ccpa admt risk assessment

The problem

Developers and product teams often assume any AI feature triggers California's heavy ADMT regulations, leading to wasted compliance drift. Conversely, missing a pre-deployment risk assessment for a new HR or lending model can create a permanent record of a violation before the tool even launches.

What it does

• Determines if an automated tool "substantially replaces" human decision-making or merely assists.
• Identifies whether AI workloads qualify as "significant decisions" under CCPA or fall into exempt categories like advertising.
• Conducts a formal balancing test weighing business benefits against foreseeable privacy risks to consumers.
• Generates the underlying documentation required for executive attestation and regulatory record-keeping.

Why this beats prompting it yourself

Generic LLMs often rely on outdated draft versions of the CCPA ADMT rules which were materially narrowed in the final text. This skill enforces a "pre-deployment gate" logic, ensuring you don't mistake a distant backstop deadline for a green light to ship new features today without an assessment.

Use cases

• Scoping whether a new resume-ranking tool or productivity scorer triggers HR inference rules.
• Drafting the pre-use notices and opt-out flows required for automated lending or housing decisions.
• Preparing the technical logic and parameter documentation needed for a CPPA attestation.
• Verifying if training an AI model on sensitive data triggers an assessment, even if the model isn't deployed yet.

Known limitations

This tool produces counsel-prep documentation, not a legal opinion or a signed attestation. It cannot be used as a substitute for privacy counsel on contested legal questions.