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The Work in the Age of Intelligent Machines (WAIM) Research Coordination Network is pleased to announce the WAIM Doctoral Research Fellowship program—a competition that aims to recognize and support outstanding graduate research related to the convergence of intelligent machines and the future of work. With funding from the National Science Foundation’s Future of Work at the Human-Technology Frontierhttps://www.nsf.gov/eng/futureofwork.jsp initiative, this fellowship program will confer a select number of $50,000 awards to eligible US doctoral students to enable them to focus solely on their research during the 2021–2022 academic year. In sponsoring this program, we hope to identify the next set of leaders in building the deep and systematic knowledge required to simultaneously consider the technical, individual, group, organizational, and societal issues involved in leveraging today’s expanding technological capabilities to serve both work and workers.
Eligible candidates for this program are late-stage students enrolled in a research-based doctoral program at an accredited US-institution who are engaged in research that embraces the future of work as a socio-technological phenomenon—one that requires attention to both social and technological systems as well as the implications of their interdependencies. Addressing this challenge requires a research approach that expands beyond a delimited focus on autonomous systems qua systems and instead endorses a convergent approach, namely “the deep integration of knowledge, techniques, and expertise from multiple fields to form new and expanded frameworks” (NSF, 2017). As such, we welcome candidates who draw on a wide variety of disciplinary perspectives, including labor studies, law, psychology, computer science, management science, policy studies, anthropology, sociology, learning science, and cognitive science, among others.
Future WAIM Fellows will interact as a cohort to enable peer exchange and learning. The cohort will come together physically at two meetings during the 2021-22 academic year. The first will be a kickoff event, currently planned for September 2021 in Manhattan. The second event will be during the summer of 2022 at the final WAIM Convergence Conference (location tbd). We will also require that each Fellow attend the dissertation defense of at least 2 peer Fellows virtually and will encourage each Fellow to open any public presentation of their research to other members of the cohort as well as members of the larger WAIM network.
Fellowship applications will be evaluated in relation to their potential for intellectual merit, broader impact, and resonance with the WAIM RCN mission and themehttps://waim.network/about. For the purpose of this call, we define ‘work’ as the mental or physical activity to achieve tangible benefit such as income, profit, or community welfare. We use the phrase ‘intelligent machines’ to refer to computing technologies characterized by autonomy, the ability to learn, and the ability to interact with other systems and with humans. The first cohort of WAIM Fellows will be announced in early August 2021.
To apply, please submit the following materials on the online reviewing systemhttps://syracuse.infoready4.com/#competitionDetail/1845709 by 15 July 2021 (midnight EDT):
Download this call as a PDFhttps://waim.network/fellowshippdf.
Associate Dean for Research, Distinguished Professor of Information Science
School of Information Studies
Editor-in-chief ACM Transactions on Social Computing and Information, Technology & People
348 Hinds Hall, Syracuse, NY 13244
Most recent publications:
Eseryel, U. Y., Crowston, K., & Heckman, R.. (In press). Functional and visionary leadership in self-managing virtual teams. Group & Organization Management. doi: 10.1177/1059601120955034
Jackson, C. B., Østerlund, C., Harandi, M., Crowston, K., & Trouille, L. (2020). Shifting forms of presence: Volunteer learning in online citizen science. Proceedings of the ACM on Human-Computer Interaction, (CSCW), 36. doi: 10.1145/3392841
Eseryel, U. Y., Wei, K., & Crowston, K. (2020). Decision-making processes in community-based free/libre open source software development teams with internal governance: An extension to decision-making theory. Communications of the Association for Information Systems, 46. doi: 10.17705/1CAIS.04620
Jackson, C., Østerlund, C., Crowston, K., Harandi, M., Allen, S., Bahaadini, S., et al. (2020). Teaching citizen scientists to categorize glitches using machine-learning-guided training. Computers In Human Behavior, 105, 106198. doi: 10.1016/j.chb.2019.106198
Check out our research coordination network on Work in the Age of Intelligent Machine: http://waim.network/