Impacts of the Use of Machine Learning on Work Design

Crowston, K., & Bolici, F.. (2020). Impacts of the Use of Machine Learning on Work Design. In 8th International Conference on Human-Agent Interaction. https://doi.org/10.1145/3406499.3415070

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 Axios: AI-generated digital art spurs debate about news illustrations: https://t.co/lnIpgjAl1s — 2 weeks 2 days ago
  • Call for papers for a special issue of Information, Technology & People on The Futures of Work in the Age of Intell… https://t.co/ljILEhmQC2 — 3 weeks 3 days ago
  • From Fast Company: When will robots take our jobs? https://t.co/7N63ExaFFx? — 3 weeks 3 days ago
  • From Entrepreneur: These 5 Freelance Jobs Are Being Transformed by AI https://t.co/esi1OyA056 (a bit techno-optimistic) — 1 month 2 weeks ago
  • From New Scientist: DeepMind AI learns physics by watching videos that don’t make sense: https://t.co/m1uQGAxB95 — 1 month 3 weeks ago
  • From MIT Technology Review: Inside a radical new project to democratize AI: https://t.co/lLuEgWLiK8 — 1 month 3 weeks ago
  • From Nature: ‘The entire protein universe’: AI predicts shape of nearly every known protein: https://t.co/RKiUawBxWw — 2 months 38 min ago
  • The described report is available here: https://t.co/mS7AZUUlsq — 2 months 3 days ago
  • From the National Academies: Automated Research Workflows Are Speeding Pace of Scientific Discovery; New Report Off… https://t.co/Xp7SFM3bvA — 2 months 3 days ago
  • From Nature: How language-generation AIs could transform science: https://t.co/6qAdDaStdw — 2 months 3 days ago

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