14.5 Self-test

Why is "a technology is not good or bad in itself" not a defence for engineers?

What does the book say ethics is, and what does it say ethics is not?

Why are organizations structurally biased toward "no" in automated decisions, and why is that rational for them but harmful in aggregate?

Define "algorithmic prison." Contrast it with the presumption of innocence.

Give the fair case for algorithmic decision-making over human judgment.

Explain the mechanism by which a model amplifies bias. Why doesn't excluding protected attributes fix it?

What does "machine learning is like money laundering for bias" mean?

Why does the book say moral imagination is required, and that only humans can provide it?

Give three accountability questions raised by automated decisions.

Contrast a traditional credit score with ML-based scoring on: the question answered, the inputs, and the possibility of correction.

Why does a correct probability distribution not justify a decision about an individual? Give the life-expectancy example.

Give the dual-use example: the same analytics capability used for good and for predation.

Trace the credit-score/employment feedback loop step by step.

Why is the German gas station example unsettling? What did nobody program?

What is systems thinking, and what is the key question it asks of a data system?

Describe the four-stage drift from "service for the user" to "surveillance."

Perform the data→surveillance substitution on a sentence from your own workplace.

Why does the book say the surveillance infrastructure exceeds what totalitarian regimes could achieve — and what is the one difference?

Give two reasons people accept corporate surveillance, and explain why each is a position of privilege.

Give three examples where surveillance is already used for consequential decisions, not just recommendations.

Give the four reasons "the user consented" fails as a defence. Which one concerns non-users?

What does GDPR require of consent, word for word on the key phrases? Name two other lawful bases.

Define privacy as a decision right. Why is "privacy is dead" a misunderstanding?

Explain the transfer of privacy rights to the data collector. Why do companies keep the outcome secret?

Why is "you can't be reidentified from that ad bucket" not a sufficient answer?

What is the limitation of user-facing privacy settings?

Contrast "data exhaust" with "data as labor." Which does the book endorse, and why?

Give five ways data can end up somewhere you didn't intend, even with good intentions.

Why "the new uranium" rather than "the new oil"?

What does Schneier's "poor civic hygiene" line mean for a data-retention decision you make today?

Draw the Industrial Revolution parallel: what were the harms, what were the safeguards, and what did they cost?

State Schneier's pollution framing. What is the environmental challenge of the information age?

Why does GDPR's purpose limitation directly conflict with the philosophy of big data? Has enforcement changed the culture?

Give the strongest argument against data protection regulation, as the book states it.

What is the single concrete first step the book recommends, and what is the one-line justification for it?

Name three of your own technical decisions from earlier chapters that carry an ethical dimension, and say what it is.

Reflective question (no right answer): take a system you've actually built or worked on. Who is its customer — the user, or someone else? What data does it collect that isn't needed to deliver the service to the user? Who is harmed if that data leaks, and who is harmed if it doesn't exist? What would you change if you started again, and what stops you changing it now?