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Examining Autocompletion as a Basic Concept for Interaction with Generative AI

Florian Lehmann

Florian Lehmann is a doctoral researcher focusing on research combining Human-Computer Interaction (HCI) and Artificial Intelligence (AI). He is working in a junior research group led by Daniel Buschek at the University of Bayreuth, Germany. He received his master’s degree in Human-Computer Interaction from LMU Munich. He has also a background in interactive media and electronics. In his research, he investigates the interaction between humans and intelligent systems such as computational generative systems. Bibliography e. g. see Google Scholar: https://scholar.google.com/citations?user=akHOQhoAAAAJ&sortby=pubdate

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and Daniel Buschek

Daniel Buschek leads a junior research group at the intersection of Human-Computer Interaction and Machine Learning / Artificial Intelligence at the University of Bayreuth, Germany. Previously, he worked at the Media Informatics group at LMU Munich, where he had also completed his doctoral studies, including research stays at the University of Glasgow and Aalto University, Helsinki. In his research, he combines HCI and AI to create novel user interfaces that enable people to use digital technology in more effective, efficient, expressive, explainable, and secure ways. In short, he is interested in both “AI for better UIs” and “better UIs for AI”. Bibliography e. g. see Google Scholar: https://scholar.google.de/citations?user=TsVkUBwAAAAJ

From the journal i-com

Abstract

Autocompletion is an approach that extends and continues partial user input. We propose to interpret autocompletion as a basic interaction concept in human-AI interaction. We first describe the concept of autocompletion and dissect its user interface and interaction elements, using the well-established textual autocompletion in search engines as an example. We then highlight how these elements reoccur in other application domains, such as code completion, GUI sketching, and layouting. This comparison and transfer highlights an inherent role of such intelligent systems to extend and complete user input, in particular useful for designing interactions with and for generative AI. We reflect on and discuss our conceptual analysis of autocompletion to provide inspiration and a conceptual lens on current challenges in designing for human-AI interaction.

Funding statement: This project is funded by the Bavarian State Ministry of Science and the Arts and coordinated by the Bavarian Research Institute for Digital Transformation (bidt).

About the authors

Florian Lehmann

Florian Lehmann is a doctoral researcher focusing on research combining Human-Computer Interaction (HCI) and Artificial Intelligence (AI). He is working in a junior research group led by Daniel Buschek at the University of Bayreuth, Germany. He received his master’s degree in Human-Computer Interaction from LMU Munich. He has also a background in interactive media and electronics. In his research, he investigates the interaction between humans and intelligent systems such as computational generative systems. Bibliography e. g. see Google Scholar: https://scholar.google.com/citations?user=akHOQhoAAAAJ&sortby=pubdate

Daniel Buschek

Daniel Buschek leads a junior research group at the intersection of Human-Computer Interaction and Machine Learning / Artificial Intelligence at the University of Bayreuth, Germany. Previously, he worked at the Media Informatics group at LMU Munich, where he had also completed his doctoral studies, including research stays at the University of Glasgow and Aalto University, Helsinki. In his research, he combines HCI and AI to create novel user interfaces that enable people to use digital technology in more effective, efficient, expressive, explainable, and secure ways. In short, he is interested in both “AI for better UIs” and “better UIs for AI”. Bibliography e. g. see Google Scholar: https://scholar.google.de/citations?user=TsVkUBwAAAAJ

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Published Online: 2021-01-15
Published in Print: 2021-01-26

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