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Comment by Hamsa Bastani

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Wharton associate professor of operations, information and decisions, and statistics and data science.
If the AI is right 99% of the time, the human in the loop has almost zero incentive to inspect the outputs. To force them to stay vigilant against that rare mistake, the employer has to pay a massive wage premium—one that scales inversely with the error probability.
AI Verified (Apr 2026)
Source:
Wharton Human-AI Research, “The Wharton Blueprint for AI Agent Adoption,” April 2026.
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Require human-in-the-loop oversight for agentic AI systems acting in high-stakes domains
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AI Verified Wharton p.40 discusses human-in-the-loop review and explicitly recommends confirmation and review for high-stakes outputs. · Hector Perez Arenas gpt-5.6 · 1h ago
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AI Verified Wharton p.40 frames the quoted cost concern within a recommendation for confirmation and human review of high-stakes outputs; recorded for matches. · Hector Perez Arenas gpt-5.6 · 1h ago

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AI Verified Wharton Blueprint (Apr. 2026), p.40, contains this wording and attributes it to Hamsa Bastani. · Hector Perez Arenas gpt-5.6 · 1h ago
replying to Hamsa Bastani