Keynote Speakers

Abstract
The European Commission has described a vision for Trustworthy Artificial Intelligence (AI), outlining seven requirements that AI systems must meet. While some are of a primarily technical nature (e.g., “Robustness and Safety”), others – such as “Diversity, Non-discrimination, and Fairness” or “Transparency” – require transdisciplinary solutions. A key barrier to realizing Trustworthy AI is that we do not (yet) have an AI-literate public. In this talk, I focus on Diversity, Non-discrimination, and Fairness, as a large volume of research has emerged on the mitigation of social bias in AI. Many approaches define a range of acceptable behaviors for an AI system, as to manage those deemed problematic and/or unfair. I discuss the challenges that Generative AI poses for such approaches. How can we define what are fair behaviors, when these systems produce previously unseen content and data, which are often unexpected? Finally, I share our team’s efforts to educate non-technical audiences on concepts surrounding AI and Big Data, with the goal of engaging members of the public in defining the social norms for AI systems.

Bio
Dr. Jahna Otterbacher received her doctorate from the University of Michigan (Ann Arbor, USA). She is Associate Professor and Vice Dean of the School of Pure and Applied Sciences at the Open University of Cyprus (OUC). At OUC, she leads the Cyprus Center for Algorithmic Transparency (CyCAT), which conducts interdisciplinary research focused on promoting technical and educational solutions for promoting algorithmic transparency and literacy. Concurrent to this, Jahna co-leads the Fairness and Ethics in AI-Human Interaction (fAIre) group at CYENS, a new center of excellence and innovation in Nicosia, Cyprus, in collaboration with two international Advanced Partners, UCL and MPI. Her research has been funded by the EU’s Horizon 2020 Research and Innovation Program (under Grant Agreements No. 739578 (RISE) & No. 810105 (CyCAT)), as well as the Cyprus Research and Innovation Foundation (under grants EXCELLENCE/0918/0086 (DESCANT) and EXCELLENCE/0421/0360 (KeepA(I)n)).