16 - Between Device and Demiurge : AI and the Legal Status of AI Creations
Bibliographic record
Abstract
The recent DABUS case has shed light on a fundamental disagreement over how the law should understand inventorship.Whereas Australia 2 and South Africa 3 have ruled that an artificial intelligence (AI) may qualify as an inventor, the United Kingdom, 4 Canada, 5 the United States, 6 and the European Patent Office 7 have ruled otherwise.Although the problem cannot be framed as clearly for copyright (which traditionally does not require the same amount of paperwork as a patent), similar questions and disagreements have been raised by decisions to grant co-authorship to an AI application in India (Sakar, 2021).To explore various legal ways to protect AI creations, there have been consultations by the WIPO (WIPO Conversation on Intellectual Property and AI of 2020) and in several countries,
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".