Artificial Intelligence and Work: AAAI 2019 Fall Symposium

We seek participants for a two and one-half day symposium to be held 7–9 November 2019 in Washington, DC, USA, to discuss and plan how AI researchers will contribute to research on human work with artificial intelligence. The draft symposium schedule and papers are now available (NB. you must be logged in to the website to see the papers).

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 .

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
Keywords:

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:

Call for papers: Organization Science special issue on Emerging Technologies and Organizing

Special Issue Editors
Diane Bailey, Samer Faraj, Pamela Hinds, Georg von Krogh, and Paul Leonardi

Workshop report: Developing Skills to Work in the Age of Intelligent Machines (Pre-HICSS workshop)

A workshop was held 1pm – 4pm, 8 January 2019 in Wailea, HI, before the annual Hawai'i International Conference on System Sciences. It was the 4th workshop to be sponsored by the WAIM RCN. The workshop was organized by Elaine Mosconi, Université de Sherbrooke, Kevin Crowston, Syracuse University and Jeffrey Nickerson, Stevens Institute of Technology. The topic was "Developing Skills to Work in the Age of Intelligent Machines", though the discussion ranged more broadly. There were about 50 attendees.

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Recent tweets

  • New Scientist: Mind meld: Artificial intelligence is improving the way humans think: https://t.co/UtcKaW5Ku0 3 days 6 hours ago
  • From Nautilus: Why Futurism Has a Cultural Blindspot: We predicted cell phones, but not women in the workplace: https://t.co/mOBnnOKID3 3 days 17 hours ago
  • Related from the BBC: DeepMind AI achieves Grandmaster status at Starcraft 2: https://t.co/63LbxltFRy 1 week 5 days ago
  • From the Independent: Artificial intelligence conquers StarCraft II in ‘unimaginably unusual’ AI breakthrough: https://t.co/YpLhMh4p0x 1 week 5 days ago
  • From Nature: Three pitfalls to avoid in machine learning: https://t.co/il3vU96UOY 1 week 6 days ago
  • From NYT: Would You Want a Computer to Judge Your Risk of H.I.V. Infection? https://t.co/X4YifDApHa 3 weeks 2 days ago
  • From Vox: An AI learned to play hide-and-seek. The strategies it came up with on its own were astounding: https://t.co/r7ncCE5ZpF 3 weeks 4 days ago
  • From Nature: Why deep-learning AIs are so easy to fool: https://t.co/UTwhH6kBUD 3 weeks 5 days ago
  • From the New Yorker: The Hidden Costs of Automated Thinking: https://t.co/qB22CvHzbp 3 weeks 6 days ago
  • From SIOP: Enhancing Judgment: The Case for Human–Algorithm Collaboration by Jon C. Willford, Edison Electric Insti… https://t.co/K9jT7EzsEd 1 month 2 weeks ago

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