The DOI matches its Crossref record.
Can a Patent Be Granted for an AI-Generated Invention?
Abstract
Three patent offices had to answer the question of whether a patent can be granted for an invention for which an Artificial Intelligence (AI) system called DABUS was named as inventor. All applications were dismissed, but for different reasons. While the European Patent Office focused on formal rules, the UK Intellectual Property Office considered more substantive aspects, and the US Patent and Trademark Office relied on statutory language. From a policy perspective, the decisions find support in the fact that there is no clear consensus for AI to be recognized as an inventor, and that difficult questions would ensue if this were accepted. From a doctrinal perspective, the decisions do not rule out the patentability of AI-assisted inventions in general, as it remains possible to designate a human inventor when AI has merely facilitated the inventive process. This leaves the question of who should own a patent for an AI-generated invention, if patentability for such inventions is considered desirable. A possible solution could be to grant ownership directly to the company operating or owning the AI.
Overview
Integrity signals
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Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“A similar conclusion can be drawn regarding the patent protection of inventive outcomes generated with the support of an LLM [59].”
From Generative AI in EU law: Liability, privacy, intellectual property, and cybersecurity (2024) · cites this paper as [59]
Citations
Cited by
Generative AI in EU law: Liability, privacy, intellectual property, and cybersecurity
Novelli, C., Casolari, F., Hacker, P., Spedicato, G., & Floridi, L. (2024) · Computer Law & Security Review · doi:10.1016/j.clsr.2024.106066 · Cited by 124
Generative Ai in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity
Novelli, C., Casolari, F., Hacker, P., Spedicato, G., & Floridi, L. (2024) · doi:10.2139/ssrn.4821952 · Cited by 57
Metadata
- Authors
- Engel, A.
- Affiliations
- Dr iur (Hamburg), LL.M. (Yale), Lecturer (Akademischer Rat), Institute for Legal Informatics, Chair of Prof Dr Christian Heinze, LL.M. (Cambridge), Leibniz University Hannover
- Venue
- GRUR International
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-09-15
- Volume
- 69
- Issue
- 11
- Pages
- 1123-1129
- ISSN
- 2632-8623
- 2632-8550
- Cited by
- 11
- References
- 0
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Can a Patent Be Granted for an AI-Generated Invention? https://app.cochat.ai/papers/10.1093/grurint/ikaa117
- The paper
- Engel, A. (2020). Can a Patent Be Granted for an AI-Generated Invention? GRUR International. https://doi.org/10.1093/grurint/ikaa117
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.