Grand Challenges for Personal Informatics and AI

Mamykina, Lena and A. Epstein, Daniel and Klasnja, Predrag and Sprujt-Metz, Donna and Meyer, Jochen and Czerwinski, Mary and Althoff, Tim and Choe, Eun Kyoung and De Choudhury, Munmun and Lim, Brian
CHI Conference on Human Factors in Computing Systems Extended Abstracts
Increasing availability of personal data opened new possibilities for technologies that support individuals' reflection, increase their self-awareness, and inform their future choices. Personal informatics, chiefly concerned with investigating individuals' engagement with personal data, has become an area of active research within Human-Computer Interaction. However, more recent research has argued that personal informatics solutions often place high demands on individuals and require knowledge, skills, and time for engaging with personal data. New advances in Machine Learning (ML) and Artificial Intelligence (AI) can help to reduce the cognitive burden of personal informatics and identify meaningful trends using analytical engines. Furthermore, introducing ML and AI can enable systems that provide more direct support for action, for example through predictions and recommendations. However, there are many open questions as to the design of personal informatics technologies that incorporate ML and AI. In this workshop, we will bring together an interdisciplinary group of researchers in personal informatics, ML, and AI to outline the design space for intelligent personal informatics solutions and develop an agenda for future research in this area.
Association for Computing Machinery
CHI EA '22