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Facial recognition technology, democracy and human rights
On 4 July 2023, the Third Section of the European Court of Human Rights (ECtHR) delivered the first judgment on the compatibility of facial recognition technology with human rights in Glukhin v. Russia. The...
In a blog post published on The Digital Constitutionalist, our Research Associate Natalia Menéndez González contributes to the debate on the epistemic and ethical implications of unification in machine learning.
The paper ‘Should attention be all we need? The epistemic and ethical implications of unification in machine learning’ by Nic Fishman and Leif Hancox-Li discusses the epistemic and ethical perks and shortcomings of unification for different areas and tasks in Machine Learning (ML) under the transformers’ architecture.
Machine learning is a subfield of artificial intelligence, broadly defined as the capability of a machine to imitate intelligent human behaviour.
“As a legal scholar reading and enjoying the paper, there was one thought, one claim, that was pounding my head all over my reading and this was: how unification will affect the regulation and policymaking over ML systems? My intention here is not to run ahead of all the arguments put forward within the paper in favour of the benefits that unification might entail for regulation and policymaking. However, I think this is an important point that should be discussed and considered, and I hope this blog post can also contribute to the academic debate that the authors tried to spark within their paper.” Continue reading on The Digital Constitutionalist