category:
Societal Impact
Data Governance (see reasoning)

The text directly discusses the fraudulent use of AI-generated content for political misrepresentation, indicating its significant societal impacts, especially in elections. This fits well within the realm of social impact as it raises concerns about misinformation, accountability of content creators, and potential harm to trust in political communications. It also touches upon consumer protections regarding AI-generated media in campaign advertisements. Furthermore, the text addresses the ethical implications of using AI in political campaigns, highlighting the importance of transparency and fairness, which further solidifies its relevance to social impact. Data governance could also be relevant because of the emphasis on the proper use and disclosure of synthetic content; however, it is primarily focused on the consequences of misuse rather than data management principles. System integrity and robustness are less applicable here as they revolve around operational security and performance standards rather than the specific issues the text aims to resolve - namely, misinformation and its penalties. Overall, this piece primarily exemplifies social impact, with some relevance to data governance.


Sector:
Politics and Elections (see reasoning)

The text explicitly addresses the implications of using artificial intelligence in political campaign advertisements, particularly regarding fraudulent misrepresentation of candidates. This makes it highly relevant to the Politics and Elections sector as it sets legal frameworks for the use of AI in electoral contexts. There is no mention or discussion of AI use in government agencies, healthcare, or other sectors, which places little to no relevance there. However, the text does touch upon accountability, principles of fairness, and transparency, all of which are essential in electoral processes, hence reinforcing its strong categorization within Politics and Elections. Other sectors such as Judicial System (related to the enforcement of laws regarding AI misuse) and Private Enterprises, Labor, and Employment could arguably have slight relevance when considering the responsibilities of political committees as covered persons, but they are not the primary focus of this legislation. Thus, the text is predominantly pertinent to the Politics and Elections sector.


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

Description: License plate reader systems; civil penalty. Provides requirements for the use of license plate reader systems, defined in the bill, by law-enforcement agencies. The bill limits the use of such systems to scanning, detecting, and recording data about vehicles and license plate numbers for the purpose of identifying a vehicle that is (i) associated with a wanted, missing, or endangered person or human trafficking; (ii) stolen; (iii) involved in an active law-enforcement investigation; or (iv) ...
Summary: The bill regulates the use of license plate reader systems by law enforcement in Virginia, establishing guidelines for data usage, privacy protections, and civil penalties for violations, ensuring accountability.
Collection: Legislation
Status date: Feb. 13, 2024
Status: Engrossed
Primary sponsor: Scott Surovell (3 total sponsors)
Last action: Constitutional reading dispensed (40-Y 0-N) (Feb. 13, 2024)

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

The text explicitly discusses the use of automated high-speed cameras and computer algorithms for license plate reader systems employed by law enforcement, indicating a direct relevance to AI under the terminology of Automated systems and Algorithms. The legislation stipulates requirements for the operation of these systems, highlighting accountability, data handling, and compliance with certain standards, connecting to the categories of System Integrity (due to the regulations around oversight and access) and Social Impact (considering implications for society regarding data privacy, surveillance, and the potential for misuse). Data Governance is also relevant as the bill mandates control over data management and security measures. However, there is less emphasis on developing new AI benchmarks or performance audits directly outlined in the text, which makes Robustness less relevant.


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

The text directly relates to Government Agencies and Public Services, as it defines how government law enforcement agencies use technology (license plate readers) to gather and manage data for public safety purposes. It discusses data retention, access management, and compliance with laws, connecting directly to the operations of public services. While aspects of AI regulation could touch on Judicial System in terms of evidence admissibility, the text does not explicitly focus on the judicial implications. Other sectors like Healthcare, Political and Elections, and Nonprofits and NGOs do not find direct relevance in the context provided by this text.


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

Description: Prohibits collecting of certain costs associated with offshore wind projects from ratepayers.
Summary: This bill prohibits collecting certain costs from ratepayers associated with offshore wind projects in New Jersey, aiming to protect consumers from indirect financial burdens linked to these renewable energy initiatives.
Collection: Legislation
Status date: May 2, 2024
Status: Introduced
Primary sponsor: Paul Kanitra (sole sponsor)
Last action: Introduced, Referred to Assembly Telecommunications and Utilities Committee (May 2, 2024)

Category: None (see reasoning)

The text primarily focuses on prohibiting the recovery of certain costs related to offshore wind energy projects. It does not explicitly mention AI or technologies related to AI like algorithms, automated systems, or machine learning. Therefore, there are no relevant sections that would pertain to the regulation or impact of AI on society, data governance, system integrity, or performance benchmarks. The legislation is centered around financial obligations rather than technological implications.


Sector: None (see reasoning)

The text does not address any specific sector involving AI. As it deals with financial regulations associated with energy systems (specifically wind energy projects), it does not connect with sectors that utilize or regulate AI, such as government services, healthcare, or industries impacted by AI technologies. Thus, none of the defined sectors are applicable to the content.


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