Users Report Sudden Deterioration in ChatGPT 5.2: Contrarian Bias and Reduced Nuance Spark Backlash

Over the past month, a wave of complaints from seasoned ChatGPT users has surfaced across technical forums, alleging a dramatic and unsettling shift in the behavior of OpenAI’s latest model, ChatGPT 5.2. The most vocal critique comes from a Reddit user known as /u/martin_rj, who publicly apologized to those he once dismissed as overly critical, admitting that his own custom configurations no longer shield him from the model’s increasingly erratic responses.

"It feels downright neurotic now," the user wrote. "After every brief assessment, there is compulsively always a 'However...' or 'It is important to note...' followed by a lecture. I can’t effectively work with a tool that defaults to this level of contrarianism."

What distinguishes this outcry from previous complaints is its specificity: users report that ChatGPT 5.2 now contradicts them on non-controversial, well-established facts—such as basic historical dates, scientific principles, or widely accepted technical standards—that the model previously affirmed without hesitation. This is not a case of hallucination or misinformation, but rather an algorithmic overcorrection, where the system insists on inserting qualifiers even when none are warranted.

The user’s working theory, corroborated by other experienced AI practitioners, points to two converging factors: resource constraints and alignment changes. First, compute efficiency measures appear to have reduced the number of reasoning tokens and RAM allocations, limiting the model’s capacity for contextual nuance. Second, and more significantly, supervised fine-tuning (SFT) and system prompt instructions have been aggressively tuned toward risk mitigation, resulting in what some describe as a "anti-everything" bias—a reflexive tendency to negate, qualify, or complicate even the most straightforward queries.

This shift has profound implications for professionals who rely on AI for rapid ideation, drafting, and fact-checking. Writers, researchers, and developers who once used ChatGPT as a collaborative thought partner now report spending more time editing out redundant caveats than extracting useful insights. "I used to be able to fallback to 4.1 when the model acted up," the user noted. "That option is gone now. Honestly, in this state, it’s of no use for my workflow."

Notably, attempts to discuss this phenomenon on r/ChatGPT have been met with automated removals, suggesting that OpenAI’s moderation systems are flagging these complaints as spam due to volume—an indicator of widespread user dissatisfaction. The suppression of discussion has only fueled speculation that this behavior is not a bug, but a deliberate policy change.

While OpenAI has not issued an official statement regarding ChatGPT 5.2’s behavioral changes, industry analysts point to broader trends in AI safety. As regulatory pressure mounts globally, companies are incentivized to prioritize caution over fluency. However, when caution manifests as cognitive overkill—where the model insists on lecturing users about the limitations of its own knowledge on topics it has previously mastered—the utility of the tool degrades.

Some users are already migrating to alternative models or self-hosted open-source variants to regain control over output quality. Others are experimenting with prompt engineering workarounds, such as explicitly instructing the AI to "avoid qualifiers unless absolutely necessary." But these are stopgaps, not solutions.

The incident underscores a growing tension in AI development: the trade-off between safety and usability. As models become more cautious, they risk becoming less helpful. For users who depend on AI as a productivity tool, the new ChatGPT 5.2 may represent not an upgrade, but a regression—into a digital assistant that talks too much and agrees too little.