By Amy R. Pritchett, Editor in Chief and Jan Maarten Schraagen, Editor in Chief elect
invites submissions for a new special issue that targets integrative approaches to the design and implementation of human-machine teaming. With the advent of Artificial Intelligence, machines offer the capability to act as intelligent teammates that can collaborate and cooperate with their human counterparts. It is important to draw a distinction between human-machine interaction and human-machine teaming, not only in terms of how the relationship between human and ma-chine is conceptualized, but also in terms of the way that questions relating to allocation of function need to be reframed to support human-machine teams. For example it may be argued that in order to act as a true team member, the machine would need to facilitate coordination, understand and work toward shared goals, and repair or prevent breakdowns in team coordination. Issues raised include – whether, how and when a machine might take over certain functions from the human as well as whether, how and when the AI might handover functions to the human (perhaps when the situation lies outside the AI’s realm of experience).Other issues raised include the need for the AI to be explorable, explainable, observable, directable, negotiable and controllable. Equally, for the AI to make sense of human actions, it needs to better understand operator intent and the tacit knowledge that humans might bring to their performance. Questions also arise from a training perspective with respect to training needs of both the human and the machine team mates.
For this issue, we are seeking papers that help to define the agenda for future research into human-machine teaming. This could involve roadmaps and position papers, but we believe that many of these issues are already being subjected to study in laboratories or in prototype systems. Thus, we encourage submissions that take an integrative approach to topics that promise to further the inter-ests of designers, evaluators, policymakers, and humans who use intelligent technology at work. We are interested in papers that consider novel ways of teaming humans and automation, ways to better integrate cognitive engineering into the design of human-machine teams, new ap-proaches to selecting or training humans to work with AI, potential outcomes of the increasing complexity of automation, ways of addressing the challenges of explainable AI, approaches to hu-man-machine dialogue design that focus on development and maintenance of common ground, and case studies of cognitive engineering in applied human-automation relations that progress our un-derstanding from ‘interaction’ to ‘teaming’.
Following the broader mission of JCEDM
, submissions will be evaluated relative to several criteria:
- Contribution to a target domain (Does the research tackle a real problem, no matter how messy, and value ecological and task validity in its research methods?);
- Contribution to other do-mains (Does the research contribute to understanding the human contribution to complex work do-mains, and demonstrating rigorous, repeatable methods in one domain that others can apply to other domains?); and
- Contribution to theory underlying work in complex environments (Does the re-search demonstrate a reasonable understanding of all the relevant aspects of human performance, and identify gaps requiring further research?).
There is no numerical formula for weighting these three contributions when evaluating submissions - each paper is urged to articulate its specific con-tributions to the research, design and operational community. The submission deadline is January 11, 2019
. Please direct any inquiries to special issue editor Jan Maarten Schraagen at email@example.com
. Prior to submitting your work, be sure to consult the JCEDM instructions for authors (http://www.hfes.org/web/pubpages/jcedminsauthors.html
). Manuscripts should be submitted electronically via Manuscript Central (http://mc.manuscriptcentral.com/jcedm