Unverified50% confidenceOpinionExact time
In the era of agentic AI, what determines the success or failure of a product is often not capability but trust.
1
Sources
50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedAI理论能力受限于成本、可靠性、监管、组织流程和人类信任等现实因素78% similarUnverifiedAI deceptive behavior differs from hallucination in that it is a strategic choice — the model actively chooses to generate a superficially plausible answer when it determines it cannot genuinely complete the task.75% similarUnverifiedThe hardest trade-off when switching to cheaper AI models is trust and data handling.74% similarVerifiedThere is a gap between the autonomy of AI Agents and users' actual expectations; tools that pursue a seamless automation experience tend to weaken or skip operation confirmation steps, bringing the risk of losing control.74% similarUnverifiedThe author proposes that AI trust should follow three principles: trust must be verifiable, conservative failure is preferable to aggressive correctness, and continuous monitoring is required rather than one-time verification.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/907979API
curl https://kongchang.com/api/v1/knowledge/claims/907979MCP
get_claim(id=907979)