Modeling needs user modeling

Frontiers in Artificial Intelligence

Artificial Intelligence

Mustafa Mert Çelikok¹  Pierre-Alexandre Murena¹  Samuel Kaski² 

[1] Department of Computer Science, Aalto University, Espoo, Finland;Department of Computer Science, Aalto University, Espoo, Finland;Department of Computer Science, University of Manchester, Manchester, United Kingdom;

关键词: user modeling;    probabilistic modeling;    machine learning;    human–AI collaboration;    AI assistance;    human-centric artificial intelligence;    human–AI interaction;   

DOI  :  10.3389/frai.2023.1097891

 received in 2022-11-14, accepted in 2023-03-24,  发布年份 2023

来源: Frontiers

【 摘 要 】

Modeling has actively tried to take the human out of the loop, originally for objectivity and recently also for automation. We argue that an unnecessary side effect has been that modeling workflows and machine learning pipelines have become restricted to only well-specified problems. Putting the humans back into the models would enable modeling a broader set of problems, through iterative modeling processes in which AI can offer collaborative assistance. However, this requires advances in how we scope our modeling problems, and in the user models. In this perspective article, we characterize the required user models and the challenges ahead for realizing this vision, which would enable new interactive modeling workflows, and human-centric or human-compatible machine learning pipelines.

【 授权许可】

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Copyright © 2023 Çelikok, Murena and Kaski.