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Triage Score: A Counterfactual Risk Assessment Instrument

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Proposes a triage score that replaces a risk-only prediction with expected counterfactual utilities and shows point identification under an additive counterfactual utility assumption. Uses a randomized rollout of the PSA in Utah with about 7,000 arrest cases, AIPW estimators and neural nets, conditions on judge-facing affidavit text via open-source LLM embeddings (≈6,000 dims), and models judge decisions as single-blinded mediators. Finds PSA changes judges’ cash-bail choices (fewer releases follow AIs) and yields more ambiguous policy rankings than risk scores, motivating tailored utility elicitation.

AI-written summary · about

  1. 0:00Introduction
  2. 1:08From evaluation to implementation
  3. 3:07Selective labels problem
  4. 4:21Triage score framework
  5. 5:32Decision theoretic foundations
  6. 8:59Public Safety Assessment case study
  7. 14:39Evaluating algorithmic recommendations
  8. 17:23Risk versus triage score
  9. 22:32Statistical challenges in utilities
  10. 25:19Pre-trial risk assessment
  11. 29:51LLMs for unstructured data
  12. 31:01Policy evaluation and decisions
  13. 33:26Preliminary results
  14. 37:44Conclusion
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