Daniel White is a senior researcher in anthropology at the Graduate School of East Asian Studies, Free University of Berlin. He conducts research at the intersections of the human and hard scientists, analyzing the cross-cultural dynamics of emotion modeling in AI, social robots, and other affective technologies. He is currently working with collaborators in Japan on a long-term ethnographic project titled Model Emotions, integrating research on anthropology, AI, and affective wellbeing. His publications and podcasts can be found in Anthropology News, Sapiens, and NatureCulture.
The applications of AI across industries and public sector are mostly based on the category of algorithms known as deep learning, and how deep-learning algorithms find patterns in data. The simple narrative is the data we feed it is biased and subsequently we have to be careful in applying AI to real life scenarios. The way we frame problems and manage the data becomes crucial and if we add adaptability, localization and social context things become even harder. This expert panel composed of national and international public sector officials, academia and industry researchers will discuss what is the best way, if any, to address this problem and how to move in the right direction.
1-5-1 Marunouchi, Chiyoda-ku, Tokyo
Shin-Marunouchi Building, Room 902
April 24, 2019 at 11:00AM - 11:50AM