UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Designing for Continuous Interaction with Artificial Intelligence Systems

Wintersberger, P; Van Berkel, N; Fereydooni, N; Tag, B; Glassman, EL; Buschek, D; Blandford, A; (2022) Designing for Continuous Interaction with Artificial Intelligence Systems. In: Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery (ACM): New Orleans, LA, USA. Green open access

[thumbnail of chi22extendedabstracts-170.pdf]
Preview
Text
chi22extendedabstracts-170.pdf - Accepted Version

Download (405kB) | Preview

Abstract

The increasing capabilities of Artificial Intelligence enable the support of users in a continuously growing number of applications. Current systems typically dictate that interaction between user input and AI output unfolds in discrete steps, as is the case with, for example, conversational agents. Novel scenarios require AI systems to adapt and respond to continuous user input, e.g., image-guided surgery and AI-supported text entry. In and across these applications, AI systems need to support more varied and dynamic interactions in which users and AI interact continuously and in parallel. Current methods and guidelines are often inadequate and sometimes even detrimental to user needs when considering continuous usage scenarios. Realizing a continuous interaction between users and AI requires a substantial change in perspective when designing Human-AI systems. In this SIG, we support the exchange of cutting-edge research contributing to a better understanding and improved methods and tools to design continuous Human-AI interaction.

Type: Proceedings paper
Title: Designing for Continuous Interaction with Artificial Intelligence Systems
Event: CHI EA '22: CHI Conference on Human Factors in Computing Systems
ISBN-13: 9781450391566
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3491101.3516409
Publisher version: https://doi.org/10.1145/3491101.3516409
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Human-AI interaction, design guidelines, continuous interaction, AI, ML, explainability
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10149321
Downloads since deposit
158Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item