Solving Separation-of-Concerns Problems in Collaborative Design of Human-AI Systems through Leaky Abstractions

要旨

In conventional software development, user experience (UX) designers and engineers collaborate through separation of concerns (SoC): designers create human interface specifications, and engineers build to those specifications. However, we argue that Human-AI systems thwart SoC because human needs must shape the design of the AI interface, the underlying AI sub-components, and training data. How do designers and engineers currently collaborate on AI and UX design? To find out, we interviewed 21 industry professionals (UX researchers, AI engineers, data scientists, and managers) across 14 organizations about their collaborative work practices and associated challenges. We find that hidden information encapsulated by SoC challenges collaboration across design and engineering concerns. Practitioners describe inventing ad-hoc representations exposing low-level design and implementation details (which we characterize as leaky abstractions) to "puncture" SoC and share information across expertise boundaries. We identify how leaky abstractions are employed to collaborate at the AI-UX boundary and formalize a process of creating and using leaky abstractions.

著者
Hariharan Subramonyam
Stanford University, Stanford, California, United States
Jane Im
University of Michigan, Ann Arbor, Michigan, United States
Colleen Seifert
U Michigan, Ann Arbor, Michigan, United States
Eytan Adar
University of Michigan, Ann Arbor, Michigan, United States
論文URL

https://dl.acm.org/doi/abs/10.1145/3491102.3517537

動画

会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)

セッション: Design Practice

290
5 件の発表
2022-05-03 20:00:00
2022-05-03 21:15:00