Unverified50% confidenceDecision RuleExact time
The specific metric for monitoring approval fatigue is counting the proportion of each type of request that is 'approved as-is'; when the pass rate of a certain low-risk action stays high over time, it should be automated.
1
Sources
50%
Confidence
Long-term
Relevance
10/16/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe pilot phase should set quantifiable acceptance metrics, such as the completeness rate of work-hour records, the processing time for exception entries, and user activity, and continuously collect data; only when the pilot metrics reach preset thresholds and feedback shows the process is workable should the next phase begin.78% similarUnverifiedWhen evaluating tasks such as persuasiveness detection, it is usually necessary to report the random baseline, the majority-class baseline, and human annotation agreement, in order to judge the true gain of the number 0.57.76% similarUnverifiedMonthly review is a common minimum review frequency requirement for maintaining the timeliness of an AI risk register.74% similarUnverifiedWhen evaluating whether to automate, factors such as the degree of task standardization, error tolerance, and maintenance costs must be weighed.73% similarUnverifiedThe evaluation method described in the official guide is a lightweight performance test, with the core focus on the endpoint's response behavior rather than model quality, and the measurable metrics include single-request latency, throughput under batch requests, and whether the endpoint can stably return results.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1044228API
curl https://kongchang.com/api/v1/knowledge/claims/1044228MCP
get_claim(id=1044228)