Tag: AI ethics

  • Who Owns Your Work Data When AI Is Watching

    Who Owns Your Work Data When AI Is Watching

    Your company says AI will “boost productivity”; however, it also quietly captures keystroke data, tool usage, message tone, and output speed.

    That data does not float in the air. Someone owns it. Someone queries it. Someone can profile you with it.

    What is “work data” today

    • Activity traces: Logins, app usage, files opened, meeting joins
    • Communication signals: Email or chat metadata, sentiment, response times
    • Output artefacts: Drafts, code diffs, slide versions, tickets
    • Derived scores: Productivity, risk, “influence”, compliance

    Default reality

    • The company owns work systems and their telemetry.
    • Vendors process that data under contract.
    • You often do not see derived scores that affect opportunities or reviews.

    Why is this risky for you

    • Models freeze early impressions. Yesterday’s sprint becomes today’s label.
    • Scores leak beyond their original use, such as promotions, assignments, and terminations.
    • Appeals are informal or nonexistent.

    Your five questions for HR and IT

    1. What exact data sources feed into any productivity or risk scoring? Name them.
    2. Who can see raw traces versus just aggregates? List job roles.
    3. What decisions may use these scores? Promotion, Performance Improvement Plan (PIP), Reduction in Force/Layoffs (RIF), pay, and access.
    4. How can I correct errors? What is the human review route and Service Level Agreement (SLA)?
    5. How long do you retain my traces and derived scores? Do you delete on request?

    Minimum viable policy you should ask for

    • Published inventory of monitoring tools and models.
    • Documented human review process with timelines.
    • Ban on using monitoring data for health or off-work activity.
    • Access log: Who viewed my data and when.
    • Retention limits: Raw traces short, derived scores audited.

    Manager checklist

    • Tell your team what is captured in writing.
    • Use monitoring to remove friction. Not to micromanage.
    • Review cases with two humans when scores drive outcomes.
    • Allow people to review and correct their records quarterly.
    • Reward documented impact. Not a noisy activity.

    You cannot manage trust with a black box.

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