User Modeling in Human-Centered AI
Files
Publication date
2025-03-29
Authors
Herder, Eelco
Masthoff, Judith
Editors
Germanakos, Panagiotis
Juhasz, Monika
Kongot, Aparna
Marathe, Devashree
Sacharidis, Dimitris
Advisors
Supervisors
Document Type
Part of book
Metadata
Show full item recordCollections
License
taverne
Abstract
Artificial intelligence is the discipline that pursues the understanding, artificial replication and possible enhancement of human intelligence. Among others, AI-based recommender systems, persuasive systems as well as decision support systems are used for making decisions that have direct impact on people’s lives. In AI-supported decision making, the initiative may lie on the user’s side (such as recommender systems), or be largely automated (such as navigation systems or automotive driving). Many organizations also employ AI systems to make decisions that concern their users, customers, or citizens. But how do these systems learn about the people involved, how are these people represented, and—most importantly—how complete, realistic, reliable and fair is this representation? In this chapter, we discuss various considerations for user modeling in human-centered AI.
Keywords
Adaptive systems, Choice architecture, Conversational systems, Decision making, Decision support, Human-in-the-loop, Personalized systems, Persuasive systems, Recommender systems, Relevance feedback, User intentions, User interests, User modelling, Taverne, Human-Computer Interaction
Citation
Herder, E & Masthoff, J 2025, User Modeling in Human-Centered AI. in P Germanakos, M Juhasz, A Kongot, D Marathe & D Sacharidis (eds), Human-Centered AI : An Illustrated Scientific Quest. Human - Computer Interaction Series, vol. Part F9477, Springer, pp. 475-491. https://doi.org/10.1007/978-3-031-61375-3_6