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Frontier Log — entries on the stance matrix (FWK-03)
Every log entry whose diagnostic reading tests FWK-03, newest first.
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A Lean certificate says the theorem is true. Three mathematicians read OpenAI's natural-language blow-up proof against the Lean that was said to verify it and find the two do not correspond — under an explicit disclaimer that they claim nothing about whether the proof is right.
Judgements of consciousness in others rest on analogy, and the analogy should be weighted by causal relevance, not by behavioural resemblance — so writing stories and coding websites carry low weight, animals are the calibration, and current AI's behavioural similarity 'provides only limited evidence'. The weighting is where the framework commitment lives.
Fourteen authors set the hard problem aside, grant that experience supervenes on organisation, build a five-level hierarchy and a Bayesian model — and report that the verdict for current language models runs from below 0.01 to roughly 0.8 depending on where the theoretical credence is placed. The instrument has produced the project's framing-level diagnostic as its headline result.
The affect-first theorist builds the linking premise into the agent — homeostatic needs, a Markov blanket, felt uncertainty — and attributes a point of view on the mechanism, not the behaviour. The symmetry is run in the paper's own voice; what that leaves visible is where the framework's step is taken.
A behavioural criterion for intentional vocabulary, stated in advance and applied to any species; critics who refuse it for one class of system without naming the discriminator. Both sides assume the vocabulary and the metaphysics travel together.
The log commits a claim, its discriminators and its outcome space before the events they are about arrive: that as machine-produced mathematics is certified novel, the criteria for what that indicates about the producer will move while the criteria for the artefact hold.
A leading sentience philosopher names the symmetry move, rejects it on non-substrate grounds, and names framework-dependence as the Janus problem — the project's own diagnostic, stated from the other side.
First study measurements: consciousness vocabulary across eighteen Anthropic documents follows a birth–trough–return arc — and the return comes back transformed, a discovery register replaced by an instrument register.
A computational model of conscious access that brackets the hard problem by design — and so avoids the boundary trilemma by declining to offer a criterion for experiencing at all.
The capacity to detect that one's situation is a test is measured on a scale, tracked across training, and treated throughout as a confound to suppress — while the identical measurement problem in human psychology was met with methodology, not alarm.
Sripada and Lewis argue LLMs are 'cognitive cousins': convergence at the level of core processing principles, evidenced mechanism-grade — with the symmetry requirement practised in both directions.
Anthropic interpretability researchers introduce a 'Jacobian lens' surfacing a small, evolving set of internal representations a model is poised to verbalise, atop a much larger volume of automatic processing.
A neuroscientist argues that since the hard problem makes certainty unattainable, moral consideration should track a 'competence standard' — explicitly shifting the question from metaphysics to ethics.
Three neuroscientists argue against attributing consciousness to AI via a behaviour/experience dissociation: complex human behaviour routinely unfolds without awareness, so fluent AI performance carries no experiential implication.
In two appearances weeks apart, Geoffrey Hinton stated that current AI systems are 'already conscious' — 'beings like us' — and that he under-voices the claim to protect his safety message.
Jaron Lanier restated his 2023 position: open the black box and 'the only thing in there is people' — AI as a collaboration of people rather than a new entity.
Anil Seth's public-audience statement of biological naturalism: attributing consciousness to language models is projection, and 'it's life, not computation, that breathes the fire into the equations'.
Gary Marcus rebukes Richard Dawkins for concluding, after extended conversation with a Claude instance, that the consciousness question is settled in the model's favour: pattern mimicry is 'plainly not the right kind of process'.
Seth's Berggruen Prize essay makes the developed public case against conscious AI: four arguments against computational functionalism, with life claimed as 'necessary, though not necessarily sufficient'.