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eXtended Artificial Intelligence: New Prospects of Human-AI Interaction Research

Please always quote using this URN: urn:nbn:de:bvb:20-opus-260296
  • Artificial Intelligence (AI) covers a broad spectrum of computational problems and use cases. Many of those implicate profound and sometimes intricate questions of how humans interact or should interact with AIs. Moreover, many users or future users do have abstract ideas of what AI is, significantly depending on the specific embodiment of AI applications. Human-centered-design approaches would suggest evaluating the impact of different embodiments on human perception of and interaction with AI. An approach that is difficult to realize due toArtificial Intelligence (AI) covers a broad spectrum of computational problems and use cases. Many of those implicate profound and sometimes intricate questions of how humans interact or should interact with AIs. Moreover, many users or future users do have abstract ideas of what AI is, significantly depending on the specific embodiment of AI applications. Human-centered-design approaches would suggest evaluating the impact of different embodiments on human perception of and interaction with AI. An approach that is difficult to realize due to the sheer complexity of application fields and embodiments in reality. However, here XR opens new possibilities to research human-AI interactions. The article’s contribution is twofold: First, it provides a theoretical treatment and model of human-AI interaction based on an XR-AI continuum as a framework for and a perspective of different approaches of XR-AI combinations. It motivates XR-AI combinations as a method to learn about the effects of prospective human-AI interfaces and shows why the combination of XR and AI fruitfully contributes to a valid and systematic investigation of human-AI interactions and interfaces. Second, the article provides two exemplary experiments investigating the aforementioned approach for two distinct AI-systems. The first experiment reveals an interesting gender effect in human-robot interaction, while the second experiment reveals an Eliza effect of a recommender system. Here the article introduces two paradigmatic implementations of the proposed XR testbed for human-AI interactions and interfaces and shows how a valid and systematic investigation can be conducted. In sum, the article opens new perspectives on how XR benefits human-centered AI design and development.show moreshow less

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Metadaten
Author: Carolin Wienrich, Marc Erich Latoschik
URN:urn:nbn:de:bvb:20-opus-260296
Document Type:Journal article
Faculties:Fakultät für Mathematik und Informatik / Institut für Informatik
Fakultät für Humanwissenschaften (Philos., Psycho., Erziehungs- u. Gesell.-Wissensch.) / Institut Mensch - Computer - Medien
Language:English
Parent Title (English):Frontiers in Virtual Reality
Year of Completion:2021
Volume:2
Article Number:686783
Source:Frontiers in Virtual Reality (2021) 7:686783. https://doi.org/10.3389/frvir.2021.686783
DOI:https://doi.org/10.3389/frvir.2021.686783
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Tag:XR-artificial intelligence combination; XR-artificial intelligence continuum; human-artificial intelligence interaction; human-artificial intelligence interface; human-centered, human-robot; recommender system; research methods
Release Date:2022/03/29
Collections:Open-Access-Publikationsfonds / Förderzeitraum 2021
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International