Par : Baptiste Caramiaux
Résumé :
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.
Bio :
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, engineering.
Jeudi 3 novembre, 10 h 30.
Lien zoom : https://uqam.zoom.us/j/88481835073
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