14. Doing the Right Thing
14.3 Where this chapter collides with the rest of the book
This is the chapter's real value: it retroactively reframes technical decisions you already made.
| Technical decision | The ethical dimension it carries |
|---|---|
| Ch 1 — "we store data because we think its value exceeds the cost" | The cost includes breach liability, compliance fines, and the SAFETY RISK TO USERS when data reveals criminalized behavior (abortion travel, sexuality). Data minimization is a design constraint, not a compliance chore |
| Ch 3 — event sourcing keeps every event forever | Directly conflicts with GDPR erasure. Crypto-shredding moves the problem, doesn't solve it |
| Ch 4 — vector embeddings and semantic search | The model learns whatever bias is in the corpus — §1.2 |
| Ch 5 — data outlives code | So does personal data. The 5-year-old row is still about a real person |
| Ch 6 — derived data can be recreated from the source | Which means a deletion must propagate to EVERY derived copy, and you must know where they all are |
| Ch 7 — shard per tenant | Turns GDPR export and deletion into "operations on their shard" — one of the seven advantages listed there, and the most underrated |
| Ch 11 — batch inference at scale | Where §1.1's "algorithmic prison" is manufactured, millions of decisions at a time |
| Ch 12 — immutability is a virtue | §2.6's "it stays around, festering." Immutability and the right to be forgotten are in direct tension |
| Ch 13 — auditability and provenance | The same machinery that lets you debug a pipeline lets you EXPLAIN A DECISION TO A JUDGE (§1.3) and prove you deleted what you said you deleted |