NAVER LABS Europe seminars are open to the public. This seminar is virtual and requires registration
Rethinking interaction with machine learning
About the speaker: Baptiste Caramiaux is a CNRS researcher at ISIR, Sorbonne Université in Paris, in the HCI Sorbonne group. He conducts research in human-computer interaction (HCI), studying and designing interactions with machine learning algorithms in the context of performing arts, health and pedagogy. He received a PhD in Computer Music from University Pierre et Marie Curie and IRCAM in 2012. He has worked at Goldsmiths College, University of London and McGill University, as a Marie Skłodowska-Curie Research Fellow. He joined CNRS (CR1) in 2018 at LRI (now LISN), Université Paris-Saclay. Since 2015, he has been a senior researcher then consultant at Mogees ltd and an associate member of the Fronte Vaccuo artistic collective.
Abstract: Machine learning algorithms are present in many of the applications and services we use every day. These technologies are often designed in isolation from their users, leading to a standardisation of their uses and a centralised control of their capabilities. Creating learning technologies that are closer to people and their context of use opens up the possibility of more responsive, appropriable and inclusive interactions. In this talk, I will present the context and the research community working on these themes at the intersection between HCI and AI. Then I will focus on my work in this field. I will show examples of research where the artistic approach is sometimes seen as a tool to reflect on technologies as cultural actors, and sometimes seen as a tool to inspire the design of rich and expressive interactions. Finally, I will present concrete ways to design interactions with machine learning algorithms through the concept of Machine Teaching.