Montreal AI Ethics Institute's (MAIEI) Submission to the World\n Intellectual Property Organization (WIPO) Conversation on Intellectual\n Property (IP) and Artificial Intelligence (AI) Second Session
Bibliographic record
Abstract
This document posits that, at best, a tenuous case can be made for providing\nAI exclusive IP over their "inventions". Furthermore, IP protections for AI are\nunlikely to confer the benefit of ensuring regulatory compliance. Rather, IP\nprotections for AI "inventors" present a host of negative externalities and\nobscures the fact that the genuine inventor, deserving of IP, is the human\nagent. This document will conclude by recommending strategies for WIPO to bring\nIP law into the 21st century, enabling it to productively account for AI\n"inventions".\n Theme: IP Protection for AI-Generated and AI-Assisted Works Based on insights\nfrom the Montreal AI Ethics Institute (MAIEI) staff and supplemented by\nworkshop contributions from the AI Ethics community convened by MAIEI on July\n5, 2020.\n
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".