Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

7-2023

Abstract

Human-Computer Interaction has been evolving rapidly with the advancement of artificial intelligence and metaverse. Human-AI Interaction is a new area in Human-Computer Interaction. In this paper, we look at AI avatars, which are human-like representations of AI systems. AI avatars closely resemble real persons. AI avatars have several advantages, including enhanced trustworthiness and increased AI system adoption. AI avatars also enable human-like interaction and engagement. AI avatars have their share of issues, such as the potential for psychological impact, discrimination, and biases. The paper discusses the benefits and pitfalls of AI avatars and proposes several research directions. This research paper has theoretical and practical significance. AI avatars are a new phenomenon. Existing theories, such as those in psychology, social psychology, and communication, may not hold when applied to AI avatars. AI avatars also present new features and characteristics, such as ease of customization and personalization, that are not easily found in humans. Such features and characteristics can be capitalized to enhance Human-AI Interaction, but their negative aspects will need to be understood and managed. For practitioners and AI developers, this pioneering research provides new insight, understanding, and possibilities of AI avatars that can be used to further enhance Human-AI Interaction.

Keywords

Human-AI Interaction, Human-Computer Interaction, Artificial Intelligence, AI Avatars, Metaverse

Discipline

Artificial Intelligence and Robotics | Databases and Information Systems

Research Areas

Information Systems and Management

Areas of Excellence

Digital transformation

Publication

Proceedings of the 25th International Conference on Human-Computer Interaction, HCII 2023, Copenhagen, Denmark, July 23-28

First Page

120

Last Page

130

Identifier

10.1007/978-3-031-48057-7_8

Publisher

Springer

City or Country

Cham

Additional URL

https://doi.org/10.1007/978-3-031-48057-7_8

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