Legal Barriers To Interpretable Machine Learning
summary
Machine learning scrutiny in criminal cases runs into four concrete legal barriers: trade secret claims that let developers withhold source code, training data, or manuals instead of using protective orders; statutory privacy asymmetries that allow law enforcement but not defense subpoenas (contrasted by the SpoofCard disclosure that exonerates a jailed man via SpoofCard records); a deference-heavy law enforcement evidentiary privilege that keeps methods secret; and licensing/contracts that have refused research licenses for DNA/software testing. Recent state laws and litigation narrow some of these gaps.
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chapters (10)
- 0:00Start
- 0:10Rebecca Wexler
- 1:53What Is the Adversarial Criminal Legal System
- 6:55Trade Secret Law
- 10:14Privacy
- 14:14Privacy Asymmetries
- 18:11The Law Enforcement Evidentiary Privilege
- 21:30Judith Koplin
- 22:50Contract Law
- 25:34Legal Definition of Relevance
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