Explainable AI (XAI) is concerned with how to make AI models more understandable to people. To date these explanations have predominantly been technocentric - mechanistic or productivity oriented. This paper introduces the Explainable AI for the Arts (XAIxArts) manifesto to provoke new ways of thinking about explainability and AI beyond technocentric discourses. Manifestos offer a means to communicate ideas, amplify unheard voices, and foster reflection on practice. To supports the co-creation and revision of the XAIxArts manifesto we combine a World Caf\'e style discussion format with a living manifesto to question four core themes: 1) Empowerment, Inclusion, and Fairness; 2) Valuing Artistic Practice; 3) Hacking and Glitches; and 4) Openness. Through our interactive living manifesto experience we invite participants to actively engage in shaping this XIAxArts vision within the CHI community and beyond.

This second international workshop on explainable AI for the Arts (XAIxArts) brought together a community of researchers in HCI, Interaction Design, AI, explainable AI (XAI), and digital arts to explore the role of XAI for the Arts. Workshop held at the 16th ACM Conference on Creativity and Cognition (C&C 2024), Chicago, USA.

We have participated in the Senseval-2 English tasks (all words and lexical sample) with an unsupervised system based on mutual information measured over a large corpus (277 million words) and some additional heuristics. A supervised extension of the system was also presented to the lexical sample task. Our system scored first among unsupervised systems in both tasks: 56.9% recall in all words, 40.2% in lexical sample. This is slightly worse than the first sense heuristic for all words and 3.6% better for the lexical sample, a strong indication that unsupervised Word Sense Disambiguation remains being a strong challenge.

The interdisciplinary makeup allowed for an expansion of the scope of Glymour's One notable extension was the move from android epistemology to android ethics. "they can know everything we know Margaret Boden presented her work Hayes and Ford were responding Participation was limited to 40 If the first two workshops on to the debate in Scientific American researchers selected from several disciplines human and machine cognition are (January 1990) between Searle and (principally computer science, representative, these meetings will the Churchlands about whether a philosophy, and psychology); become hotbeds of constructive and machine could think. Ironically, although this approach makes for much-needed debate. They focus on from the perspective of Hayes and stimulating discussion, it has resulted the foundational and methodological Ford, Searle and the Churchlands are in a competitive review process concerns of those who want to forge essentially in agreement, diverging (about a 10-percent acceptance rate). It is just a theories about the necessary in U.S. politics, the theme of the fact of life that there isn't much material basis (biological versus parallel) Second International Workshop on agreement about methodology and for intelligence. They both Human and Machine Cognition was, foundational issues within these two make specific implementation features What do androids know, and when fields. The positions covered One feature of the workshop that for intelligence. As might be expected, a wide range: "They can know facilitated and, at times, obstructed Paul Churchland objected to this only what androids can know: Android fruitful discussion was its highly interdisciplinary grouping.

The Second International Workshop on User Modeling was held March 30- April 1, 1990 in Honolulu, Hawaii. The general chairperson was Dr. Wolfgang Wahlster of the University of Saarbrucken; the program and local arrangements chairperson was Dr. David Chin of the University of Hawaii at Manoa. The workshop was sponsored by AAAI and the University of Hawaii, with AAAI providing eight travel stipends for students.

It 445 Burgess Drive In spite of the many strong technical was generally agreed that the formalization Menlo Park, CA 94025-3496 results that have been produced, it is of commonsense reasoning (415) 328-3123 still far from clear whether existing should be a top-level item for future approaches are sufficient to formalize research.