About the RCN

Members of the WAIM network are developing the understanding needed to jointly design both sides of the human-technology frontier in work settings and using intelligent machines. Join now by clicking .

Artificial intelligence and the world of work, a co-constitutive relationship

Submitted by crowston on Mon, 2020-07-06 15:50

Check out this new JASIS&T paper based on the 2019 iConference workshop: . Thanks (and congrats) to Carsten, Mohammad, Matt, Karen and Christine!

Call for participation: Virtual paper development workshops for papers on work in the age of intelligent machines

Submitted by crowston on Fri, 2020-07-03 11:48

Our main activity over the past few years has been organizing workshops and an annual conference, but both are on hold due to the ongoing COVID crises. Indeed, with everything that’s going on, research may currently be lower-priority or even on pause for many people. Yet, as a research coordination network, we’d like to provide a small means of social support that may spur you on even in these challenging times. To this end, we are organizing a series of mini paper-development workshops, to be held virtually throughout the summer and perhaps beyond.

Lessons for Supporting Data Science from the Everyday Automation Experience of Spell-Checkers

Crowston, K. (2020). Lessons for Supporting Data Science from the Everyday Automation Experience of Spell-Checkers. In Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual. Presented at the Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual, Virtual workshop.

WAIM Convergence Conference 2020 postponed

Submitted by crowston on Mon, 2020-03-30 08:23

In light of the ongoing COVID-19 crisis, we have decided to postpone the 3rd annual WAIM Convergence Conference to northern hemisphere fall 2020. A new date and participation information will be posted soon.

CSCW Workshop: Better supporting workers in ML workplaces

This workshop is aimed at bringing together a multidisciplinary group to discuss Machine Learning and its application in the workplace as a practical, everyday work matter. It’s our hope this is a step toward helping us design better technology and user experiences to support the accomplishment of that work, while paying attention to workplace context. Despite advancement and investment in ML business applications, understanding workers in these work contexts have received little attention.

The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning

Harandi, M., Crowston, K., Jackson, C., & Østerlund, C.. (2020). The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning. In Hawai'i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.719

Factors Influencing Approval of Wikipedia Bots

Dalgali, A., & Crowston, K.. (2020). Factors Influencing Approval of Wikipedia Bots. In Hawai'i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.018

Situating “explainability”: Making sense of data-driven assemblages in organizational context

Submitted by chris-wolf on Mon, 2019-08-19 08:21
Type: Presentation
Author: Christine T. Wolf
Year of Publishing: 2019
Keywords:
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The rise of data-driven technologies in recent years has sparked renewed attention to questions of technological sensemaking and in particular the explainability or interpretability of such systems (a growing technical subfield commonly called “Explainable AI” or “XAI”). These approaches tend to focus on the technology itself (often at the level of model or predictive output) and fail to consider the broader context of use and the situated nature of technological sensemaking.

WAIM Convergence Conference: At the Boundary: Exploring Human-AI Futures in Context

The 2nd WAIM Convergence Conference on the theme At the Boundary: Exploring Human-AI Futures in Context was held 14-15 August 2019 at Syracuse University's on the upper east side of Manhattan. Some key documents (note that you must be logged in to the site to view some of these):

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Recent tweets

  • From Forbes: Is Augmented Intelligence The Best Perspective On AI? https://t.co/tui6lxSVEC — 1 week 6 days ago
  • From Communications of the ACM: Leveraging Unlabeled Data: https://t.co/YyQne7st6s — 1 week 6 days ago
  • From The Next Web: Self-supervised learning is the future of AI: https://t.co/5Izid4EBod — 3 weeks 2 days ago
  • From the Register: What would machine learning look like if you mixed in DevOps? Wonder no more, we lift the lid on… https://t.co/R0dZk7g86v — 3 weeks 6 days ago
  • From Car and Driver: The Enemies of the Autonomous Vehicle: https://t.co/UE4Nx2Yevu — 4 weeks 1 hour ago
  • From Baidu via MIT Technology Review: How coronavirus is accelerating a future with autonomous vehicles: https://t.co/yiHGoPr51Z — 4 weeks 1 day ago
  • From: MIT Technology Review: Self-driving cars are being trained in virtual worlds while the real one is in chaos: https://t.co/nIMr4nJHXL — 1 month 18 hours ago
  • https://t.co/WYRgjt34TF for participation: Virtual paper development workshop for papers on work in the age of intelligent machines> — 1 month 1 week ago
  • From Cornell via NSF: AI as mediator: ‘Smart’ replies help humans communicate during pandemic: https://t.co/aJEOXqYS7i — 1 month 1 week ago
  • A news report about the conference from MIT: https://t.co/GVALJqWRpT — 1 month 1 week ago

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