CSCW 2020 Conference Examines How Technology Will Impact the Future of Collaborative Work
Computer-Supported Cooperative Work and Social Computing Program Includes Leading-edge Research in Healthcare, Social Justice and Data for Good
New York, NY, October 19, 2020 – The dynamic interactions that occur when humans and computers collaborate will again be the focus of the 23rd Association for Computing Machinery (ACM) Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2020). CSCW is an international and interdisciplinary peer-reviewed conference presenting the best research on all topics relevant to collaborative and social computing. CSCW 2020, which will be held virtually for the first time ever on October 17-21, features outstanding research papers, as well as numerous posters and demos. The scope of CSCW spans the socio-technical domains of work, home, education, healthcare, the arts, entertainment and ethics.
“With society facing so many major challenges— especially in the areas of healthcare and social justice—research in computer-supported cooperative work can be vital in informing computer-human interaction,” said CSCW General Co-chair Andrea Wiggins, of the University of Nebraska at Omaha. “The annual CSCW conference showcases the best of this research, and how it can be applied to today’s issues.”
Added CSCW General Co-chair Matthew Bietz of the University of California, Irvine, “Our 2020 program demonstrates how research from an interdisciplinary community shines a light on the impact that can be made through socio-technical systems, and how those systems can impact society. The conference offers a range of keynotes, research papers and workshops designed to explore all these areas.”
CSCW 2019 HIGHLIGHTS
Storytelling for a More Equitable Open Science Enterprise
Maryam Zaringhalam, National Library of Medicine
Maryam Zaringhalam, PhD, the Data Science and Open Science Officer in the National Library of Medicine’s Office of Strategic Initiatives, believes the open science movement has often failed to address the needs of the general public, who are crucial stakeholders in the scientific enterprise. She argues that open science must therefore include open communication, particularly around emerging technologies that may carry an array of ethical and social implications. She will discuss how storytelling can place science in context while building trust and understanding—and creating opportunities for dialogue among diverse audiences.
Art of the Possible: Showcasing Data Science Solutions for a Better World
Afua Bruce, MBA (DataKind)
Afua Bruce, Chief Program Officer for DataKind, will discuss “data for good” programs at DataKind, a nonprofit organization that harnesses the power of data science in the service of humanity. Bruce will explore several real-world examples of successful projects to examine what it takes to shift work from individual interventions to systemic change that positively impacts sectors. As we collectively consider social justice in data science, Bruce will also discuss principles of civic engagement, best practices for ethical AI, and how co-designing inclusive projects allows diverse inputs to return equitable outcomes.
Below we have highlighted a few research papers from the CSCW 2020 program. For a full list of papers, visit here.
“Using the Crowd to Prevent Harmful AI Behavior”
Travis Mandel, Randall Tanaka, Chansen Haili, Jahnu Best, Hiram Temple, Sebastian J. Carter University of Hawaii at Hilo; Kayla Schlechtinger, University of Minnesota; Roy Szeto, University of Washington
To prevent harmful AI behavior, people need to specify constraints that forbid undesirable actions. In this paper, the authors study how to enable a crowd of humans to work together to communicate high-quality, reliable constraints to AI systems. Next, the authors develop a novel rule-based interface which allows people to craft rules in an accessible fashion without programming knowledge. They test their approaches on a real-world AI problem in the domain of education, and find that our new filtering mechanisms and interfaces significantly improve constraint quality and human efficiency. They also demonstrate how these systems can be applied to other real-world AI problems (e.g. in social networks).
“Learning from Tweets: Opportunities and Challenges to Inform Policy Making During Dengue Epidemic”
Farhana Shahid, Bangladesh University of Engineering & Technology & Cornell University; Shahinul Hoque Ony, Takrim Rahman Rahman Albi, BRAC University; Sriram Chellappan, University of South Florida, Aditya Vashistha, Cornell University; A. B. M. Alim Al Islam, Bangladesh University of Engineering & Technology
Social media platforms are now prevalent in almost all aspects of daily life. In this paper the authors study the responses of general public in response to dengue (a mosquito-borne tropical disease) in the scarce-resource settings of Bangladesh. The authors seek to explore the utility of pervasive social media health data in health research in the limited-resource settings of Bangladesh, where the availability and accessibility to government health data is limited. On the other hand, the lower Internet adoption rate in such areas make it difficult to seamlessly integrate such social media platforms in effective disease planning and intervention programs. Therefore, this paper explores the scope of effective policy making approaches based on the social media health data.
“On the Misinformation Beat: Understanding the Work of Investigative Journalists Reporting on Problematic Information Online”
Melinda McClure Haughey, Meena Devii Muralikumar, Cameron A Wood, Kate Starbird, University of Washington
Through in-depth interviews with twelve journalists, the University of Washington team explores how journalists investigate and report on online misinformation and disinformation. Their findings reveal some of the unique challenges of reporting on this beat, as well as the ways in which reporters overcome those challenges. The University of Washington team highlights and discusses how journalistic values could be better embedded into the design of tools to support their work, the power dynamics between social media companies and journalists, and the promise of collaborations as a way to support and educate journalists on this beat. One goal of this study is to provide contextual knowledge to researchers looking to better support investigative journalists (on the misinformation beat and beyond) as their work becomes more entangled in sociotechnical systems.
Best Paper Awards:
- “So-called privacy breeds evil Narrative Justifications for Intimate Partner Surveillance in Online Forums”
Rosanna Bellini, Newcastle University; Emily Tseng, Thomas Ristenpart, Nicola Dell Jacobs, Cornell Tech; Nora McDonald, Drexel University; Rachel Greenstadt, Damon McCoy, New York University
- “CommunityClick: Capturing and Reporting Community Feedback from Town Halls to Improve Inclusivity”
Mahmood Jasim, Pooya Khaloo, Somin Wadhwa, Ali Sarvghad, Narges Mahyar, University of Massachusetts Amherst; Amy X. Zhang, University of Washington
- “Decolonizing Tactics as Collective Resilience: Identity Work ofAAPI Communities on Reddit”
Bryan Dosono, Bryan Semaan, Syracuse University
- “How We've Taught Algorithms to See Identity”
Morgan Klaus Scheuerman, Kandrea Wade, Jed R. Brubaker, University of Colorado, Boulder; Caitlin Lustig, University of Washington
- “Between Subjectivity and Imposition: A Grounded Theory Investigation into Data Annotation”
Milagros Miceli, Martin Schuessler, Tianling Yang, Technical University Berlin
- “Undatafied Caregiving in an Increasingly Datafied World”
Karthik S Bhat, Neha Kumar, Georgia Institute of Technology
- “Socio-Spatial Comfort: Using Vision-based Analysis to Inform User-Centred Human-Building Interactions”
Michael Lee, Alexander Tessier, Pan Zhang, Autodesk Research; Bokyung Lee, Autodesk Research and Korea Institute of Science & Technology (KAIST); Daniel Saakes, KAIST; Azam Khan, University of Toronto
- “Piracy and the Impaired Cyborg: Assistive Technologies, Accessibility, and Access”
Priyank Chandra, University of Toronto
- “They Just Don't Get It: Towards Social Technologies for Coping with Interpersonal Racism”
Alexandra To, Jessica Hammer, Geoff Kaufman, Carnegie Mellon University; Wenxia Sweeney, Coe College
CSCW (cscw.acm.org) is the premier venue for presenting research in the design and use of technologies that affect groups, organizations, communities, and networks. Bringing together top researchers and practitioners from academia and industry who are interested in the area of social computing, CSCW encompasses both the technical and social challenges encountered when supporting collaboration.
ACM, the Association for Computing Machinery, is the world's largest educational and scientific computing society, uniting educators, researchers and professionals to inspire dialogue, share resources and address the field's challenges. ACM strengthens the computing profession's collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.