Privacy and data hygiene when using AI at work — companion videos

IBM Technology

Jeff Crume's lightboard explainer of the three places generative AI introduces risk — the data, the model, and the usage — and what good controls look like for each. Useful for the article's argument that "be careful" isn't enough; you need to think about which category of risk you're actually exposed to as an employee.

What you should get from this: You can name the three risk surfaces generative AI adds at work — data, model, usage — and describe the controls each one needs.

Watch or know first: None — aimed at employees, not security engineers.

IBM Technology

Sits below our usual 100K bar but earns the slot because it's the single best short explanation of why an employee using a personal ChatGPT account on work problems is the actual risk most companies face. Crume's "don't say no, say how" framing is the same posture the article takes — you're not trying to ban AI, you're trying to make safe use the easy default.

What you should get from this: Explain why personal AI accounts create workplace data risk and how to set safer boundaries.

Watch or know first: None — watchable cold; it lands harder after the primary pick's three risk surfaces.