Understanding Mental Models of AI through Player-AI Interaction

Jichen Zhu; Jennifer  Villareale

Understanding Mental Models of AI through Player-AI Interaction

Jichen Zhu, Jennifer Villareale

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

Abstrakt

Designing human-centered AI-driven applications require deep understandings of how people develop mental models of AI. Currently, we have little knowledge of this process and limited tools to study it. This paper presents the position that AI-based games, particularly the player-AI interaction component, offer an ideal domain to study the process in which mental models evolve. We present a case study to illustrate the beneﬁts of our approach for explainable AI.

Originalsprog	Engelsk
Titel	Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (CHI EA '21)
Publikationsdato	2021
Artikelnummer	11
Status	Udgivet - 2021

Adgang til dokumentet

2103.16168(3)

Citationsformater

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title = "Understanding Mental Models of AI through Player-AI Interaction",

abstract = "Designing human-centered AI-driven applications require deep understandings of how people develop mental models of AI. Currently, we have little knowledge of this process and limited tools to study it. This paper presents the position that AI-based games, particularly the player-AI interaction component, offer an ideal domain to study the process in which mental models evolve. We present a case study to illustrate the beneﬁts of our approach for explainable AI.",

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booktitle = "Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (CHI EA '21)",

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AU - Zhu, Jichen

AU - Villareale, Jennifer

PY - 2021

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AB - Designing human-centered AI-driven applications require deep understandings of how people develop mental models of AI. Currently, we have little knowledge of this process and limited tools to study it. This paper presents the position that AI-based games, particularly the player-AI interaction component, offer an ideal domain to study the process in which mental models evolve. We present a case study to illustrate the beneﬁts of our approach for explainable AI.

M3 - Article in proceedings

BT - Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (CHI EA '21)

ER -