“An EU copyright & data legislative framework fit for research: barriers, challenges and potential measures to address them”
A workshop on proposing a research-appropriate EU legislative and regulatory framework on copyright and data was organised in Brussels on February 23 and 24, 2023 in the scope of Action 2 of the European Research Area (ERA). Dr Maja Bogataj Jančič attended the workshop as the Slovenian representative for Action 2 in the ERA group. She presented the Slovenian data and text mining exemption, which is among the most advanced in Europe, and pointed out the many copyright obstacles in Slovenian legislation.
The workshop focused on the implementation of the priority actions under the new policy agenda for the European Research Area 2022-2024 and part of the June 2022 Council conclusions on the implementation of open science.
The priority action aims to:
– identify barriers and challenges to access to and re-use of publicly funded research and innovation results, publications and data for scientific purposes and identify potential impacts on research, by analysing relevant provisions under EU copyright and data legislation and related regulatory frameworks, as well as relevant institutional and national initiatives; and
– propose legislative and non-legislative measures to improve the current EU legislative and regulatory frameworks in the area of copyright and data.
ODIPI is addressing the topic of data and text mining in more detail in the framework of the Knowledge Rights 21 research network.
ODIPI is organizing ERA KR21 Conference: Barriers and Incentives for Open Science in the Copyright Law that will take place on 2 December, 2024 at Hotel Four Points by Sheraton (Mons) in Ljubljana and also online.
The District Court of Hamburg ruled in the case of Kneschke v. LAION e.V. that LAION did not infringe the copyright of photographer Kneschke, as the use of his photograph was covered by the exception for text and data mining (TDM) for scientific purposes.
“Can copyright bring artificial intelligence to its knees? Which other circumstances may cause that the “making” of generative AI can dramatically change in the (near) future. This short paper presents potential challenges that copyright poses to the training of the machines on large amount of data. Different jurisdictions address these issues differently. In the USA the legality of these activities is tested in several court cases. Do gentlemen’s agreements and pragmatic symbiosis known from the “search engines business model” provide sufficient basis and/or incentive for the business model of “making” generative AI business model as well?