Open Science in the Age of AI: Copyright, Bias, and Access to Knowledge

Open Science in the Age of AI: Copyright, Bias, and Access to Knowledge | Zenodo Skip to main Communities My dashboard Log in Sign up Zenodo is currently experiencing slowness and intermittent outages due to heavy automated traffic from bots and AI crawlers. We are aware of the problem, and our team is focused on stabilizing the service. Thank you for your patience. KU Leuven Open Science Day Published May 8, 2026 | Version v1 Presentation Open Open Science in the Age of AI: Copyright, Bias, and Access to Knowledge Authors/Creators King, Leona 1 Portante D'Alessandro, Francesca 1 Show affiliations 1. KU Leuven Description The open science movement emerged in response to long-standing concerns about access to knowledge, the enclosure of publicly funded research, and the distributive effects of copyright and academic publishing practices. Its core objective has been to ensure that scientific knowledge functions as a shared resource : accessible, reusable, and open to scrutiny. In the age of AI, however, these foundational assumptions are increasingly being tested. AI systems rely on large-scale training on scientific texts and data, raising new questions about how copyright law structures access to knowledge and redistributes control over its downstream uses. This presentation argues that copyright law plays a central yet under-examined role in shaping the epistemic foundations of AI systems, including the reproduction of gendered and racialised bias. By limiting lawful access to scientific works and datasets, copyright law incentivises AI developers to rely on legally low-risk and easily accessible materials, which are often older, less diverse, and less representative. These dynamics risk reinforcing existing epistemic and social inequalities through AI systems and their outputs. At the same time, much high-quality research remains locked behind paywalls as a result of copyright assignment and licensing practices in academic publishing. Recent licensing agreements between academic publishers and AI developers further intensify concerns about the enclosure of scientific knowledge and the displacement of decision-making away from researchers and the public. Against this background, the presentation advances a research agenda for open science in the age of AI. It asks whether existing open science tools such as open access publishing, open data practices, Creative Commons licensing, and text-and-data-mining exceptions remain fit for purpose when scientific knowledge becomes a primary input for AI development. It further explores whether and how open science must be reimagined not only as a framework for access and reuse, but also as a means of addressing structural bias, accountability, and fairness in AI systems. The presentation concludes by questioning whether AI systems built on genuinely open scientific resources can contribute to the democratisation of access to knowledge, or whether, absent a recalibration of copyright law and open science practices, they risk entrenching new forms of epistemic enclosure. Files Files (12.5 MB) Name Size Download all KUL Open Science.pptx md5:918caa9c4fe041344bf9008078c7cb5e 12.5 MB Download Additional details Dates Available 2026-06-05 118 Views 57 Downloads Show more details All versions This version Views Total views 118 118 Downloads Total downloads 57 57 Data volume Total data volume 738.2 MB 738.2 MB More info on how stats are collected.... Versions External resources Indexed in OpenAIRE Communities Details DOI DOI Badge DOI 10.5281/zenodo.20080023 Markdown [](https://doi.org/10.5281/zenodo.20080023) reStructuredText .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.20080023.svg :target: https://doi.org/10.5281/zenodo.20080023 HTML <a href="https://doi.org/10.5281/zenodo.20080023"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.20080023.svg" alt="DOI"></a> Image URL https://zenodo.org/badge/DOI/10.5281/zenodo.20080023.svg Target URL https://doi.org/10.5281/zenodo.20080023 Resource type Presentation Publisher Zenodo Conference KU Leuven Open Science Day 2026 , Leuven, 6 May 2026 Rights License Creative Commons Attribution 4.0 International The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited. Read more Citation Export Technical metadata Created May 8, 2026 Modified May 8, 2026 Jump up About About Policies Infrastructure Principles Projects Roadmap Contact Blog Blog Support Help FAQ Developers REST API OAI-PMH Contribute GitHub Donate Funded by Powered by CERN Data Centre & InvenioRDM Status Privacy policy Cookie policy Terms of Use This site uses cookies. Find out more on how we use cookies Accept all cookies Accept only essential cookies

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