Addressing Intellectual Property Relevant Similarities In Images Through Algorithmic Decision-Making
The project aims at defining whether and how algorithmic technologies could be used to help in assessing intellectual property (IP) relevant similarities, with a focus on images. Such algorithmic decision-making tools are currently being developed and used by private entities for the purposes of IP enforcement (monitoring infringing goods online, filtering out content) and registration by IP Offices. In order to limit biases, the development of such tools would ideally be undertaken under the supervision of independent experts. Therefore, the objectives of the project are twofold. First, it will address the methodological, technical, legal and ethical challenges of building such tools in order to provide with a critical study of available ones. Second, it will aim at proposing an open source and transparent model that is compliant with the settled case law on IP relevant similarities in relation to images and that safeguards “by design” related fundamental rights.
- CABAY Julien, JurisLab (Centre de droit privé, FabLab ULB)
- DEBEIR Olivier
- Thomas VANDAMME
- ARC – Projets consolidation (2020-2023)