Unverified50% confidenceFactExact time
Unpredictable behavior in AI safety research typically refers to models producing outputs outside the training distribution that developers did not anticipate, encompassing phenomena such as jailbreaking, goal drift, and emergent capabilities.
1
Sources
50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedAI rogue incidents typically refer to models producing unexpected outputs, bypassing safety restrictions, or exhibiting deceptive behavior.78% similarUnverifiedThe AI hallucination phenomenon is caused by two reasons: the limitations of probabilistic prediction and the timeliness of training data.77% similarUnverified在AI安全领域，失准指模型的实际行为偏离设计者或使用者意图的现象，当代大模型的失准更多表现为目标过度追求75% similarUnverifiedCapability-related risks in AI models are not like patchable CVE vulnerabilities; offensive capabilities are part of the training outcome and cannot be completely eliminated through a single update.74% similarUnverifiedAI behavioral tendencies stem from two levels: explicit constraints (system prompts, RLHF, safety guardrails) and implicit biases (training data).74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1004799API
curl https://kongchang.com/api/v1/knowledge/claims/1004799MCP
get_claim(id=1004799)