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Chapter 2 Priority Map

Priority 1 — Must Know Cold

Target Standard Typical clue
Definition / scope Ethical handling across procurement, storage, management, interpretation/application and disposal, considering effects on people/organizations. “Which concern belongs to Data Ethics?”
Three central concerns People impact; misuse; economic value/ownership. Why quality/use/sharing has ethical consequence.
Belmont + Menlo Respect; Beneficence; Justice; Law/Public Interest. Short dilemma asking most direct principle.
Ethics vs legality Law is not the whole ethical standard. “It is legal, therefore fine.”
Six risk areas Timing; visualization; definitions/comparisons; bias; integration; obfuscation. Classify the failure mechanism.
Principle→Risk→Practice→Control Value → possible harm → expected behavior → enforce/test mechanism. “Which one is a control?”
Four checkpoints Population; capture; analysis; results/use. Where to review personal-data project risk.
Governance role Standards/policy/oversight + BI/analytics review with legal counsel. Best organizational response.

Priority 2 — Must Understand

Data Quality as ethics

Inaccurate/incomplete data can materially change decisions affecting people. Reject answers that treat quality as only technical housekeeping.

Privacy-management themes

Purpose, limitation/minimization, accuracy, retention, safeguards, transparency, accountability, participation/redress. Use these to reason about overcollection, hidden reuse, indefinite retention and weak safeguards.

Online-data issues

Ownership, Right to be Forgotten, identity and freedom of speech highlight control, persistence, profiling, reputation and harm.

Bias across the lifecycle

Bias may enter collection, sample selection, analysis, interpretation, context/culture and presentation.

Transformation/integration

Trust requires provenance, lineage, Metadata, quality, ownership/protection and auditable change history as data moves.

Obfuscation

Direct identifiers removed ≠ permanently safe. Combination can re-identify.

Ethical culture

Leadership, policy/code, communication, training, safe escalation, no retaliation, monitoring and OCM make ethical expectations real.

Priority 3 — Must Distinguish

Confusion pair Deciding distinction
Ethical vs Legal Legal = codified requirements; ethical = broader responsible judgment.
Privacy vs Data Ethics Privacy is a major subset; Data Ethics includes quality, bias, ownership, interpretation, visualization, transformation and social impact.
Principle vs Practice vs Control Value/expectation vs expected behavior vs enforce/test mechanism.
Bias vs poor Data Quality Systematic slant vs broader unreliability/unfitness.
Accurate numbers vs ethical presentation Correct values can still mislead by timing, scale, definitions, comparison or omission.
Anonymization vs safety Masking reduces exposure but does not guarantee no re-identification.
Governance vs individual responsibility Governance sets/oversees standards; practitioners still recognize/escalate risk.
Legal counsel vs Governance Legal interprets law/legal risk; Governance owns organizational handling standards/decision oversight.

Priority 4 — Must Apply

Personal-data analytics dilemma

Identify affected people, possible harm and fairness; apply ethical principles; involve Governance/legal review; document and mitigate.

Misleading chart

Fix the scale/context/omissions rather than defending technically correct values.

Unclear comparison

Define the population/terms and compare like with like.

Biased analysis

Challenge selection/sampling/confirmation behavior; test alternatives and disclose exclusions.

Integration risk

Verify lineage, quality, Metadata, ownership/protection and remediation history before consequential use.

Privacy reuse/retention

Ask purpose, necessity, notice/consent where relevant, retention need, safeguards and accountability.

Ethical culture gap

Assess current state; map principles/risks/practices/controls; build strategy/roadmap; train; monitor; create safe escalation.

Possible ethics breach

Raise it through appropriate channels. Do not rely solely on automated monitoring; protect reporters from retaliation.

Low-priority detail

Do not displace the above with: - publication years/authors/bibliographic detail; - exact wording of every privacy principle across every jurisdiction; - current-law developments beyond the source chapter; - exact numerical examples used to illustrate timing/statistics; - detailed masking/security implementation beyond Chapter 2's ethics/governance purpose.

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