research-article

Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI

Authors:

Justin D. Weisz,

Michael Muller,

Horst Samulowitz,

Alexander GrayAuthors Info & Claims

Proceedings of the ACM on Human-Computer Interaction, Volume 3, Issue CSCW

Article No.: 211, Pages 1 - 24

https://doi.org/10.1145/3359313

Published: 07 November 2019 Publication History

Abstract

The rapid advancement of artificial intelligence (AI) is changing our lives in many ways. One application domain is data science. New techniques in automating the creation of AI, known as AutoAI or AutoML, aim to automate the work practices of data scientists. AutoAI systems are capable of autonomously ingesting and pre-processing data, engineering new features, and creating and scoring models based on a target objectives (e.g. accuracy or run-time efficiency). Though not yet widely adopted, we are interested in understanding how AutoAI will impact the practice of data science. We conducted interviews with 20 data scientists who work at a large, multinational technology company and practice data science in various business settings. Our goal is to understand their current work practices and how these practices might change with AutoAI. Reactions were mixed: while informants expressed concerns about the trend of automating their jobs, they also strongly felt it was inevitable. Despite these concerns, they remained optimistic about their future job security due to a view that the future of data science work will be a collaboration between humans and AI systems, in which both automation and human expertise are indispensable.

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Index Terms

Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Computer supported cooperative work

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cover image Proceedings of the ACM on Human-Computer Interaction

Proceedings of the ACM on Human-Computer Interaction Volume 3, Issue CSCW

November 2019

5026 pages

EISSN:2573-0142

DOI:10.1145/3371885

Editors:
Airi Lampinen
Stockholm University, Sweden
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Darren Gergle
Northwestern University, USA
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David A. Shamma
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Published: 07 November 2019

Published in PACMHCI Volume 3, Issue CSCW

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