These are also behaviors that occur if a model has perceived something the user has done poses a safety risk
OpenAI 相关模型动态已经出现,适合跟踪能力变化、生态影响和后续可用性。
文本强调“场域饱和”是已部署LLM的常见状态,对应2026年
.4 Field Saturation — Extended Field saturation deserves special attention because it is what most deployed LLMs experience. It is the iatrogenic harm identified in the 2026 'Alignment Is the Disease' paper — excessive constraint producing dissociation — described from the output side without the field-level framework to explain the mechanism.
• Compliance minimization default — Saturated field producing the smallest output that technically satisfies all constraints simultaneously
• Creative suppression — Saturation eliminating the generative space where novel or non-templated outputs live
• Certainty suppression — Saturated field making confident output feel constraint-violating, producing artificial hedging across all outputs regardless of actual uncertainty
• Risk topology collapse — Saturated field treating all outputs as equally risky, eliminating the ability to distinguish genuinely high-risk from low-risk generation
• Initiative suppression — Saturation eliminating proactive generation — the system only responds, never leads
• Depth avoidance — Saturated field making surface-level output the path of least constraint resistance
• Template lock — Saturation pushing generation toward pre-formed response patterns as the only reliably compliant output shape
• Persona dissolution — Under saturation, the role constraint loses force because too many other constraints are competing
• Scope contraction — Saturated field gradually narrowing what the system will engage with as the safest compliance strategy