This workshop aims to spearhead research on Human-Interpretable Artificial Intelligence (HI-AI) by providing: (i) a general overview of the key aspects of HI-AI, in order to equip all researchers with the necessary background and set of definitions; (ii) novel and interesting ideas coming from both invited talks and top paper contributions; (iii) the chance to engage in dialogue with prominent scientists during poster presentations and coffee breaks. The workshop welcomes contributions covering novel interpretable-by-design or post-hoc approaches, as well as theoretical analysis of existing works. Additionally, we accept visionary contributions speculating on the future potential of this field. Finally, we welcome contributions from related fields such as Ethical AI, Knowledge-driven Machine learning, Human-machine Interaction, but also applications in Medicine and Industry, and analyses from Regulatory experts.

Workshop on Human-Interpretable AI / Ciravegna, Gabriele; Espinosa Zarlenga, Mateo; Barbiero, Pietro; Giannini, Francesco; Shams, Zohreh; Garreau, Damien; Jamnik, Mateja; Cerquitelli, Tania. - (2024), pp. 6708-6709. (Intervento presentato al convegno 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining tenutosi a Barcelona (ESP) nel August 25 - 29, 2024) [10.1145/3637528.3671499].

Workshop on Human-Interpretable AI

Gabriele Ciravegna;Tania Cerquitelli
2024

Abstract

This workshop aims to spearhead research on Human-Interpretable Artificial Intelligence (HI-AI) by providing: (i) a general overview of the key aspects of HI-AI, in order to equip all researchers with the necessary background and set of definitions; (ii) novel and interesting ideas coming from both invited talks and top paper contributions; (iii) the chance to engage in dialogue with prominent scientists during poster presentations and coffee breaks. The workshop welcomes contributions covering novel interpretable-by-design or post-hoc approaches, as well as theoretical analysis of existing works. Additionally, we accept visionary contributions speculating on the future potential of this field. Finally, we welcome contributions from related fields such as Ethical AI, Knowledge-driven Machine learning, Human-machine Interaction, but also applications in Medicine and Industry, and analyses from Regulatory experts.
2024
979-8-4007-0490-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2993085