How to Design Human Oversight for AI Agents with ZizkaDB

Description and use

<p>This is the next how-to guide in the series. The earlier guides covered individual functions, instrumentation, audit preparation, incident investigation, and selling to enterprises. This one covers a requirement that most teams get wrong in a quiet way: human oversight. Many teams put a person somewhere in the loop and consider the box ticked. Regulators, and your own risk team, will ask a harder question: could that person actually understand what the agent was doing, and could they have stopped it?</p> <p>It is written for CTOs, heads of risk, and product leads at banks, insurers, and ver

Problem

<p>This is the next how-to guide in the series. The earlier guides covered individual functions, instrumentation, audit preparation, incident investigation, and selling to enterprises. This one covers a requirement that most teams get wrong in a quiet way: human oversight. Many teams put a person somewhere in the loop and consider the box ticked. Regulators, and your own risk team, will ask a harder question: could that person actually understand what the agent was doing, and could they have stopped it?</p> <p>It is written for CTOs, heads of risk, and product leads at banks, insurers, and ver

Outcome

<p>This is the next how-to guide in the series. The earlier guides covered individual functions, instrumentation, audit preparation, incident investigation, and selling to enterprises. This one covers a requirement that most teams get wrong in a quiet way: human oversight. Many teams put a person somewhere in the loop and consider the box ticked. Regulators, and your own risk team, will ask a harder question: could that person actually understand what the agent was doing, and could they have stopped it?</p> <p>It is written for CTOs, heads of risk, and product leads at banks, insurers, and ver

Evidence

How to Design Human Oversight for AI Agents with ZizkaDB

Source