Designing how people — and groups — decide with the help of intelligent systems.
Three decades of human–computer interaction research on user modeling, recommender systems and choice architecture — now applied to building practical tools for the way teams decide.
A path from the research lab to building products — with a consistent question underneath: how do systems fit the way people actually think and decide?
The company I founded to turn research on decision support and human-centred AI into practical tools that help teams weigh options and decide well together.
German Research Center for Artificial Intelligence. Directed research on interactive intelligent systems, user modeling and decision support — bridging empirical study and applied projects with industry.
Teaching and research in human–computer interaction and user-centred design.
Five threads, one through-line: helping people make good decisions when an intelligent system is part of the loop.
How the presentation of options shapes decisions — the bridge between behavioural science and interaction design.
Recommending to several people at once, balancing preferences, fairness and the social dynamics of deciding together.
Empirically grounded, often Bayesian models of what a user knows, wants and can attend to — learned from real data.
Adapting to a user's momentary limits of time and working memory, instead of assuming an idealised user.
Making intelligent systems legible and controllable, so their adaptivity helps the user rather than surprising them.
A small sample from ~67 publications spanning 1973–2017. Filter by theme.
Anthony Jameson is a researcher and entrepreneur working at the meeting point of artificial intelligence and human decision-making. Over three decades he helped shape the fields of user modeling, recommender systems and intelligent user interfaces — with a particular interest in how systems can support people as they weigh options and decide, both alone and in groups.
That work moved deliberately between theory and practice: empirical studies of how people reason under real constraints, formal models that capture those patterns, and applied projects that put them to use. Today he leads Contaction AG, translating the same ideas into practical tools for working with generative AI.