Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Creativity and expression are no longer a forte of a human being. Advanced algorithms, also known as AI, are capable of creating content of their own such as painting and composing music. In the era of Industry 5.0, Google's AI company, DeepMind, has created software that can produce novel music sounds and unique images. If such things had been created by humans, they would have been subject to protection under copyright laws but since machine lacks the characteristics of humans, the question arises about who owns the copyrights for the content. US circuit court has recently held in the case of Naruto et al . vs David Slater that animals, other than humans, cannot sue for copyright protection. Furthermore, WIPO member countries enacted a law that states non-humans are not subjected to protection under IP laws. Furthermore, it depends a lot upon the interpretation of courts for originality requirements under authorship and if it requires creative inputs from humans. In India, to get protection under copyright, one must prove creativity in addition to variation from previous works. Another issue that this paper reflects on would be the determination of several possibilities for assigning authorship where an object has been designed by AI. This paper will analyse the claims of the stakeholders such as programmers, users, and AI software itself to determine who has the greatest claim towards ownership of products and further possibilities for assigning authorship where an object has been designed by AI, thus analysing the question of “who is the author” of the works created by AI. This piece contributes to the literature on conundrums arising in the Industry 5.0 era, which on hand is striving hard to develop technologies in assistance of AI but is also facing issues on who owns the assets and liabilities arising out from the labour of AI. With the press release of the Japanese government that plans to create a legal framework, especially for the works created by AI to protect copyrights on novels, music, and other works, it becomes a relevant question if laws, including international treaties, should redefine the term “authorship” and include non-legal entities as well under the umbrella or should develop a new legal framework for AI.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it