Get coffee, chat convivial tools, and hang out with folks in human-centered computing. This month, special guest Ivan Reese is joining us! (Location is outdoors, near transit and multiple coffee shop...

Check out our special issue on the topic!

Learn how AI agents automate tasks like code generation, testing and documentation, but still require oversight for complex decision-making.

Welcome to the First Interdisciplinary Workshop on Human-Computer Narrative Interactions (HCNI) at CHI PLAY 2025! We’ll engage in hands-on exploration of player-game interactivity for impactful digita...

This paper contends with the notion that the methods of machine learning (ML) are unique among the tools of science in enabling a form of theory-free inductive inference. I challenge these assertions of epistemic distinctness, attributing the prevalence of these views to an untenable conception of scientific objectivity: what I term a theory-free ideal, in homage to its normative counterpart. ML, as a formal method of induction, must rely on conceptual or theoretical resources to get inference off the ground. By means of two case studies, I argue that this theory-free ideal has a deleterious effect on the epistemic standing of ML-involving science.

I have been attending the ACM Hypertext 2025 conference in Chicago, part of which was the Narrative and Hypertext workshop which I run with Charlie Hargood from Bournemouth University. This year we…

This year, we interfaced successfully with one member of the general public. Here's how it went