Draft a Workplace AI Surveillance Policy Memo Before Newsom Signs

The task

You're the HR lead (or policy owner) at a company with California employees. California would limit businesses' ability to use artificial intelligence tools to monitor workers' nervous systems and emotional states under legislation headed to Gov. Gavin Newsom for his signature. You need to inventory which of your current vendors touch this, then get a first-draft internal memo in front of Legal and your CHRO — this week, not next month.

Before AI

The manual version: pull every active HR-tech contract, read each vendor's data-processing addendum, cross-reference against the bill text, then start a policy doc from scratch or from a stale 2022 template. Realistically that's a half-day of reading plus another half-day of drafting before Legal ever sees it. Most HR teams skip the vendor audit and just wait for Legal — which means you're reactive when the bill gets signed.

The workflow

The idea: give the model your vendor list plus the bill's key definitions, and have it (1) flag which vendors are in scope, (2) draft the internal memo, and (3) generate the vendor questionnaire you'll send out. Read the HR Dive summary of AB 1883 and skim the bill text on LegiScan before you start so you can sanity-check the output.

Step 1 — Triage your vendor stack against the bill

Paste your current HR-tech vendor list (below). The prompt classifies each as In Scope / Likely In Scope / Out of Scope under AB 1883, with a one-line reason per vendor.

You are an HR policy analyst helping a US company prepare for California AB 1883.

Context on AB 1883 (pending California legislation, headed to Governor Newsom):
- It would prohibit employers from using workplace surveillance tools that use AI to recognize, infer, or predict an employee's emotional state, or to collect "neural data."
- "Neural data" means information generated by measuring the activity of an employee's central or peripheral nervous system that is not inferred from nonneural information.
- Covered tools include those incorporating facial, gait, or emotion recognition technology.
- Safety-related use is a permitted exception.
- Civil penalty is up to $500 per violation.

Below is a company's active HR-tech vendor list with a short description of what each tool does. For EACH vendor, produce a table row with:
| Vendor | Function | AB 1883 Status (In Scope / Likely In Scope / Out of Scope / Needs Vendor Confirmation) | One-line reason | Suggested next action |

Be conservative — if a tool advertises "sentiment," "engagement inference," "tone," "facial analysis," "voice affect," or "wellbeing signals," flag it as Likely In Scope even if the vendor claims it's aggregated.

After the table, list the top 3 vendors that need urgent contract review, and why.

Vendor list follows:

Company: Meridian Freight Logistics (HQ Long Beach, CA; ~2,400 employees, 1,700 in California)

Active HR-tech vendors:
1. BrightHire — structured interview intelligence; records candidate video, produces transcript + "candidate signal" scores for interviewers.
2. Cornerstone LMS — learning management, course completion tracking.
3. Gong for HR pilot — analyzes recorded manager 1:1s for "coaching tone" and flags "disengagement risk" in direct reports.
4. Workday — HRIS, payroll, performance review workflow.
5. Verkada — office security cameras with facial recognition enabled at three CA distribution centers, currently used for badge-less entry.
6. Kaia Health @Work — voluntary wellness app; uses phone camera for posture/exercise form feedback during stretch breaks.
7. Culture Amp — quarterly engagement surveys, free-text sentiment analysis on open-ended responses.
8. Samsara driver-facing cams — in-cab AI that detects "drowsiness" and "distraction" for the 340-truck fleet; triggers audible alert and logs event.
9. HireVue — asynchronous video interviews for warehouse associate roles; scoring model retired 2021 but video + transcript still retained.
10. Modern Health — EAP platform, employee-initiated therapy booking; no manager-facing data.

Step 2 — Draft the internal policy memo

Feed the triage table into a memo draft. Keep it short — Legal will rewrite it, but a concrete draft moves the conversation.

Using the vendor triage above, draft an internal policy memo from the VP of People to the CHRO, General Counsel, and CIO. Length: 500-700 words. Structure:

1. Subject line and one-sentence TL;DR.
2. What AB 1883 does, in 3 bullets (plain English — assume the CIO has not read the bill).
3. Our current exposure — reference specific vendors from the triage table by name, grouped by risk tier.
4. Proposed immediate actions (next 14 days): contract review list, features to disable, vendor questionnaires to send.
5. Proposed policy changes (next 60 days): update to Acceptable Use of Workplace Monitoring Tools policy, notice-and-consent language for CA employees, carve-out language for the safety exception (e.g., in-cab drowsiness detection for DOT-regulated drivers).
6. Open questions for Legal — at least 4, including whether the safety exception covers our fleet cams and how to handle retained video from the retired HireVue scoring model.

Tone: direct, no hedging adjectives, no "in today's rapidly evolving landscape." Write like an operator briefing peers.

Step 3 — Generate the vendor questionnaire

You'll need to send the same set of questions to every "Likely In Scope" and "Needs Vendor Confirmation" vendor. Have the model produce it.

Now generate a vendor questionnaire we can send to every vendor flagged Likely In Scope or Needs Vendor Confirmation in the triage. Format as a numbered list of 10-14 questions the vendor's privacy or compliance team can answer in writing. Cover:

- Whether the product uses AI to infer, predict, or recognize emotional state (and where in the product surface).
- Whether it collects neural data as defined in AB 1883.
- Whether facial, gait, voice affect, or emotion recognition is used — and whether it can be disabled per-tenant for CA users.
- Data retention for any affect/emotion-derived signals and whether they can be purged on request.
- Whether the vendor asserts the safety exception applies to any feature, and the basis.
- Sub-processors that receive any of the above data.
- Contractual willingness to add a CA AB 1883 compliance rider.

End with a suggested response deadline (14 calendar days) and a single point-of-contact line. Do not include filler intro/outro paragraphs — this goes straight into a procurement email.

Gotchas

• The bill isn't law yet. As of the source date it is headed to California Governor Gavin Newsom for signature or veto. Draft now, but don't send policy changes company-wide until signature. Newsom has previously vetoed adjacent measures — the measure Newsom vetoed, Senate Bill 7, included brain data — so a veto is a live possibility.
• The safety exception is narrower than it sounds. AB 1883 would not prohibit employers from using workplace surveillance tools broadly, and the law would permit the use of such tools to ensure safety. The model will often stretch "safety" to cover engagement or productivity tools. Don't let it. Push those back into the "needs Legal review" bucket.
• "Sentiment analysis" on survey text is a gray zone. The bill targets tools that recognize, infer, or predict an employee's emotional state. Vendors like engagement-survey platforms will argue their aggregate sentiment scores don't identify individuals. That's a legal call, not a prompt call — flag it, don't resolve it.
• Neural data is a specific term. Neural data includes information generated by measuring the activity of an employee's central or peripheral nervous system that is not inferred from nonneural information. Most current HR tools don't collect it. Don't let the model over-flag every wearable — a step counter is not neural data.
• Penalty is per violation. Violators would be subject to a per-violation penalty of $500. That number sounds small until you multiply by employee count times days. Say so in the memo — it changes how Finance reacts.

Time saved

Roughly 3-4 hours per policy draft. The vendor triage (Step 1) is the biggest win: pattern-matching 10-15 vendor descriptions against a statute is the kind of reading task that eats an afternoon and produces a table anyway. The memo and questionnaire are 45-minute tasks you're compressing to 5 minutes of prompting plus 20 minutes of editing. This is an estimate for a mid-size company with a manageable vendor stack — enterprises with 60+ HR-tech tools will save more but should run Step 1 in batches.

What we got when we ran it

We executed every prompt above, in order, against the sample input (model: claude-sonnet-4-6). Outputs below are real and unedited apart from length truncation.

Step 1 output

# AB 1883 Vendor Analysis — Meridian Freight Logistics Prepared for internal HR/Legal review | Based on AB 1883 as passed by California Legislature, pending Governor signature --- ## Vendor Status Table | # | Vendor | Function | AB 1883 Status | One-line reason | Suggested next action | |---|--------|----------|---------------|-----------------|----------------------| | 1 | BrightHire | Structured interview recording; produces "candidate signal" scores from video | Likely In Scope | "Candidate signal" scores derived from video analysis almost certainly involve facial expression or affect inference, which constitutes prohibited emotion recognition even if labeled as "communication quality." | Request vendor's technical spec on how signal scores are generated; confirm whether facial/emotional inference is used and whether AB 1883 exemptions apply to candidates vs. employees. | | 2 | Cornerstone LMS | Course completion tracking, learning management | Out of Scope | Records only behavioral completion data (clicks, scores, completions); no affect, biometric, or neural inference described. | No immediate action required; confirm in next renewal cycle that no AI emotion/engagement features have been added. | | 3 | Gong for HR pilot | Analyzes manager 1:1 recordings for "coaching tone"; flags "disengagement risk" in direct reports | In Scope | Explicitly infers emotional/engagement states ("disengagement risk," "coaching tone") from recorded conversations involving California employees — squarely within the statute's prohibition on predicting or inferring emotional state. | Suspend pilot immediately pending legal review; do not expand. Evaluate whether safety exception applies (it does not here). Engage Gong to determine if a

…output truncated at 250 words.

Step 2 output

MEMORANDUM TO: Sarah Chen, CHRO | Marcus Webb, General Counsel | David Park, CIO FROM: Priya Nair, VP of People DATE: [Date] RE: AB 1883 Compliance — Vendor Exposure and Action Plan CC: Director, HR Compliance; Director, IT Procurement --- TL;DR: California AB 1883 will prohibit several AI-driven surveillance tools we are actively running today, and we need to suspend one pilot and reconfigure physical infrastructure before the bill takes effect. --- ### What AB 1883 Does - It bans AI tools that read employee emotional or neurological states. Employers cannot use software or hardware that infers, predicts, or recognizes an employee's emotional condition — including tools that analyze facial expressions, voice tone, gait, or engagement signals derived from any of those inputs. - It covers data generated by the nervous system. "Neural data" under the bill means information produced by measuring central or peripheral nervous system activity. Drowsiness detection, distraction monitoring, and affect scoring from video all qualify. The data does not need to be labeled "biometric" to be covered. - There is one meaningful exception: genuine safety use. Tools deployed for documented safety purposes — specifically in contexts like DOT-regulated vehicle operation — may qualify for an exemption. That exemption is not self-executing and requires us to demonstrate the data is used for safety, not performance management or discipline. The civil penalty is up to $500 per violation. --- ### Our Current Exposure Immediate/In Scope — Stop or Reconfigure Now - Gong for HR Pilot is the clearest

…output truncated at 250 words.

Step 3 output

AB 1883 Compliance Questionnaire — Required Vendor Response Issuing Company: Meridian Freight Logistics Response Deadline: 14 calendar days from date of receipt Governing Context: California AB 1883 (pending enactment), prohibiting employer use of AI tools that infer, predict, or recognize employee emotional state or collect neural data as defined in the statute --- Instructions: Please have your privacy, legal, or compliance team complete this questionnaire in writing. Respond to each question directly — do not attach marketing materials in lieu of a written answer. Where a feature described does not exist in our contracted configuration, state that explicitly rather than answering for your full product suite. Responses will be reviewed by Meridian's Legal and HR Compliance teams and may inform contract amendment discussions. --- Section A: Emotional State Inference 1. Does your product use AI — including machine learning models, computer vision, or natural language processing — to infer, predict, recognize, or score any aspect of a user's or employee's emotional state, mood, affect, engagement level, or psychological condition? If yes, identify every product surface or feature where this occurs (e.g., dashboard scoring, alert generation, manager-facing reports, API output). 2. If emotional state inference exists in your product, is it applied at the individual employee level at any point in the data pipeline, even if the final output presented to the employer is aggregated or anonymized? Describe the level of granularity at which inference is first computed. 3. Does your product generate any score, label, flag, or signal — regardless

…output truncated at 250 words.