The Accountability Baseline: Why the “Human-in-the-Loop” is Your Newest Discovery Risk in Insurance Claims Handling | Houston Harbaugh, P.C.

Here is a summarized list of the key points from “Defending the Algorithm™ Newsletter: Insurance AI Insights – Edition 1”:

Efficiency Creates Liability:
- The promise of reduced cycle times through AI in insurance claims handling also brings new legal exposures and challenges in accountability.
- The focus of the insurer’s duty of good faith shifts to defending decisions made by AI, which professionals may not fully understand.
Regulatory Shift:
- States like Arizona and Colorado have implemented mandates requiring human oversight and explanations for AI-based decisions, especially for claim adjudications involving medical judgments and extracontractual claims.
- Regulators emphasize that accountability cannot be outsourced to AI.
The Danger of “Rubber Stamp” Adjusters:
- Claims professionals who uncritically accept AI recommendations without active review are at risk in bad faith litigation.
- Documentation of human discernment and understanding of AI-assisted recommendations is crucial for defense.
Practical Guardrails:
- Understand what data the AI uses.
- Explain the logic of AI-assisted decisions in plain language.
- Document any human deviations from AI recommendations.
- Require AI vendors to provide explainability documentation.
A Collaborative Approach:
- The focus remains on responsible deployment of AI in claims handling.
- Future editions will cover broader impacts of AI on underwriting, fraud detection, claims decisions, and commercial litigation.