Interaction Design With Multi-Objective Bayesian Optimization

Interaction design typically involves challenging decision making that requires designers to consider multiple parameters and careful tradeoffs between various objectives. This article examines how AI can facilitate the process of interaction design by offloading some of the complex decision making required of designers. We study how multi-objective Bayesian optimization can be used to support designers when creating a tactile display for smart watches. We present the results of a study that explores how such human-AI collaboration afforded by multi-objective Bayesian optimization can be exploited by designers, and the advantages and disadvantages this solution offers over conventional design practice.

Automated summary

This article examines how AI can facilitate the process of interaction design by offloading complex decision making needed by designers. It discusses the use of multi-objective Bayesian optimization to support designers in creating tactile displays for smart watches. The study presents the advantages and disadvantages of utilizing the human-AI collaboration enabled by multi-objective Bayesian optimization over conventional design practice.