Will the U.S. Congress pass, and the President sign, a bill by January 10, 2025 11:59 PM EST that meets one or more of the criteria for 'Major AI Regulation'?

Criteria:

- Privacy and Data Rights

- Mandates the explicit informed consent of individuals before their personal data is collected

or processed by AI systems.

- Restrictions on the sale, sharing, or third-party use of personal data processed by AI

systems without clear and explicit user consent.

- A right to data erasure, allowing individuals to request the deletion of their data from AI

systems.

- Requirements for timely notification to affected individuals in the event of a data breach or

unauthorized access to their personal data within AI systems.

- Transparency and Explainability

- Requirements for AI systems to provide user-friendly explanations for their decisions,

particularly when used in critical sectors like health, finance, or judicial processes.

- Obligations for AI systems that emulate humans to reveal to people / users that they are AI,

and / or generic disclosure rules for outputs of generative AI.

- Obligations for AI developers or deployers to disclose the datasets and methodologies used

in training the AI, ensuring external auditors can assess the system's fairness and reliability.

- Bias and Fairness

- AI developers must implement tools and methodologies to identify and rectify biased

decision-making in AI systems.

- Periodic third-party audits to ensure AI systems are not perpetuating or amplifying societal

biases, with findings made available to the public.

- Safety and Reliability

- Guidelines or standards for the validation and testing of AI in sectors where human safety is

at risk.

- Ongoing monitoring requirements for deployed AI systems to track potential drifts from

expected behavior, with mandated corrective actions when anomalies are detected.

- Targeted bans or other legal restrictions on the use of “high risk” AI systems, e.g. bans on

voice cloning or models with a biosafety risk.

- Accountability and Liability

- Clear definitions of legal responsibilities for AI system malfunctions or erroneous decisions,

whether they lie with developers, deployers, or operators.

- Amendments to Section 230 of the CDA to clarify that the liability protections for internet

platforms do not extend to AI outputs / companies

- A framework for affected individuals or entities to seek redress or compensation in the event

of harm or damages caused by AI systems.

- Human Oversight

- Requirements for AI systems, particularly those with autonomous decision-making

capabilities, to have human-in-the-loop mechanisms where a human can intervene in real-time

decisions.

- Obligations for regular review and validation of AI decisions by human experts in sectors

deemed critical.

- Training Runs and Compute

- Disclosure mandates for AI developers to report on the compute resources used during

model training, to ensure environmental sustainability and ethical use of computational

resources.

- Restrictions on training runs that utilize datasets in violation of privacy and data rights or that

exceed certain environmental thresholds.

- Guidelines on the acceptable sources and methods for data collection for training AI models,

ensuring ethical sourcing and data quality.