DTU Compute is pleased to invite all interested parties to welcome our Professor Aasa Feragen as professor in Medical Image Analysis. In her inaugural lecture Aasa will explain why it is important that technical AI professionals take part in discussions about the role of AI in society.
Aasa's inaugural lecture will take place on Friday 27 January 2023 from 15:00 to 16:00 in Building 101, Room M1, Anker Engelundsvej, 2800 Kgs. Lyngby. The lecture is followed by a reception from 16:00 to 17:00.
About Aasa's lecture: As artificial intelligence (AI) becomes increasingly integrated into our societal infrastructures, we see a steady flow of examples of unwanted AI behavior: Lack of robustness; shortcut learning and lack of generalization; or bias exemplified via blatant racism and sexism.
This has engaged a number of different stakeholders, ranging from researchers in social sciences, via activists, through politicians, in the analysis of and debate on AI's role in society. As these discussions have a dominant ethical and political nature, it is both easy and common for technical AI professionals to leave these discussions to the non-technical stakeholders.
Through this lecture, I hope to convince you - my technical colleague - that taking this stance would be a mistake.
First: By developing AI tools that are transparent about their function and limitations, we can support a more informed, and hence more useful, debate on responsible AI. A more informed debate would ideally also lead to more informed political decisions, which will impact our ability to do good with
AI in the future.
Second: By understanding the problems raised, we can develop AI technology which is more easily adapted into real-world practice - increasing the value of our own work.
Finally: This is not just the right thing to do. Responsible AI also comes with a series of exciting, open technical challenges.
Aasa Feragen holds a Master of Science degree (2005) in mathematics and a PhD degree (2010) in mathematics (topology), both from the University of Helsinki in Finland. Her scientific focus areas are geometry in machine learning and statistics; responsible machine learning and machine learning for biomedical imaging. Visit Aasa Feragen's personal
homepage at dtu.dk