[Air-L] Call for participation: PDW at Academy of Management on Work in the Age of Intelligent Machines

[Kevin G Crowston]

Call for Participation

Work in the Age of Intelligent Machines<https://waim.network/node/748>
Academy of Management Professional Development Workshop

9:30-12:30 CT 11 August 2018 Swisshotel, Chicago IL

Quick links: Position statement submission<https://easychair.org/conferences/?conf=waimaom2018>  Registration<https://secure.aom.org/PDWReg/logon.asp> (by 9 August 2018)

How work will be impacted by rapidly increasing technological capabilities has been a long-standing concern of many researchers from numerous disciplines. However, growing interest in the impacts of automation on work is beginning to compel researchers to form new coalitions across traditional disciplinary boundaries.

This professional development workshop (PDW) at the Academy of Management Annual Meeting aims to promote disciplinary convergence among its participants in relation to work in the age of intelligent machines. Convergence is defined by the National Science Foundation as “the deep integration of knowledge, techniques, and expertise from multiple fields to form new and expanded frameworks” (NSF, 2017<https://www.nsf.gov/od/oia/convergence/index.jsp>). Using this idea as an organizing principle, the PDW will introduce participants to the idea that by embracing research from other disciplines, researchers can inform our emergent conceptual foundations and concomitant strategies in relation to the transformation of work via artificial intelligence.

Three issues illustrate the implicit interdisciplinarity of work in the age of the intelligent machine.

  *   First, most people spend the majority of their time working, an act that provides them not only with material rewards, but, for many, personal identity, social status and psychological well-being. As a result, designing work in the age of intelligent machines implicates workers on variety of levels, including attitudinal outcomes such as satisfaction or motivation, behavioral outcomes such as performance or turnover, cognitive outcomes such as learning or identity, and well-being outcomes, such as anxiety, stress or burnout.
  *   Second, automation may cause not only shifts in the type of jobs and needed qualifications, but also in their location. For example, knowledge work is normally associated with a a shift from rural to urban jobs, but more automated transportation may extend commutes. It is critical therefore to identify and monitor the differential impact of intelligent machines along a variety of specific facets, such as workforce diversity, regional unemployment variations, or other issues of education, social class and race.
  *   Third, there are important organization-level issues to consider as the core of the organization is automated. How, for example, will career paths shift if a system automates entry-level work?

These and a myriad of additional examples point to an urgent need for cooperative integration among disciplines. It is only by this means that a better understanding of the interrelationships among machines, people, tasks, and organizations can be adequately assessed.

Goals

The PDW will pursue three goals: 1) identifying specific research problems around work and intelligent machines that require an interdisciplinary, convergent approach; 2) discussing how to develop a common language base that can facilitate interdisciplinary collaboration among researchers; and 3) imagining the necessary resources to support convergent research, including information and cyber-infrastructure needs.

Participation

To participate, please submit a short position statement that expresses your interest in intelligent machines and their impacts on and implications for work. We encourage participation from any disciplinary perspective, including (but not limited to) urban planning, computer science, sociology, information systems, transportation, economics, psychology, law, media studies, engineering, public policy, artificial intelligence—any perspective that can help foster convergent thinking around this increasingly important topic in our society.

The following types of position statements are welcome:

Track 1: Current Empirical Research:  What is happening now?

Position statements in this track should report on studies that examine the current state of the art with regard to intelligent machines and work.

Track 2: Research questions:  What will happen next?

Position statements in this track should identify generative research questions and potential study designs. For any particular question, we are especially interested in identifying necessary empirical requirements, including data, site access, etc. What would be needed to answer your question?

Statements should be submitted at https://easychair.org/conferences/?conf=waimaom2018. The deadline to register online<https://secure.aom.org/PDWReg/logon.asp> for the PDW is 9 August 2018.

Venue

The PDW will be held in conjunction with the Academy of Management Annual Meeting in Chicago, IL. The workshop will begin at 9:30 am CT on Saturday 11 Aug 2018 in the Swisshotel and run to lunch. An optional off-site lunch and meeting will enable participants to continue their discussions.

Organizers

Kevin Crowston, Syracuse University
Mary Beth Watson-Manheim, University of Illinois, Chicago
Ingrid Erickson, Syracuse University
Jeffrey Nickerson, Stevens Institute of Technology

Sponsorship

This workshop is part of a series sponsored by the Research Collaboration Network on Work in the Age of Intelligent Machines<http://waim.network/> (NSF IIS-1745463).

Contact

All questions about submissions or the PDW should be emailed to aom18 at waim.network


Kevin Crowston
Associate Dean for Research, Distinguished Professor of Information Science
School of Information Studies

+1 (315) 443.1676
crowston at syr.edu<mailto:crowston at syr.edu>

348 Hinds Hall, Syracuse, NY 13244
crowston.syr.edu <http://crowston.syr.edu/>

Syracuse University
Most recent publications:

Jackson, C. B., Crowston, K., Østerlund, C., & Harandi, M. (2018). Folksonomies to support coordination and coordination of folksonomies. Computer Supported Cooperative Work. doi:10.1007/s10606-018-9327-z

Lee, T. Kyoung, Crowston, K., Harandi, M., Østerlund, C., & Miller, G.. (2018). Appealing to different motivations in a message to recruit citizen scientists: results of a field experiment. Journal of Science Communication. doi:10.22323/2.17010202

Crowston, K., & Fagnot, I.. (2018). Stages of motivation for contributing user-generated content: A theory and empirical test. International Journal of Human-Computer Studies, 109, 89-101. doi:10.1016/j.ijhcs.2017.08.005

Check out our new research coordination network on Work in the Age of Intelligent Machine:  http://waim.network/