Responsible AI draws on widely different scientific disciplines, from the technical aspects of AI, via ethics, philosophy and law, to the individual realities of different application domains. With this hybrid-format seminar series, we wish to take advantage of the limitations imposed by Covid-19 to start an informal conversation about different aspects of Responsible AI across Denmark and abroad.

Please join us for exciting, important, and truly interdisciplinary conversations!

Organizers: Eike Petersen, Aasa Feragen, Melanie Ganz and Sune Hannibal Holm from the DFF-funded project Bias and Fairness in Medicine.

The seminar can always be attended at this fixed zoom link.

If you want to receive information about upcoming seminars, please sign up for our newsletter (at the bottom of this page)!

Coming talks

Stay tuned and sign up for our newsletter below. More seminars are coming soon!

Previous talks

Wojciech Samek (TU Berlin, Fraunhofer HHI): From Attribution Maps to Concept-Level Explainable AI. June 24, 2022. [Video]
Ben Glocker (Imperial College London, Kheiron Medical Technologies): Algorithmic encoding of protected characteristics. March 30, 2022. [Video]
Laure Wynants (Maastricht University): A journey through the disorderly world of diagnostic and prognostic models for covid-19: a living systematic review. March 2, 2022. [Video]
Timothy Miller (University of Melbourne): Explainable artificial intelligence: beware the inmates running the asylum. Or: How I learnt to stop worrying and love the social and behavioural sciences. February 9, 2022. [Video]
Enzo Ferrante (CONICET): Gender bias in X-ray classifiers for computer-assisted diagnosis. November 5, 2021. [Video]
Julia Amann (ETH): Reconciling medical AI & patient-centered care. October 1, 2021. [Video]
Anders Eklund (Linköping University): Sharing synthetic medical images — a way to circumvent GDPR? September 17, 2021. [Video]
Jens Chistian Krarup Bjerring, (AU): Black-box decision making in medicine: some thoughts and questions. June 18, 2021. [Video]
Veronika Cheplygina (ITU): How I failed machine learning in medical imaging — shortcomings and recommendations. May 28, 2021. [Slides] [Video]
Lars Kai Hansen (DTU): Values in AI. May 7, 2021. [Slides] [Video]

All previous talks can be found in our Youtube playlist.


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