Problem Solving Through Human-AI Preference-Based Cooperation

Subhabrata Dutta; Timo Kaufmann; Goran Glavaš; Ivan Habernal; Kristian Kersting; Frauke Kreuter; Mira Mezini; Iryna Gurevych; Eyke Hüllermeier; Hinrich Schuetze

arXiv · 2408.07461

Problem Solving Through Human-AI Preference-Based Cooperation

Subhabrata Dutta·Timo Kaufmann·Goran Glavaš·Ivan Habernal·Kristian Kersting·Frauke Kreuter·Mira Mezini·Iryna Gurevych·Eyke Hüllermeier·Hinrich Schuetze

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Abstract

While there is a widespread belief that artificial general intelligence (AGI) -- or even superhuman AI -- is imminent, complex problems in expert domains are far from being solved. We argue that such problems require human-AI cooperation and that the current state of the art in generative AI is unable to play the role of a reliable partner due to a multitude of shortcomings, including difficulty to keep track of a complex solution artifact (e.g., a software program), limited support for versatile human preference expression and lack of adapting to human preference in an interactive setting. To address these challenges, we propose HAICo2, a novel human-AI co-construction framework. We take first steps towards a formalization of HAICo2 and discuss the difficult open research problems that it faces.

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Subhabrata Dutta, Timo Kaufmann, Goran Glavaš, Ivan Habernal, Kristian Kersting, Frauke Kreuter, Mira Mezini, Iryna Gurevych, Eyke Hüllermeier, Hinrich Schuetze. 2024-08-14. Problem Solving Through Human-AI Preference-Based Cooperation. https://arxiv.org/abs/2408.07461

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