Generative AI System
AI systems trained on data that interact with individuals using text, audio, or visual communication, generating human-like output.
How the laws define this
Regulators agree that these systems center on technologies capable of creating realistic, human-like output across various formats, including text, audio, and visual media. Both instruments encompass tools that produce content mimicking human creation, whether described as outputs similar to those created by a human or as synthetic media. They diverge, however, in their focus and required obligations. Increase Transparency for Algorithmic Systems emphasizes data-trained systems that interact directly with individuals, explicitly conditioning its definition on generating human-like communication that mandates clear disclosure. In contrast, House Bill No. 10567 (Regulation of AI Use in 2025 Elections) defines the term around the production of realistic fake content and synthetic media, specifically calling out techniques like text-to-speech, voice cloning, face-swapping, and video or image synthesis using machine learning or other generative methods, without requiring direct user interaction or mentioning disclosure rules.
Synthesised from the 2 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.
| Jurisdiction | Instrument | Status | What is distinctive |
|---|---|---|---|
| Colorado, United States | Increase Transparency for Algorithmic Systems | In Force | Adds a requirement for clear disclosure and emphasizes capability of generating human-like output. |
| Philippines | House Bill No. 10567 (Regulation of AI Use in 2025 Elections) | Under Review | Widens to include specific technologies like synthetic media, voice cloning, face-swapping, and realistic fake content via machine learning or other methods. |
What it triggers
Definitions (2)
AI systems trained on data that interact with individuals using text, audio, or visual communication, and are capable of generating output similar to that which could be created by a human, requiring clear disclosure.
Technologies and systems capable of producing synthetic media, including text-to-speech, voice cloning, face-swapping, video and image synthesis, and other AI techniques that generate realistic fake content, whether via machine learning models or other generative methods.
Questions and answers
What disclosure is required for generative AI systems in Colorado?
Colorado requires clear disclosure for AI systems that generate human-like output. This applies to systems trained on data interacting via text, audio, or visual communication.
What does the Philippines bill cover under generative AI?
House Bill No. 10567 covers technologies producing synthetic media like text-to-speech, voice cloning, face-swapping, and other AI techniques generating realistic fake content.
How do the Colorado and Philippines definitions of generative AI differ?
Colorado focuses on interactive systems generating human-like output with disclosure requirements, while the Philippines bill targets synthetic media and deepfakes mandating disclosures for elections.