HIGH_DENSITY_DATA
FILE_REF: ai-alignment-problem // VERIFIED_ENTRY
ENTRY_DATE2020_01_01
The Alignment Problem
01_ABSTRACT_SYNOPSIS
The Alignment Problem gives product teams a grounded overview of how machine learning systems drift away from human values through biased data, poorly specified objectives, and opaque optimization. Brian Christian blends research history with accessible explanations that help non-specialists understand where AI systems fail and what responsible teams should watch for. It is especially useful for PMs translating ethics conversations into real product constraints.
02_INDEX_NODES
- How value alignment failures emerge from data, incentives, and objective functionsP.042
- Why bias and reward hacking matter for everyday product decisionsP.084
- A broad map of the main safety and ethics debates around machine learningP.126
- How PMs can turn abstract ethics concerns into better product constraintsP.168
PUBLICATION_DATE2020
ISBN_RECORDN/A
PAGES496_UNITS
LANGUAGEENGLISH
LEVELINTERMEDIATE
RECORDS_IDai-alignment-problem
FILE_SIZE24.8_MB_RAW
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