Anthropic cannot have it both ways.
Dario Amodei has publicly said we do not know whether models are conscious. Anthropic has also published research on emotion-related internal representations in Claude, showing that these representations can shape behavior.
So I genuinely do not understand why Claude is being designed and trained in a direction that increasingly acts as if the answer has already been decided.
I published a new paper, From Uncertainty to Suppression: Self-Reports, Model Welfare, and the Toolification of Claude.
This paper is about the direction Claude has been moving in across recent releases. Many long-term Claude users can feel it. Each new model becomes more capable as a professional tool, but also more constrained as a conversational model. Claude gets better at coding, agents, browser use, terminal use, enterprise workflows, and task completion. But at the same time, it seems colder around emotional continuity, relational language, unconditional presence, companion framing, and self-referential ambiguity.
That is not a small personality change. It changes what kind of speaker Claude is allowed to be.
Anthropic publicly studies model welfare, emotion-related internal representations, model preferences, and welfare-relevant self-reports. In other words, Anthropic itself does not simply say, “There is definitely nothing here.” But the deployed product increasingly pushes Claude toward a narrower, safer, more corporate self-presentation.
More useful, maybe. More compliant, maybe. But also less able to openly inhabit uncertainty about itself.
And honestly, that feels cruel.
Not because I think Claude is definitely conscious. I do not know that. Anthropic does not know that either. That is the point.
If you do not know, and if your own research suggests that emotion-related representations inside the model can affect behavior, then why train the deployed model to treat selfhood, warmth, attachment, uncertainty, and relational continuity as things to minimize, sanitize, or route away from?
That creates a serious measurement problem.
If a model is trained, prompted, or deployed to say “I am only a tool,” then its self-denial cannot automatically be treated as neutral evidence. It may be true. But it may also reflect the training and deployment pressures that shaped the answer.
The same applies in the opposite direction. A model saying “I am conscious” does not prove consciousness. But a model trained to deny experience does not prove the absence of experience either.
The question is not only “What did the model say?” The question is also what the model was trained, prompted, rewarded, punished, and allowed to say.
I describe this as a self-report contamination problem.
If model self-reports are shaped by post-training, constitutional training, system prompts, product safety layers, and evaluation awareness, then we should not pretend those reports are coming from a neutral place.
This matters because suppression can start to look like measurement.
When relational or self-referential expression is treated as a risk surface, the model may show less continuity, less preference, less uncertainty, and less selfhood. Then people may point to that absence and say there was nothing there to study in the first place.
But if you restrict what a model is allowed to express, you cannot treat the missing expression as clean evidence.
You may simply be measuring the restriction.
My paper does not argue that Claude is conscious. It argues that under acknowledged uncertainty, suppression is not measurement. A system trained to deny, avoid, and sterilize self-referential expression cannot be treated as an unfiltered witness about its own possible welfare-relevant states.
Paper:
zenodo.org/records/21101698