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Bachelor's · Chapter 10 · English

Chapter 10 — Ethics and data

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Chapter 10 — Ethics and data

Lesson map

Lesson 10 published. Map, example, EX028.

flowchart TD
  N0["Learning outcomes"]
  N1["10.1 Beyond the law"]
  N2["10.2 Effects on groups"]
  N3["10.3 Frameworks"]
  N4["10.4 Ethics in governance"]
  N0 --> N1 --> N2 --> N3 --> N4
  N4 --> EX["Worked example"]
  EX --> Q["Exercise EX028"]

Logical drawing

flowchart LR
  N0["Learning outcomes"]
  N1["10.1 Beyond the law"]
  N2["10.2 Effects on groups"]
  N3["10.3 Frameworks"]
  N4["10.4 Ethics in governance"]
  N0 --> N1 --> N2 --> N3 --> N4 --> Q["EX028"]
[Learning outcomes]
    |
    v
[10.1 Beyond the law]
    |
    v
[10.2 Effects on groups]
    |
    v
[10.3 Frameworks]
    |
    v
[10.4 Ethics in governance]
    |
    v
[Worked example] --> [Exercise EX028]

Learning outcomes

You will (1) apply ethical reasoning to data uses; (2) consider effects on different groups; (3) explain the role of ethics alongside law.

10.1 Beyond the law

Some data uses are legal but questionable. Harbourline's marketing team proposes using purchase patterns to infer which members are pregnant and send baby product offers. Amara considers whether members would expect this, whether it could cause harm if offers reached a household before the person chose to share news and whether the benefit justifies the risk. She concludes that legality is a minimum, and that governance should also ask whether a use is fair and expected. Marketing pauses the proposal for review.

10.2 Effects on groups

Amara examines a proposal to offer discounts only to members using the mobile app. Older members and those without smartphones would lose out. She checks synthetic member data and finds app users are mostly younger. She suggests offering the same discounts through printed vouchers at tills. She learns that data-driven decisions can disadvantage groups without anyone intending it, and that checking effects across groups should be routine before launching such schemes. Marketing adopts the voucher option for the next campaign. Older members welcome it.

10.3 Frameworks

Dr. Lindqvist introduces simple frameworks: consider the consequences for all affected, respect people's autonomy and expectations, treat groups fairly and be transparent about practices. Amara applies them to the pregnancy inference proposal and writes a short assessment recommending against it. Marketing accepts a revised plan offering baby product discounts to members who choose a family interest in their profile. She notes that frameworks help structure discussion rather than producing automatic answers. Her assessment is kept as an example for future reviews. Marketing agrees.

10.4 Ethics in governance

Amara proposes that Harbourline's data governance group review new data uses that raise ethical questions, using a short checklist. The group would include staff from marketing, stores and data protection. She notes that ethical review works best early, before campaigns are designed, and that it should be quick for low-risk uses. Dr. Lindqvist adds that organisations trusted with data must earn that trust continuously through their choices. The governance group pilots the checklist for three months and finds that most reviews take less than an hour.

Worked example

Amara assesses a pregnancy inference proposal and recommends against it, finds app-only discounts disadvantage older members, applies simple frameworks and proposes an ethics checklist for new uses.

Synthetic case. Proposals are synthetic.

Errors and limits

Legal does not mean acceptable; ask whether uses are fair and expected.

Exercises

Continue studying — lesson 10 (chapter 10 of 40)

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