skip to main content
10.1145/3334480.3381069acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
panel

From Human-Human Collaboration to Human-AI Collaboration: Designing AI Systems That Can Work Together with People

Published: 25 April 2020 Publication History
  • Get Citation Alerts
  • Abstract

    Artificial Intelligent (AI) and Machine Learning (ML) algorithms are coming out of research labs into the real-world applications, and recent research has focused a lot on Human-AI Interaction (HAI) and Explainable AI (XAI). However, Interaction is not the same as Collaboration. Collaboration involves mutual goal understanding, preemptive task co-management and shared progress tracking. Most of human activities today are done collaboratively, thus, to integrate AI into the already-complicated human workflow, it is critical to bring the Computer-Supported Cooperative Work (CSCW) perspective into the root of the algorithmic research and plan for a Human-AI Collaboration future of work. In this panel we ask: Can this future for trusted human-AI collaboration be realized? If so, what will it take? This panel will bring together HCI experts who work on human collaboration and AI applications in various application contexts, from industry and academia and from both the U.S. and China. Panelists will engage the audience through discussion of their shared and diverging visions, and through suggestions for opportunities and challenges for the future of human-AI collaboration.

    References

    [1]
    Matthew Arnold, Rachel K. E. Bellamy, Michael Hind, et al. 2018. FactSheets: Increasing Trust in AI Services through Supplier's Declarations of Conformity. arXiv:1808.07261 [cs].
    [2]
    Alessandra Curioni-Fontecedro. 2017. A new era of oncology through artificial intelligence. ESMO open 2, 2: e000198--e000198.
    [3]
    Mies C van Eenbergen, Lonneke V van de Poll-Franse, Peter Heine, and Floortje Mols. 2017. The Impact of Participation in Online Cancer Communities on Patient Reported Outcomes: Systematic Review. JMIR cancer 3, 2: e15--e15.
    [4]
    Robert Lindsey, Aaron Daluiski, Sumit Chopra, et al. 2018. Deep neural network improves fracture detection by clinicians. Proceedings of the National Academy of Sciences 115, 45: 11591--11596.
    [5]
    Licklider, J. C. R. 1960. Man-Computer Symbiosis IRE Transactions on Human Factors in Electronics Volume HFE-1(1): 4--11.
    [6]
    Yi-Chia Wang, Robert Kraut, and John M. Levine. 2012. To stay or leave?: the relationship of emotional and informational support to commitment in online health support groups. Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work - CSCW '12, ACM Press, 833
    [7]
    Dakuo Wang, Justin D. Weisz, Michael Muller, Parikshit Ram, Werner Geyer, Casey Dugan, Yla Tausczik, Horst Samulowitz, and Alexander Gray. "Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI." Proceedings of the ACM on Human-Computer Interaction 3, no. CSCW (2019): 1--24.
    [8]
    Jaimie Drozdal, Justin Weisz, Dakuo Wang, Gaurav Dass, Bingsheng Yao, Changruo Zhao, Michael Muller, Lin Ju, and Hui Su. "Trust in AutoML: Exploring Information Needs for Establishing Trust in Automated Machine Learning Systems." arXiv preprint arXiv:2001.06509 (2020).
    [9]
    Zhang, Amy X., Michael Muller, and Dakuo Wang. "How do Data Science Workers Collaborate Roles, Workflows, and Tools." arXiv preprint arXiv:2001.06684 (2020).

    Cited By

    View all

    Index Terms

    1. From Human-Human Collaboration to Human-AI Collaboration: Designing AI Systems That Can Work Together with People

      Recommendations

      Comments

      Please enable JavaScript to view thecomments powered by Disqus.

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      CHI EA '20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
      April 2020
      4474 pages
      ISBN:9781450368193
      DOI:10.1145/3334480
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 25 April 2020

      Check for updates

      Author Tags

      1. ai partner
      2. ai-powered healthcare
      3. computer-supported corporative work
      4. explainable ai
      5. group collaboration
      6. human-ai collaboration
      7. trusted ai

      Qualifiers

      • Panel

      Conference

      CHI '20
      Sponsor:

      Acceptance Rates

      Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)3,197
      • Downloads (Last 6 weeks)259
      Reflects downloads up to 14 Aug 2024

      Other Metrics

      Citations

      Cited By

      View all
      • (2024)Navigating the Fourth Industrial RevolutionData-Driven Business Intelligence Systems for Socio-Technical Organizations10.4018/979-8-3693-1210-0.ch001(1-27)Online publication date: 23-Feb-2024
      • (2024)The Future Is Already HereThe Role of Generative AI in the Communication Classroom10.4018/979-8-3693-0831-8.ch015(316-336)Online publication date: 23-Feb-2024
      • (2024)Hybrid work – a reconceptualisation and research agendai-com10.1515/icom-2023-002723:1(71-78)Online publication date: 20-Mar-2024
      • (2024)Does More Advice Help? The Effects of Second Opinions in AI-Assisted Decision MakingProceedings of the ACM on Human-Computer Interaction10.1145/36537088:CSCW1(1-31)Online publication date: 26-Apr-2024
      • (2024)AINeedsPlanner: A Workbook to Support Effective Collaboration Between AI Experts and ClientsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661577(728-742)Online publication date: 1-Jul-2024
      • (2024)Generative AI for Pull Request Descriptions: Adoption, Impact, and Developer InterventionsProceedings of the ACM on Software Engineering10.1145/36437731:FSE(1043-1065)Online publication date: 12-Jul-2024
      • (2024)Rocks Coding, Not Development: A Human-Centric, Experimental Evaluation of LLM-Supported SE TasksProceedings of the ACM on Software Engineering10.1145/36437581:FSE(699-721)Online publication date: 12-Jul-2024
      • (2024)Mental-LLMProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435408:1(1-32)Online publication date: 6-Mar-2024
      • (2024)"It Felt Like Having a Second Mind": Investigating Human-AI Co-creativity in Prewriting with Large Language ModelsProceedings of the ACM on Human-Computer Interaction10.1145/36373618:CSCW1(1-26)Online publication date: 26-Apr-2024
      • (2024)Healthcare Voice AI Assistants: Factors Influencing Trust and Intention to UseProceedings of the ACM on Human-Computer Interaction10.1145/36373398:CSCW1(1-37)Online publication date: 26-Apr-2024
      • Show More Cited By

      View Options

      Get Access

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      HTML Format

      View this article in HTML Format.

      HTML Format

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media