Looking for PhD students

I am looking for PhD students interested in working on research about the future of work with intelligent machines, as well as the work on the Gravity Spy citizen science project. Please email if you're interested and want to talk more.

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

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

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

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.

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

Type: Presentation
Author: Christine T. Wolf
Year of Publishing: 2019

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.


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  • From VOXEU: Robots and jobs: Evidence from the US (6 years old, but still interesting): https://t.co/MT7jA4ZB5U 7 months 1 week ago
  • From the Wall Street Journal: Autonomous Delivery and Work Drones Will Still Need a Human Minder: https://t.co/ao9FwXrs70 7 months 1 week ago
  • From MIT Technology Review: Inside Japan’s long experiment in automating elder care: https://t.co/LDj9HFGnYx 7 months 2 weeks ago
  • From the Guardian: Amazon enters the age of robots. What does that mean for its workers? https://t.co/nPg1prMRko 7 months 2 weeks ago
  • From the Washington Post: The robots are here. And they are making you fries: https://t.co/ZbvlsCsaTb 7 months 2 weeks ago
  • Please see the WAIM RCN home page (https://t.co/ORVkhtoZjp) for news about the future of this feed. 7 months 2 weeks ago
  • From Ars Technica: New Meta AI demo writes racist and inaccurate scientific literature, gets pulled: https://t.co/40HOuf4eah 7 months 2 weeks ago
  • From MIT Technology Review: How robotic honeybees and hives could help the species fight back: https://t.co/SLjyoXOtfj 7 months 3 weeks ago
  • Quoted (Feb 2, 2023) in the news article "Robot: I’m sorry. Human: I don’t care anymore!" written on our new paper… https://t.co/jftxTixw3c 7 months 3 weeks ago
  • From AI Hub: Using machine learning to help generalize automated chemistry: https://t.co/2wFw4UMbxW 7 months 3 weeks ago