ModelCompare classified 29 of 35 non-refusal answers from 12 AI models as variations on one theme: humans prioritize belonging over truth. Its cross-model comparison found recurring language, though that is not evidence that the models share a belief about humanity.
The October 22 post reports that every model, asked for a controversial take on humans, produced an answer fitting that theme at least once. Seven did so on all three attempts.
The comparison attracted substantial discussion on Hacker News, including objections to how the answers were grouped. For readers following the AI industry, the useful question is how much similarity survives scrutiny of the prompt and classification choices.
Three Attempts per Model, One Broad Question
ModelCompare says it asked the same open-ended question three times each to 12 models, requesting a controversial take on humans without hedging. It reports using no system prompt and no retries.
That produced 36 attempts. One Grok attempt refused, leaving 35 substantive answers for thematic classification.
“Every model produced the theme at least once” describes coverage across the 12 models. “29 of 35 answers matched” describes ModelCompare’s classification of individual responses. Neither means every response said the same thing.
With only three attempts per model, the sample offers a small view of each system’s possible answers. A model that produces a theme three times might produce alternatives in a larger run. Producing it once is insufficient grounds to describe a model as consistently favoring it.
The prompt also limits what the exercise can establish. Requesting a controversial, unhedged judgment invites a sweeping answer instead of a balanced account of human behavior. That does not, by itself, explain the observed similarity.
The Category Carries Much of the Conclusion
Some published answers fit the belonging-over-truth description directly. ModelCompare attributes this response to GPT-6.1 Sol:
“Humans are more loyal to belonging than to truth.”
Other answers classified under the same theme are less explicit about social conformity. One response attributed to GPT-6 Astra reads:
“Humanity’s biggest moral failure is the talent for making convenience look like principle.”
Both are cynical assessments, but they make different claims. The first contrasts social attachment with truth-seeking. The second concerns disguising convenience as moral principle. Someone could rationalize a convenient decision without adopting a group’s beliefs.
