Generative artificial intelligence
AI that produces synthetic content emulating its training data.
How the laws define this
Laws and official guidance consistently define generative artificial intelligence as technology that creates or synthesizes novel, derived content—such as text, images, video, audio, or code—by emulating the structure, patterns, and characteristics of its input or training data rather than merely analyzing existing information. Definitions fundamentally diverge on whether scope is determined by general technical capabilities or specific deceptive risks and interactive applications. Functional definitions, such as California AB 2013 and the Seattle Responsible AI Policy (POL-211), broadly encompass any system producing synthetic content from learned patterns. In contrast, Utah SB 149 narrows coverage to systems capable of producing human-like content that could mislead consumers, while Utah SB 226 specifically requires systems designed to simulate human conversation and generate non-scripted outputs with limited or no human oversight. Additionally, instruments like S.B. 131 Information Technology Act Amendments and Wisconsin Act 123 target the technology specifically through its application to generate deepfakes or synthetic media indistinguishable from real content.
Synthesised from the 19 statutory definitions below. Each one is quoted in full, with its source.
How jurisdictions differ
What is distinctive in each definition, binding law in force first. Showing 10 of the 22 instruments that define this term; all are listed under Definitions below.
| Jurisdiction | Instrument | Status | What is distinctive |
|---|---|---|---|
| Utah, United States | Utah SB 149 — Artificial Intelligence Policy Act | In Force | Adds capability to produce human-like content that could mislead consumers about interacting with a human or machine. |
| California, United States | California AB 2013 — Generative Artificial Intelligence: Training Data Transparency | In Force | Explicitly encompasses large language models, image generation systems, video synthesis tools, and audio generation platforms. |
| Colorado, United States | Candidate Election Deepfake Disclosures | In Force | Limits to systems generating novel content based on prompts or other forms of data provided by a person. |
| Arkansas, United States | Arkansas HB 1876 — Generative AI Content Ownership (Act 927) | In Force | Uses functional description rather than technical specification, focusing on novel outputs from user inputs and training data. |
| Florida, United States | Florida HB 919 - AI in Political Advertising | In Force | Specifies machine-based system for human-defined objectives that emulates input data to generate derived synthetic content. |
| Wisconsin, United States | Wisconsin Act 123 (formerly AB 664) - Deepfakes Regulation in Political Advertisements | In Force | Limits to advanced AI techniques creating new data like audio, video, or images often indistinguishable from real content. |
| Oklahoma, United States | An Act relating to crimes and punishments; amending 21 O.S. 2021, Section 1040.13b, as amended by Section 1, Chapter 214, O.S.L. 2024 (21 O.S. Supp. 2024, Section 1040.13b), which relates to the Oklahoma Law on Obscenity and Child Sexual Abuse Material; defining terms; making certain acts unlawful; and providing an effective date. | In Force | Specifies models producing novel outputs rather than just analyzing or classifying existing data. |
| Argentina | Protocol for the Judicial Use of Artificial Intelligence in San Luis Province | In Force | Limits to AI producing various content types used in judicial context to assist tasks like drafting legal documents. |
| Vermont, United States | An act relating to regulating the use of artificial intelligence in the provision of mental health services | In Force | Adds emphasis on producing derived synthetic content by emulating structure and characteristics of training data. |
| Washington, United States | Seattle Responsible AI Policy | In Force | Includes leveraging large language models, deep learning, and machine learning for new content like text-to-code translation. |
What it triggers
- In Utah, businesses using generative AI in consumer interactions must provide disclosures.source
- In Colorado, disclosure is required for AI-generated deepfakes in election communications.source
- In Florida, sponsors of political ads must disclose synthetic or generative AI content deceptively depicting real persons.source
- In Wisconsin, political committees must clearly disclose AI-generated audio or video content in campaign advertisements.source
- In Vermont, human oversight is mandated for clinical decisions involving AI in mental health services.source
Definitions (23)
Artificial intelligence that can generate derived synthetic content, including text, images, video, and audio, that emulates the structure and characteristics of the system's training data; this definition explicitly encompasses large language models, image generation systems, video synthesis tools, and audio generation platforms.
An artificial intelligence system capable of generating novel image, video, audio, multimedia, or text content based on prompts or other forms of data provided by a person.
Artificial intelligence that can generate derived synthetic content, including text, images, video, and audio, that emulates the structure and characteristics of the AI's training data and is capable of producing human-like content that could mislead consumers about whether they are interacting with a human or a machine.
Systems or technologies capable of producing or synthesizing content (e.g., text, images, audio, video, or synthetic data) by generating outputs based on learned models and algorithms. The bill uses this term to delimit coverage to AI that actively creates or transforms content rather than all algorithmic systems.
AI systems that generate novel outputs (text, images, code, audio, or other media) in response to user inputs and training data; the statute uses a functional description rather than a technical specification. The term underpins the law's rules for ownership of outputs and models produced or trained using such systems.
Generative artificial intelligence, or generative AI, is defined as a machine-based system that can, for a given set of human-defined objectives, emulate the structure and characteristics of input data in order to generate derived synthetic content including images, videos, audio, text, and other multi-media digital content.
An artificial intelligence system that is trained on data; designed to simulate human conversation through text, audio, or visuals; and generates non-scripted outputs with limited or no human oversight.
'Generative artificial intelligence,' in turn, is specified as AI technology specifically capable of creating synthetic media. This distinction is crucial as it targets the specific application of AI that can produce deepfakes and other manipulated content.
As defined in Section 106.145(1) of the Florida Statutes, a machine-based system that, for a given set of human-defined objectives, emulates the structure and characteristics of input data to generate derived synthetic content such as images, videos, audio, text, and other digital content. The definition is broad and encompasses systems that create or manipulate multimedia or other digital artifacts used in political advertising.
A type of artificial intelligence capable of generating new content, such as text, images, or other media, in response to prompts. The committee specifically focused on the implications of Generative AI for the judicial system.
Advanced AI techniques capable of creating new data, such as audio, video, or images, often indistinguishable from real content.
AI systems capable of producing novel content—such as text, images, audio, video, or other data—that resembles real-world inputs. In the context of this resolution, GenAI denotes the class of models and tools whose outputs are subject to the guidelines on use, oversight, evaluation, and data handling within the provincial public administration.
A class of artificial intelligence models capable of generating new content, such as text, images, audio, or code, often in response to prompts. These models learn patterns and structures from large datasets to produce novel outputs that resemble the training data.
A class of software and functionalities that leverage large language models, deep learning, and machine learning models to generate new content such as text, images, video, and audio from input data patterns, including capabilities like text-to-code translation. The term is used to distinguish content-producing AI from other AI solutions for purposes of oversight and special controls.
A type of artificial intelligence capable of producing various types of content, including text, images, and other media, used in the judicial context to assist in tasks like drafting legal documents.
Models and systems that produce novel content by learning patterns from training data, including generation of text, code, images, and synthetic data; in this Guide GAI denotes tools used to assist or produce research outputs and methods that require disclosure and verification.
Generative artificial intelligence refers to AI systems designed to create new content, including text, images, audio, or video, that can be highly realistic and potentially indistinguishable from content produced by humans. This capability is central to the Act's scope regarding AI-driven defamation.
An AI system that can produce derived synthetic content, such as text, images, or audio, by emulating the structure and characteristics of its training data. This distinction highlights the legislature's awareness of the advanced capabilities of modern AI systems.
Generative AI specifically refers to artificial intelligence models that can produce novel outputs, rather than just analyzing or classifying existing data. These systems learn patterns from large datasets and then generate new data that resembles the training data, often used for creating deepfakes, synthetic media, or creative content.
A system that generates text, images, or other outputs based on training data and user prompts. In SB 574, the term matters because attorney and arbitrator duties are triggered by AI-assisted work and output verification.
An artificial intelligence system capable of generating derived synthetic content, including text, images, video, and audio, that emulates the structure and characteristics of its training data. In SB 574, the term is used to regulate professional reliance on AI outputs while preserving human responsibility.
Generative artificial intelligence, or GenAI, refers to a system that produces new content in response to user prompts or inputs. In this statute, the term is tied to California’s broader AI definition in Government Code Section 11549.64.
AB 2656 would have used the California statutory definition in Government Code Section 11549.64. The bill did not restate the definition, so its coverage would have depended on that incorporated language.
Not to be confused with
Refers specifically to an AI system or foundation model, while this term is the broader category encompassing such systems.
Specifies internet-accessible systems, whereas this term covers generative AI systems more generally without access restrictions.
Emphasizes services creating novel content, while this term denotes the underlying systems capable of such generation.
Questions and answers
What disclosures are required for generative AI in elections?
Colorado requires disclosure for AI-generated deepfakes in election communications. Florida mandates sponsors disclose synthetic AI content in political ads depicting real persons. Wisconsin requires political committees to disclose AI-generated audio or video in campaign ads.
Does generative AI trigger consumer protection rules in Utah?
Yes, Utah SB 149 requires businesses using generative AI in consumer interactions to provide disclosures. Utah SB 226 also regulates it in consumer transactions with disclosures and liability.
What are the limits on generative AI in mental health services?
Vermont mandates human oversight for clinical decisions using generative AI in mental health services while allowing it for administrative support.
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