@article{li2022assessing,
author = {Li, Tianyi and Vorvoreanu, Mihaela and DeBellis, Derek and Amershi, Saleema},
title = {Assessing Human-AI Interaction Early through Factorial Surveys: A Study on the Guidelines for Human-AI Interaction},
year = {2022},
month = {April},
abstract = {This work contributes a research protocol for evaluating human-AI interaction in the context of specific AI products. The research protocol enables UX and HCI researchers to assess different human-AI interaction solutions and validate design decisions before investing in engineering. We present a detailed account of the research protocol and demonstrate its use by employing it to study an existing set of human-AI interaction guidelines. We used factorial surveys with a 2x2 mixed design to compare user perceptions when a guideline is applied versus violated, under conditions of optimal versus sub-optimal AI performance. The results provided both qualitative and quantitative insights into the UX impact of each guideline. These insights can support creators of user-facing AI systems in their nuanced prioritization and application of the guidelines.},
url = {http://approjects.co.za/?big=en-us/research/publication/assessing-human-ai-interaction-early-through-factorial-surveys-a-study-on-the-guidelines-for-human-ai-interaction/},
journal = {ACM Transactions on Computer-Human Interaction},
}