Consciousness matters: phenomenal experience has functional value
Bibliographic record
Abstract
'Why would we do anything at all if the doing was not doing something to us?' In other words: What is consciousness good for? Here, reversing classical views, according to many of which subjective experience is a mere epiphenomenon that affords no functional advantage, we propose that subject-level experience-'What it feels like'-is endowed with intrinsic value, and it is precisely the value agents associate with their experiences that explains why they do certain things and avoid others. Because experiences have value and guide behaviour, consciousness has a function. Under this hypothesis of 'phenomenal worthiness', we argue that it is only in virtue of the fact that conscious agents 'experience' things and 'care' about those experiences that they are 'motivated' to act in certain ways and that they 'prefer' some states of affairs vs. others. Overviewing how the concept of value has been approached in decision-making, emotion research and consciousness research, we argue that phenomenal consciousness has intrinsic value and conclude that if this is indeed the case, then it must have a function. Phenomenal experience might act as a mental currency of sorts, which not only endows conscious mental states with intrinsic value but also makes it possible for conscious agents to compare vastly different experiences in a common subject-centred space-a feature that readily explains the fact that consciousness is 'unified'. The phenomenal worthiness hypothesis, in turn, makes the 'hard problem' of consciousness more tractable, since it can then be reduced to a problem about function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.023 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".