Neural Language Models as What If? -Engines for HCI Research

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Collecting data is one of the bottlenecks of Human-Computer Interaction (HCI) and user experience (UX) research. In this poster paper, we explore and critically evaluate the potential of large-scale neural language models like GPT-3 in generating synthetic research data such as participant responses to interview questions. We observe that in the best case, GPT-3 can create plausible reflections of video game experiences and emotions, and adapt its responses to given demographic information. Compared to real participants, such synthetic data can be obtained faster and at a lower cost. On the other hand, the quality of generated data has high variance, and future work is needed to rigorously quantify the human-likeness, limitations, and biases of the models in the HCI domain.

Original languageEnglish
Title of host publication27th International Conference on Intelligent User Interfaces, IUI 2022 Companion
Number of pages4
ISBN (Electronic)9781450391450
Publication statusPublished - 22 Mar 2022
MoE publication typeA4 Conference publication
EventInternational Conference on Intelligent User Interfaces - Virtual, Online, Finland
Duration: 22 Mar 202225 Mar 2022
Conference number: 27

Publication series

NameInternational Conference on Intelligent User Interfaces


ConferenceInternational Conference on Intelligent User Interfaces
Abbreviated titleIUI
CityVirtual, Online


  • GPT-3
  • Language models
  • User experience
  • User models


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