research-article

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

Authors:

Hariharan Subramonyam,

Colleen Seifert,

Eytan AdarAuthors Info & Claims

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Article No.: 481, Pages 1 - 21

https://doi.org/10.1145/3491102.3517537

Published: 29 April 2022 Publication History

Abstract

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.

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Cited By

Wang YLin YHuang RWang JLiu S(2024)Enhancing user experience in large language models through human-centered design: Integrating theoretical insights with an experimental study to meet diverse software learning needs with a single document knowledge baseComputing and Artificial Intelligence10.59400/cai.v2i1.5352:1(535)Online publication date: 19-Apr-2024
https://doi.org/10.59400/cai.v2i1.535
Aldoseri AAl-Khalifa KHamouda A(2024)AI-Powered Innovation in Digital Transformation: Key Pillars and Industry ImpactSustainability10.3390/su1605179016:5(1790)Online publication date: 22-Feb-2024
https://doi.org/10.3390/su16051790
Liao QVorvoreanu MSubramonyam HWilcox L(2024)UX Matters: The Critical Role of UX in Responsible AIInteractions10.1145/366550431:4(22-27)Online publication date: 26-Jun-2024
https://dl.acm.org/doi/10.1145/3665504
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Index Terms

Solving Separation-of-Concerns Problems in Collaborative Design of Human-AI Systems through Leaky Abstractions
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI theory, concepts and models
2. Software and its engineering
  1. Software creation and management
    1. Collaboration in software development
    2. Designing software
  2. Software organization and properties
    1. Software system structures
      1. Abstraction, modeling and modularity

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cover image ACM Conferences

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

April 2022

10459 pages

ISBN:9781450391573

DOI:10.1145/3491102

Editors:
Simone Barbosa
PUC-Rio, Brazil
,
Cliff Lampe
University of Michigan, USA
,
Caroline Appert
Université Paris-Saclay, France
,
David A. Shamma
Toyota Research Institute, USA
,
Steven Drucker
Microsoft Research, USA
,
Julie Williamson
University of Glasgow, UK
,
Koji Yatani
University of Tokyo, Japan

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https://doi.org/10.59400/cai.v2i1.535
Aldoseri AAl-Khalifa KHamouda A(2024)AI-Powered Innovation in Digital Transformation: Key Pillars and Industry ImpactSustainability10.3390/su1605179016:5(1790)Online publication date: 22-Feb-2024
https://doi.org/10.3390/su16051790
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