...
Extends crime of identity theft to include fraudulent
impersonation or false depiction by means of artificial intelligence or
deepfake technology.
CURRENT VERSION OF TEXT
As introduced.
An Act concerning identity theft by means of artificial
intelligence or deepfake technology, and amending N.J.S.2C:21-17 and P.L.2003,
c...
...ends the crime of
identity theft to include fraudulent impersonation or false depiction by means
of artificial intelligence or deepfake technology. A so-called "deepfake" or,
as defined under this bill, a "false personation record," includes images,
video, sound, speech, or text generated entirely by or substantially
man...
..., speech, or text generated entirely by or substantially
manipulated using newer technology such as artificial intelligence with the
intent of making it appear, as realistically as possible, that the person being
depicted has engaged in activity or speech that did not actually occur.
Deepfakes have been used to embarrass ...
...theft to include fraudulent
impersonation or false depiction by means of artificial intelligence or
deepfake technology.
CURRENT VERSION OF TEXT
As introduced.
An Act concerning identity theft by means of artificial
intelligence or deepfake technology, and amending N.J.S.2C:21-17 and P.L.2003,
c.184.
Be It
...
...SION OF TEXT
As introduced.
An Act concerning identity theft by means of artificial
intelligence or deepfake technology, and amending N.J.S.2C:21-17 and P.L.2003,
c.184.
Be It
Enacted by the Senate and General Assembly of
the State of New Jersey:
1. N.J.S.2C:21-17 is amended
to read as follows:
2C:21-17. a...
...theft to include fraudulent impersonation or false depiction by means
of artificial intelligence or deepfake technology. A so-called "deepfake" or,
as defined under this bill, a "false personation record," includes images,
video, sound, speech, or text generated entirely by or substantially
manipulated usi...
...nation or false depiction by means
of artificial intelligence or deepfake technology. A so-called "deepfake" or,
as defined under this bill, a "false personation record," includes images,
video, sound, speech, or text generated entirely by or substantially
manipulated using newer technology such as artific...
...ic both with and without the intention of pecuniary
gain. Falsely depicting a person by means of a deepfake is tantamount to
stealing that person's identity.
Under the bill, the grading of
identity theft into crimes of the fourth, third, and second degree remains
unchanged. However, false depiction by mea...
... of the fourth, third, and second degree remains
unchanged. However, false depiction by means of a deepfake would be graded by
the number of victims affected. Thus, false depiction affecting one victim is
a crime of the fourth degree except that a second or subsequent conviction for
such an offense consti...
...mediate the economic or
reputational harm caused by a false depiction, the court may order that the
deepfake be destroyed and a public retraction be made at the defendant's
expense. In addition, the bill clarifies that any civil action for economic
restitution by a victim does not preclude a civil action f...
4160 results:
Description: Extends crime of identity theft to include fraudulent impersonation or false depiction by means of artificial intelligence or deepfake technology.
Collection: Legislation
Status date: Feb. 27, 2024
Status: Introduced
Primary sponsor: Victoria Flynn
(sole sponsor)
Last action: Introduced, Referred to Assembly Science, Innovation and Technology Committee (Feb. 27, 2024)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services
Judicial system
Hybrid, Emerging, and Unclassified (see reasoning)
Keywords (occurrence): artificial intelligence (3) deepfake (7) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
The text explicitly addresses the crime of identity theft as it relates to the use of artificial intelligence and deepfake technology. It mentions these technologies in the context of fraudulent impersonation and false depictions, making them relevant to the Social Impact category due to their potential harm to individuals and society, including misrepresentation and reputational damage. It addresses concerns like the psychological harm and societal consequences of deepfakes, clearly connecting to consumer protections and the role of AI in misinformation. Regarding Data Governance, there are implications regarding the management and protection of personal data used in identity theft situations, although it's not the primary focus. The System Integrity category is relevant as it discusses accountability measures and the intent behind these crimes, although less emphasis is placed on security measures for AI systems itself. Robustness is less applicable, as the document does not focus on benchmarks or standards for AI performance development. Overall, Social Impact is the most relevant, while Data Governance and System Integrity have some relevance but to a lesser degree. Therefore, strong relevance is noted in Social Impact, while other categories score lower due to their indirect nuance in relation to AI.
Sector:
Government Agencies and Public Services
Judicial system
Hybrid, Emerging, and Unclassified (see reasoning)
The text primarily focuses on the implications of AI and deepfake technology concerning identity theft, which mainly falls under the realm of protection against fraud and personal rights. It may touch on issues related to Politics and Elections, particularly about misinformation campaigns using deepfakes, but it is not explicitly outlined in the document. Government Agencies and Public Services could be involved to some extent in law enforcement against these technologies. The Judicial System is impacted as the law would have implications for how identity theft cases are prosecuted. However, specific references to healthcare, private enterprises, or academic sectors are not evident in the text. For International Cooperation and Standards, while AI technologies do have global implications, the document does not address international agreements or cooperation directly. Nonprofits and NGOs might be affected due to the need for awareness campaigns about the dangers of deepfakes and identity theft. Emerging and unclassified sectors may fit as this legislation addresses a new type of crime enabled by technology, but primarily, it is about existing societal issues of identity theft. Overall, there is moderate relevance to the Judicial System and Government Agencies, but less so for the other sectors.
Keywords (occurrence): artificial intelligence (3) deepfake (7) show keywords in context
Description: For legislation to establish a commission (including members of the General Court) relative to state agency automated decision-making, artificial intelligence, transparency, fairness, and individual rights. Advanced Information Technology, the Internet and Cybersecurity.
Collection: Legislation
Status date: Feb. 16, 2023
Status: Introduced
Primary sponsor: Sean Garballey
(4 total sponsors)
Last action: Accompanied a new draft, see H4024 (Aug. 3, 2023)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Judicial system (see reasoning)
Keywords (occurrence): artificial intelligence (2) machine learning (2) automated (27) algorithm (1) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text addresses the establishment of a commission dedicated to examining automated decision-making systems that utilize artificial intelligence (AI) within government operations in Massachusetts. This means it is deeply tied to societal issues surrounding AI technology, such as fairness, transparency, accountability, and individual rights, which directly aligns with the focus of the Social Impact category. The reference to evaluating existing systems and making recommendations for their use also indicates relevant prominence to the principles of data governance, especially concerning bias and fairness in AI systems. The legislation points to a structured approach to system integrity—ensuring that automated systems are auditable and transparent—and robustness through recommendations for best practices and standards. Consequently, all categories exhibit significant relevance to the AI-related portions of the text.
Sector:
Government Agencies and Public Services
Judicial system (see reasoning)
The proposed legislation is centered around governmental organizations and agencies in Massachusetts, as it specifically discusses AI and automated decision-making in relation to public services. This makes it extremely relevant to the sector of Government Agencies and Public Services, as it seeks insights and oversight on the application of AI in delivering government services. The legislation also indirectly touches upon various aspects of the Judicial System, as decisions made by automated systems can impact legal rights and due processes for individuals, but this connection is slightly weaker compared to the primary focus on government agencies. The legislation does not sufficiently engage with other sectors listed and does not present explicit ties to politics and elections, healthcare, private enterprises, academic fields, international standards, nonprofits, or hybrid sectors.
Keywords (occurrence): artificial intelligence (2) machine learning (2) automated (27) algorithm (1) show keywords in context
Description: "New Jersey Disclosure and Accountability Transparency Act (NJ DaTA)"; establishes certain requirements for disclosure and processing of personally identifiable information; establishes Office of Data Protection and Responsible Use in Division of Consumer Affairs.
Collection: Legislation
Status date: Jan. 9, 2024
Status: Introduced
Primary sponsor: Vin Gopal
(sole sponsor)
Last action: Introduced in the Senate, Referred to Senate Commerce Committee (Jan. 9, 2024)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services
Judicial system
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): machine learning (1) automated (8) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
The New Jersey Disclosure and Accountability Transparency Act (NJ DaTA) involves explicit references to AI, especially regarding 'automated decision making' and 'profiling'. The bill mandates transparency requirements for automated decision-making, which is directly relevant to the 'Social Impact' category since it stipulates consumer rights and protections related to AI. The focus on informing consumers about automated processes addresses concerns about algorithmic fairness and discrimination, positioning it strongly within this category. 'Data Governance' is also relevant due to the bill's requirements for the processing of personally identifiable information (PII) and associated data protection roles, as it outlines how data must be collected, processed, and secured, which is crucial for managing data in AI systems. 'System Integrity' pertains to the need for security measures and can be connected to the act's focus on the responsible use of technology, ensuring AI is utilized transparently and securely. The 'Robustness' category is less applicable, as there is no mention of benchmarks for AI performance or standards for compliance specific to AI development. Thus, this legislation primarily addresses social implications and data governance related to AI applications, while systemic integrity is a secondary concern.
Sector:
Government Agencies and Public Services
Judicial system
Private Enterprises, Labor, and Employment (see reasoning)
The NJ DaTA has significant implications for various sectors, particularly 'Government Agencies and Public Services', as it establishes a framework for the responsible processing of consumer data by public entities. The emphasis on data protection and rights is central to its function, particularly concerning governmental roles in data governance and consumer relations. It is also relevant to the 'Private Enterprises, Labor, and Employment' sector since it outlines how private entities collect and manage consumer data, reflecting on workplace data practices and implications for employees' rights concerning automated decisions. 'Judicial System' may have a slight connection due to provisions related to consumer rights and data governance that could intersect with legal processes. However, direct references to judicial applications of AI are not explicit. The 'Healthcare' sector receives minimal consideration; while PII and decisions based on data processing could impact healthcare data management, the bill does not emphasize healthcare-specific applications. Overall, the legislation's impact primarily resonates within public services, though it does touch on considerations for private entities.
Keywords (occurrence): machine learning (1) automated (8) show keywords in context
Description: A bill to direct the Secretary of Commerce to develop a national strategy regarding artificial intelligence consumer literacy and conduct a national artificial intelligence consumer literacy campaign.
Collection: Legislation
Status date: July 30, 2024
Status: Introduced
Primary sponsor: Mark Kelly
(2 total sponsors)
Last action: Read twice and referred to the Committee on Commerce, Science, and Transportation. (July 30, 2024)
Category:
Societal Impact (see reasoning)
Sector:
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): artificial intelligence (30) show keywords in context
Societal Impact (see reasoning)
Given the title and description of the bill, the focus is on developing a national strategy for artificial intelligence consumer literacy. This directly suggests a significant societal impact since it aims to educate and inform individuals regarding AI technologies. Therefore, the Social Impact category is relevant. However, there are no direct indications of data governance, system integrity, or robustness concerns in the absence of specifics, resulting in lower relevance for those categories.
Sector:
Government Agencies and Public Services (see reasoning)
The bill's emphasis on consumer literacy regarding artificial intelligence indicates its relevance to multiple sectors. While it doesn't explicitly mention political campaigns or government agencies, understanding AI literacy in relation to the public has implications for government agencies and public services in ensuring informed citizenry. The Private Enterprises and Academic sectors may have indirect implications through consumer education and possible inclusion in curricula or corporate training. However, without more specific applications or examples in the text, the strongest connection is to the Government Agencies and Public Services sector, as the strategy will involve government-led initiatives for consumer engagement. Other sectors like Politics and Elections, Judicial System, Healthcare, International Cooperation, Nonprofits, and the Unclassified sector do not have clear relevance in this context.
Keywords (occurrence): artificial intelligence (30) show keywords in context
Description: Establishes the Stop Addictive Feeds Exploitation (SAFE) For Kids Act prohibiting the provision of addictive feeds to minors by addictive social media platforms; establishes remedies and penalties.
Collection: Legislation
Status date: June 20, 2024
Status: Passed
Primary sponsor: Andrew Gounardes
(38 total sponsors)
Last action: SIGNED CHAP.120 (June 20, 2024)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Healthcare
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): machine learning (1) automated (1) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
The text addresses the negative impacts of addictive feeds created by social media platforms, particularly on minors, which closely aligns with concerns about the social impact of AI. The use of 'machine learning algorithms' indicates the reliance on AI technologies for personalizing these feeds, which can contribute to mental health issues among youth. The act aims to regulate these phenomena by prohibiting the provision of addictive feeds to minors, highlighting its relevance to accountability and consumer protection which further underscores its social implications.
Sector:
Healthcare
Private Enterprises, Labor, and Employment (see reasoning)
The legislation specifically targets the effects of AI-driven algorithms in social media, impacting minors' health and online safety. While it does not directly address AI in government services, healthcare, or the judicial system, it does touch on regulation of private enterprises (social media platforms). Thus, its broad implications for youth welfare and the regulation of technology in these contexts make it marginally relevant here. However, it is primarily focused on social media rather than healthcare or legal applications.
Keywords (occurrence): machine learning (1) automated (1) show keywords in context
Description: Reinserts the provisions of the bill as amended by Senate Amendment No. 1 with the following changes. Provides that each disclosing State department or agency (rather than only department) shall execute a single master data use agreement that includes all data sets and is in accordance with the applicable laws, rules, and regulations pertaining to the specific data being requested. Provides that the State department or agency may require the names of any authorized users who will access or us...
Collection: Legislation
Status date: Aug. 4, 2023
Status: Passed
Primary sponsor: Anna Moeller
(28 total sponsors)
Last action: Public Act . . . . . . . . . 103-0423 (Aug. 4, 2023)
Category:
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): automated (2) show keywords in context
Data Governance
System Integrity (see reasoning)
The text focuses on public health data and its accessibility while emphasizing data protection, privacy, and specific regulations regarding data sharing between state departments and local health authorities. However, it does not directly address social impacts of AI, such as biases or ethical implications. The lack of AI terminology diminishes the relevance to Social Impact. Similarly, while it outlines governance relating to public health data, the legislation does not delve into the nuances of data management within AI systems, making Data Governance moderately relevant. On the other hand, it does highlight safeguards and risk management concerning data security, aligning with System Integrity, albeit indirectly. Lastly, while it mentions agreements and protocols similar to those used in AI contexts, it does not specify benchmarks or standards applicable to AI, thus scoring lower in Robustness. Overall, while there are elements pertinent to governance and integrity, the text does not engage directly with AI in the broader contexts presented by the categories.
Sector:
Government Agencies and Public Services (see reasoning)
The text primarily addresses public health and the management of health data accessibility, which is closely tied to Government Agencies and Public Services, as it discusses the functions and responsibilities of state health departments and the access to health data by certified local health departments. It does not engage with the use of AI within Political and Electoral processes, nor does it address implications for the Judicial System, Healthcare as a sector in itself beyond data management, Private Enterprises, or Academic Institutions specifically. The text aligns with contexts of data governed by health services but does not explicitly reference AI regulations in those sectors. Given this focus and contextual relevance, Government Agencies and Public Services is rated higher than others.
Keywords (occurrence): automated (2) show keywords in context
Description: Creating a charter of people's personal data rights.
Collection: Legislation
Status date: Jan. 26, 2023
Status: Introduced
Primary sponsor: Shelley Kloba
(4 total sponsors)
Last action: By resolution, reintroduced and retained in present status. (Jan. 8, 2024)
Category:
Societal Impact
Data Governance (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (3) automated (5) show keywords in context
Societal Impact
Data Governance (see reasoning)
The text is primarily focused on personal data rights and privacy, particularly as they relate to the handling of personal information by entities within Washington state. It emphasizes the significance of protecting personal data that may be used in automated processes, and it addresses potential harms stemming from privacy violations, including discrimination driven by AI systems. The presence of terms such as 'algorithms' plainly relates to the Data Governance and Social Impact categories due to its emphasis on data security and the consequences of its misuse on marginalized communities. Thus, relevance to the discussed categories will vary. The System Integrity category could be only slightly relevant as it touches on oversight and obligations related to data collection and processing but doesn't explicitly outline measures for AI system integrity. The Robustness category is not explicitly relevant since benchmarks, compliance, and oversight for AI performance are not discussed.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
The text details legislation related to data privacy and personal rights in the context of Washington state. While it does not specifically mention sectors such as Healthcare or Education, it addresses issues that can closely touch upon the sectors of Government Agencies and Public Services (as it regulates entities interacting with personal data) and Private Enterprises, Labor, and Employment (due to implications for businesses handling personal information). The primary sector connections here will thus be with Government Agencies and Private Enterprises, which focused on data handling standards.
Keywords (occurrence): artificial intelligence (3) automated (5) show keywords in context
Description: Relative to strengthening Massachusetts' economic leadership
Collection: Legislation
Status date: June 5, 2024
Status: Introduced
Primary sponsor: Committee on Economic Development and Emerging Technologies
(sole sponsor)
Last action: New draft substituted, see H4789 (June 27, 2024)
Category:
Societal Impact
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Healthcare
Private Enterprises, Labor, and Employment
Hybrid, Emerging, and Unclassified (see reasoning)
Keywords (occurrence): artificial intelligence (5) show keywords in context
Societal Impact
Data Robustness (see reasoning)
The text provides funding to support the adoption and application of artificial intelligence across various sectors within Massachusetts. This indicates a strong relevance to the 'Social Impact' category, particularly regarding economic opportunities and the promotion of innovation. The text highlights the importance of leveraging AI to advance the commonwealth’s technological leadership, which aligns with social progress and technological accountability. Furthermore, it discusses job creation, which ties into both social equity and the economic benefits of adopting AI technologies. While there are mentions of funding allocations that could be relevant to data governance, system integrity, and robustness through grants aimed at technological improvement, the focus is heavily weighted towards social impacts and economic innovation. Overall, the legislation appears to address various impacts of AI on society, particularly regarding job creation and industry leadership rather than specific governance or technical integrity issues, leading to a higher score in 'Social Impact' and lower relevance in the other categories.
Sector:
Government Agencies and Public Services
Healthcare
Private Enterprises, Labor, and Employment
Hybrid, Emerging, and Unclassified (see reasoning)
The text discusses several funding allocations for technology development with explicit mentions of artificial intelligence applications primarily in economic sectors. The references to leveraging AI technologies to advance growth in sectors such as life sciences, healthcare, and education indicate a direct connection to the 'Healthcare' and 'Government Agencies and Public Services' sectors, as these are areas that will likely adopt AI for improved service delivery and innovation. The legislation aims to enhance the commonwealth's infrastructure and stimulate economic development, which relates to 'Private Enterprises, Labor, and Employment' due to the promotion of job creation through technology advancement. There are mentions of support for agricultural biotechnology, which aligns partially with 'Private Enterprises, Labor, and Employment.' However, many sectors that don’t explicitly discuss the use of AI would score lower, reflecting a moderate relevance overall. Given the broad nature of the impacts considered, the legislation constitutes strong relevance to 'Government Agencies and Public Services', 'Healthcare', and 'Private Enterprises, Labor, and Employment' while scoring lower for 'Academic and Research Institutions' or 'International Cooperation and Standards' as those connections are not clear.
Keywords (occurrence): artificial intelligence (5) show keywords in context
Description: To reauthorize wildlife habitat and conservation programs, and for other purposes.
Collection: Legislation
Status date: Dec. 20, 2024
Status: Enrolled
Primary sponsor: David Joyce
(13 total sponsors)
Last action: Presented to President. (Dec. 20, 2024)
Category:
Societal Impact
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (136) machine learning (8) automated (32) large language model (1) algorithm (1) show keywords in context
Societal Impact
System Integrity
Data Robustness (see reasoning)
The legislation primarily focuses on military activities, personnel management, and the authorization of funds for various defense programs. However, it includes specific references to artificial intelligence, such as Section 221, which addresses defining the AI workforce, and Section 225, which discusses the duties related to AI models and technologies. Given that these references indicate a clear connection to AI's role in defense strategies and personnel requirements, several categories are relevant. The strongest relevance is to 'System Integrity' due to mandates for controlling AI systems, followed closely by 'Robustness' given the focus on AI performance benchmarks and compliance. 'Social Impact' is relevant but to a lesser degree, and 'Data Governance' has weak associations without explicit connections to data management.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
This legislation is primarily related to 'Government Agencies and Public Services' as it lays out provisions for military operations, funding, and the enhancement of defense capabilities. It directly involves the Department of Defense and military personnel, making it highly relevant. There are also associations with 'Private Enterprises, Labor, and Employment' concerning workforce definitions and AI integration, but these connections are less direct. Other sectors like Healthcare and Judiciary show little to no relevance.
Keywords (occurrence): artificial intelligence (136) machine learning (8) automated (32) large language model (1) algorithm (1) show keywords in context
Description: Amends the Artificial Intelligence Video Interview Act. Makes a technical change in a Section concerning the short title.
Collection: Legislation
Status date: Feb. 2, 2023
Status: Introduced
Primary sponsor: Omar Aquino
(6 total sponsors)
Last action: Senate Floor Amendment No. 1 Pursuant to Senate Rule 3-9(b) / Referred to Assignments (June 26, 2023)
Category:
None
(see reasoning)
Sector:
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (2)
The text pertains specifically to an amendment of the Artificial Intelligence Video Interview Act. By explicitly mentioning 'Artificial Intelligence', it signifies relevance to how AI is utilized in the context of employment practices, particularly through video interviewing. However, the text does not delve into the social impact, data governance, system integrity, or robustness of AI systems or their implications. It is primarily a technical change, which limits its relevance to the broader categories. The relevance to 'Social Impact' is minimal since there are no discussions of societal implications or protections related to AI usage in video interviewing processes. The 'Data Governance' is also not applicable here since it doesn't discuss data management or accuracy in AI applications. Similarly, there are no security or oversight mandates in this context, limiting the relevance to 'System Integrity' and 'Robustness'. Therefore, while AI is mentioned, the overall applicability to these categories is weak.
Sector:
Private Enterprises, Labor, and Employment (see reasoning)
The text discusses the 'Artificial Intelligence Video Interview Act', which indicates its relevance to the employment sector specifically, as it relates to how AI is integrated into employment practices through video interviews. However, it does not address broader impacts or implications in other sectors. Other sectors such as Healthcare or Government Agencies are not mentioned or relevant here. Thus, the only relevant sector is Private Enterprises, Labor, and Employment, though the details are limited. The legislation touches upon employment but doesn't elaborate on regulations affecting the labor market or employment practices significantly, which leads to a lower relevance score.
Keywords (occurrence): artificial intelligence (2)
Description: Creating the Government Technology Modernization Council within the Department of Management Services for a specified purpose; prohibiting a person from knowingly possessing or controlling or intentionally viewing photographs, motion pictures, representations, images, data files, computer depictions, or other presentations which the person knows to include generated child pornography; prohibiting a person from intentionally creating generated child pornography, etc.
Collection: Legislation
Status date: April 29, 2024
Status: Passed
Primary sponsor: Rules
(3 total sponsors)
Last action: Chapter No. 2024-118 (April 29, 2024)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Judicial system
Hybrid, Emerging, and Unclassified (see reasoning)
Keywords (occurrence): artificial intelligence (6) machine learning (1) automated (1) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text clearly outlines legislation focused on both the creation of the Government Technology Modernization Council and regulations surrounding generated child pornography. The references to artificial intelligence, especially in the establishment of the council, link it to the development and regulation of technology. The council is tasked with promoting AI systems, addressing ethical considerations, evaluating the impact of automated decision systems, and recommending policies to protect citizens from malicious uses of AI. Given this context, the legislation has strong implications for social impact, data governance, and system integrity if AI technologies are to be implemented responsibly. Furthermore, the text discusses AI's role in managing security and safety, reinforcing the relevance of the robustness category as it implies the establishment of benchmarks and regulations. Overall, the implications of AI for social accountability and ethical considerations make the social impact category especially relevant, while the regulation of AI systems points to the importance of data governance and system integrity.
Sector:
Government Agencies and Public Services
Judicial system
Hybrid, Emerging, and Unclassified (see reasoning)
This legislation pertains to several sectors through its provisions and objectives. The establishment of the Government Technology Modernization Council suggests a strong relevance to Government Agencies and Public Services, as it is designed to enhance the deployment and regulation of technology within the state. The mention of artificial intelligence and automated decision systems also implies considerations relevant to the Judicial System due to concerns about rights and biases arising from AI use. Additionally, as the legislation addresses responsibilities around the use of AI to combat issues such as generated child pornography, it touches on social justice impacts relevant to the broader community. It does not directly pertain to sectors like Healthcare or academics, nor does it address international cooperation specifically. However, its broad implications point to significant relevance for multiple sectors with an emphasis on governance and regulatory compliance.
Keywords (occurrence): artificial intelligence (6) machine learning (1) automated (1) show keywords in context
Description: Enacts regulations on automated license plate reader systems
Collection: Legislation
Status date: Jan. 31, 2024
Status: Introduced
Primary sponsor: Mike Cierpiot
(sole sponsor)
Last action: Second Read and Referred S Transportation, Infrastructure and Public Safety Committee (Feb. 8, 2024)
Category:
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): automated (5) show keywords in context
Data Governance
System Integrity (see reasoning)
The text explicitly addresses the regulation of automated license plate reader systems, which involves the use of computer algorithms to process data. While it touches upon the governance and management of technology through regulations, it does not deeply explore the broader social impacts of AI, data privacy concerns, or the integrity of the system beyond how it may apply to automated license plate readers. It discusses specific terms and rafts legal boundaries for usage without addressing wider nuances of AI's influence.
Sector:
Government Agencies and Public Services (see reasoning)
This bill directly pertains to government use of AI technology, specifically regarding public safety systems like license plate readers. It limits the use of these systems by governmental bodies and outlines associated data handling, which is pertinent to the regulation of AI in governmental contexts. The relevance is moderate since it discusses the implementation and implications of such technology in public agencies but lacks broader implications for other sectors.
Keywords (occurrence): automated (5) show keywords in context
Description: An act relating to the temporary use of automated traffic law enforcement (ATLE) systems
Collection: Legislation
Status date: May 10, 2024
Status: Passed
Primary sponsor: Martine Gulick
(3 total sponsors)
Last action: Senate Message: Signed by Governor May 30, 2024 (May 10, 2024)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Judicial system (see reasoning)
Keywords (occurrence): automated (37) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text primarily focuses on the implementation of Automated Traffic Law Enforcement (ATLE) systems and Automated License Plate Recognition (ALPR) technologies. The usage of automated systems for traffic enforcement ties directly into discussions around AI and automation as it utilizes algorithms for monitoring and recording violations, which makes it pertinent to all categories. The Social Impact category is relevant due to the societal implications of deploying ATLE systems, including potential concerns about surveillance, accuracy in the use of this technology, and how penalties are enforced based on recorded data. The Data Governance category is relevant because the act discusses the collection, management, and retention of data collected by these systems, addressing the necessity of legitimate law enforcement purposes for data usage, which is necessary for privacy and accuracy considerations. The System Integrity category is relevant due to the references to operational checks, maintenance of accuracy, and the integrity of data collected which are crucial to ensuring the systems function correctly and are not misused. Finally, the Robustness category applies as it pertains to the implementation of standards and requirements for the operation of the ATLE systems, ensuring they are properly calibrated and tested, which relates to performance benchmarks and regulatory compliance.
Sector:
Government Agencies and Public Services
Judicial system (see reasoning)
This text is highly relevant to the Government Agencies and Public Services sector, as it directly involves the deployment of automated systems by the Agency of Transportation for public safety purposes. It also relates moderately to the Judicial System sector, given that the regulations concerning civil violations and the adjudication process are mentioned. The restrictions on data access and retention also touch on concerns relevant to the Privacy sector, but this is not a defined sector in the criteria given. However, the emphasis on law enforcement uses of the systems makes it primarily pertinent to government operations rather than other sectors.
Keywords (occurrence): automated (37) show keywords in context
Description: Amend The South Carolina Code Of Laws By Adding Article 6 To Chapter 5, Title 39 So As To Stop Certain Social Media Censorship, To Provide Penalties, And To Provide Exceptions.
Collection: Legislation
Status date: Jan. 10, 2023
Status: Introduced
Primary sponsor: James Burns
(4 total sponsors)
Last action: Member(s) request name added as sponsor: Beach (Feb. 2, 2023)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Politics and Elections
Government Agencies and Public Services
Judicial system (see reasoning)
Keywords (occurrence): algorithm (3) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text discusses social media censorship and the use of algorithms, making it relevant to all four categories. In terms of 'Social Impact', it raises issues on the impact of censorship on political and religious speech, which directly aligns with societal impacts of AI-driven moderation. For 'Data Governance', while not explicitly focused on data management, the reference to algorithms and the requirement for fair practices in speech indirectly invokes considerations of how data-related practices affect users. 'System Integrity' is relevant due to the mention of algorithmic use and potential biases in social media platforms, seeking to ensure users have human-level oversight in case of disputes. 'Robustness' is relevant as the bill discusses maintaining standards for algorithms that govern speech, although the main focus is on censorship rather than performance metrics. Overall, there is a significant emphasis on the social implications and the governance of algorithms with respect to public discourse and trust, contributing to higher scores.
Sector:
Politics and Elections
Government Agencies and Public Services
Judicial system (see reasoning)
The legislation prominently addresses issues pertinent to the regulation of AI through algorithms on social media, especially in the context of political speech, making it highly relevant to 'Politics and Elections'. The potential penalties and standards for algorithmic moderation also lend relevance to 'Government Agencies and Public Services', as officials may need to enforce these regulations. 'Judicial System' relevance is evident through its implications for legal actions users can take against social media platforms. While healthcare and private enterprise sectors are not directly addressed, the principle of algorithm accountability may resonate in these areas as they intersect with operational practices of various entities. Overall, 'Politics and Elections' stands out as the most relevant sector closely tied to the legislative text's focus on censorship and algorithmic influence.
Keywords (occurrence): algorithm (3) 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.
Collection: Legislation
Status date: Feb. 2, 2024
Status: Introduced
Primary sponsor: State Affairs
(sole sponsor)
Last action: REFERRED TO STATE AFFAIRS (Feb. 2, 2024)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): artificial intelligence (11) machine learning (2) automated (1) deepfake (3) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text primarily addresses the implications of AI, particularly in the realm of deepfakes and their disclosure in campaign communications. It engages with issues of misinformation, accountability, and consumer protections in the context of political integrity, making it highly relevant to Social Impact. Additionally, it establishes procedures for data governance within state agencies using AI, thus connecting to Data Governance. Concerns about cybersecurity also suggest relevance to System Integrity. The focus on mandatory impact assessments indicates a commitment to developing frameworks that assure the robustness of AI systems, but it is less about performance benchmarks and more about compliance and responsibility, placing it moderately relevant to Robustness.
Sector:
Politics and Elections
Government Agencies and Public Services (see reasoning)
The text addresses the use of AI in political communications explicitly, particularly concerning the regulation of deepfakes during campaigns, yielding a high relevance to Politics and Elections. It also discusses the role of state agencies in employing AI for consequential decisions and outlines impact assessments, highlighting its importance in Government Agencies and Public Services. While there are broad implications for AI across other sectors, the text does not specifically address them, leading to lower relevance scores for the remaining sectors.
Keywords (occurrence): artificial intelligence (11) machine learning (2) automated (1) deepfake (3) show keywords in context
Description: Creates standards for independent bias auditing of automated employment decision tools.
Collection: Legislation
Status date: March 18, 2024
Status: Introduced
Primary sponsor: Andrew Zwicker
(sole sponsor)
Last action: Introduced in the Senate, Referred to Senate Labor Committee (March 18, 2024)
Category:
Societal Impact
Data Governance
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (2) machine learning (1) automated (7) show keywords in context
Societal Impact
Data Governance
System Integrity (see reasoning)
This legislation primarily impacts Social Impact as it addresses biases in employment decisions made by automated employment decision tools (AEDTs), which can affect the job opportunities of individuals. The legislation mandates independent bias auditing, which aims to ensure fairness and accountability in AI systems used in hiring, thus addressing potential discrimination and promoting equitable treatment. Given the specific mention of bias audits and compliance with anti-discrimination laws, this score is high. Data Governance is also highly relevant, as it involves ensuring that the data used by AEDTs is accurate and free from biases, as indicated by the legislation's requirements for audits based on historical and test data. System Integrity is moderately relevant since the legislation doesn’t explicitly mention system security, though the requirement for transparency aligns with core integrity concepts. Robustness is less relevant here as the focus of this bill is more on auditing and compliance rather than performance benchmarks for AI. Overall, the strongest connections are with Social Impact and Data Governance, which are crucial given that the bill directly relates to preventing bias in employment scenarios.
Sector:
Government Agencies and Public Services
Private Enterprises, Labor, and Employment (see reasoning)
The primary sectors impacted by this legislation include Private Enterprises, Labor, and Employment, as it concerns the use of AEDTs within workforce hiring practices, promoting fairness and accountability in employment decisions. The legislation requires employers to be transparent about their use of these tools and their assessment processes, directly impacting how businesses operate concerning employment. Government Agencies and Public Services may also be relevant to some extent, as the regulation could involve public sector employment entities, but is primarily targeted toward private employers. Judicial System is not significantly addressed as the text focuses on employment auditing rather than any legal adjudication process. The remaining sectors such as Politics and Elections, Healthcare, Academic and Research Institutions, and Nonprofits and NGOs are not directly applicable here as they don’t pertain to the scope of automated employment decisions. Thus, the most pertinent sector for this legislation is Private Enterprises, Labor, and Employment.
Keywords (occurrence): artificial intelligence (2) machine learning (1) automated (7) show keywords in context
Description: Prohibits a person from recklessly distributing, or entering into an agreement with another person to distribute, materially deceptive media, subject to certain exceptions. Establishes criminal penalties for distributing materially deceptive media. Establishes remedies for parties injured by the distribution of materially deceptive media. (CD1)
Collection: Legislation
Status date: July 5, 2024
Status: Passed
Primary sponsor: Karl Rhoads
(2 total sponsors)
Last action: Act 191, 07/03/2024 (Gov. Msg. No. 1292). (July 5, 2024)
Category:
Societal Impact
Data Governance (see reasoning)
Sector:
Politics and Elections (see reasoning)
Keywords (occurrence): artificial intelligence (3) machine learning (1) deep learning (1) automated (1) deepfake (2) show keywords in context
Societal Impact
Data Governance (see reasoning)
The text prominently discusses the implications of artificial intelligence in the context of electoral processes, particularly in relation to the distribution of materially deceptive media facilitated by AI technologies like deepfakes. It emphasizes the social impact of AI on elections and highlights the necessity of regulating AI to prevent misinformation, which is a critical societal concern. Hence, Social Impact is assessed as very relevant. Data Governance is moderately relevant as it indirectly concerns the accuracy of information distributed through AI but does not directly engage with data management policies. System Integrity focuses on security and transparency of AI processes, which are not explicitly addressed here, hence is rated as not relevant. Robustness pertains to benchmarks and compliance standards for AI, not directly applicable in the context of this legislation, resulting in a not relevant score. Therefore, only Social Impact stands out as a highly relevant category due to its direct relation to the consequences of misleading media in elections fueled by AI.
Sector:
Politics and Elections (see reasoning)
This text explicitly addresses the use of AI in the political and electoral process, particularly relating to the harmful implications of deepfakes and the framework that needs to be in place to protect election integrity. Therefore, it fits squarely within the Politics and Elections sector, which focuses on the regulatory measures surrounding AI in political campaigns. It does not address governmental operations, judicial applications, healthcare, or any of the other sectors listed, making the relevance to other sectors quite low. Thus, Politics and Elections receives a high score while all others are rated as not relevant.
Keywords (occurrence): artificial intelligence (3) machine learning (1) deep learning (1) automated (1) deepfake (2) show keywords in context
Description: House bill No. 4642, as amended and passed to be engrossed by the House. May 15, 2024.
Collection: Legislation
Status date: May 15, 2024
Status: Engrossed
Last action: Reported by H4889 (July 19, 2024)
Category:
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
Sector:
Government Agencies and Public Services
Nonprofits and NGOs (see reasoning)
Keywords (occurrence): artificial intelligence (1) machine learning (1) automated (1) show keywords in context
Societal Impact
Data Governance
System Integrity
Data Robustness (see reasoning)
The text outlines a comprehensive plan to enhance the information technology infrastructure of Massachusetts, specifically mentioning artificial intelligence and machine learning systems. Given that AI technologies play a significant role in improving efficiency and effectiveness within public services, the legislation has notable implications regarding social impact, data governance, system integrity, and robustness. The categories are evaluated below based on the specific elements mentioned in the text.
Sector:
Government Agencies and Public Services
Nonprofits and NGOs (see reasoning)
The bill covers multiple sectors, with a clear emphasis on government operations and public services through technological enhancements. The inclusion of AI systems suggests a transformative approach within state agencies, impacting public services directly. The relevance to various sectors is considered based on the applications and implications of AI in enhancing public service delivery, as well as the importance of data security and quality.
Keywords (occurrence): artificial intelligence (1) machine learning (1) automated (1) show keywords in context
Description: A bill to prohibit, or require disclosure of, the surveillance, monitoring, and collection of certain worker data by employers, and for other purposes.
Collection: Legislation
Status date: Feb. 2, 2023
Status: Introduced
Primary sponsor: Robert Casey
(6 total sponsors)
Last action: Read twice and referred to the Committee on Health, Education, Labor, and Pensions. (Feb. 2, 2023)
Category:
Societal Impact
Data Governance (see reasoning)
Sector:
Private Enterprises, Labor, and Employment (see reasoning)
Keywords (occurrence): artificial intelligence (2) automated (6) show keywords in context
Societal Impact
Data Governance (see reasoning)
The text explicitly discusses the regulation of automated decision systems, which are typically grounded in AI technologies. It also outlines terms related to data collection and automated systems that could influence outcomes in work environments, indicative of potential social and ethical implications. An emphasis on automated decision systems and their outputs directly ties into social implications, particularly concerning worker rights and privacy. However, while it highlights data governance aspects due to its focus on data collection and management, it does not address issues of robustness or system integrity directly.
Sector:
Private Enterprises, Labor, and Employment (see reasoning)
The text primarily concerns the relationship between employers and employees regarding surveillance practices and automated systems, impacting the labor sector directly. The mention of automated decision systems indicates potential applications in various industries that involve employment processes, but does not provide in-depth exploration of any medical, governmental, or non-profit application. Thus, the relevance remains strongest within the labor context outlined in the bill, with lesser importance to other sectors.
Keywords (occurrence): artificial intelligence (2) automated (6) show keywords in context
Description: Aligns state and local procurement laws with federal law prohibiting the procurement of certain information and communications technology and electronic parts or products which are determined to pose a risk to state and national security.
Collection: Legislation
Status date: Feb. 27, 2024
Status: Introduced
Primary sponsor: Jenifer Rajkumar
(6 total sponsors)
Last action: ordered to third reading rules cal.503 (June 6, 2024)
Category:
System Integrity (see reasoning)
Sector:
Government Agencies and Public Services (see reasoning)
Keywords (occurrence): automated (1) show keywords in context
System Integrity (see reasoning)
The text primarily focuses on the procurement restrictions regarding certain information and communications technology due to security risks. It explicitly mentions automated decision-making systems, but does not delve into the broader social impacts of AI, data governance surrounding AI systems, system integrity beyond procurement, or robustness in the context of AI performance. The explicit mention of automated decision-making could indicate some relevance to system integrity, but it's primarily about procurement and security matters.
Sector:
Government Agencies and Public Services (see reasoning)
The text's relevance is tangential to sectors like Government Agencies and Public Services, as it discusses government procurement procedures. However, it does not directly address the use of AI technologies in these contexts. There's minimal relevance to other sectors, as it does not pertain to politics, the judicial system, healthcare, private enterprises, academia, or international standards. The overarching theme regarding security and procurement impacts primarily government operations.
Keywords (occurrence): automated (1) show keywords in context