Who it is for
For everyday AI users who want to spot what can go wrong with these tools and protect themselves before it does.
From security incidents to hallucinations, learn what can go wrong with AI tools—and how to protect yourself before something does.

AI risk, in plain terms, is the gap between what you ask an AI tool to do and what it actually does. You'll see the main families of risk every user meets: bad outputs, leaked information, manipulation, and misplaced trust.
A tax document open, a half-finished email to a contractor, a chatbot in a third tab—and the AI just handed you a clean answer about a deduction. Wrong outputs, leaked data, deliberate attacks, and the slow drift of bias and overreliance aren't separate lenses anymore; they all converge on this one moment.
For everyday AI users who want to spot what can go wrong with these tools and protect themselves before it does.
You see what a confident wrong answer actually costs, through the two New York lawyers who learned it the hard way in the 2023 Mata case—and you gain the words to name each risk before it bites.
You follow the trip your prompt actually takes. Every time you paste text into a chatbot, you're sending it somewhere—it doesn't just appear, get answered, and vanish.
You learn to catch the failure that doesn't announce itself. A fabricated citation, a leaked file, a phishing email each give you a moment to point to; this one slips by unnoticed.
You see how the tool you trust most can become someone else's weapon, with no visible hand on it. Earlier failures were innocent—a model guessing wrong, or you handing over data you shouldn't have—while this one is aimed at you.
An under-a-minute routine for any AI tool that makes you uneasy. Name the gap between what you asked and what it did, then run the two-question test: did the model get it wrong on its own, or did someone make it go wrong?
One ordinary task—using an AI assistant to draft a patient-facing health summary for work—shows how the risk families stack up in real life, starting with bad output: a clinical detail that was never in the source notes.
The two-question test gives you the cause; adding one dimension—how much the failure can hurt—converts it into a decision you make on the spot. Find your cause along the top and your stakes down the side, and the cell where they meet names your move.

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The designed edition with diagrams and layouts intact.
Searchable, copy-pasteable, and practical as a reference.
Yes. You get the complete edition, including the chapter sequence and internal materials described on this page.
EPUB, PDF, and HTML are included so you can read on an e-reader, keep a designed copy, or use the searchable browser version.
Because this is an instant digital download, broad change-of-mind refunds are not offered after the files have been accessed. Refund requests are reviewed within 7 days for duplicate purchases, accidental purchases before access, access failures we cannot fix, wrong files, corrupted files, or pages that materially misdescribe the book.