Call for Papers - Machine learning; Artificial Intelligence and Human Factors Design Special Issue Guest Editors: Nathan Lau, Virginia Tech; Myounghoon Jeon, Virginia Tech; & Michael Hildebrandt, Institute for Energy Technology Submissions are invited for a special issue in Ergonomics in Design (EID) Machine learning (ML) is enabling a new generation of artificial intelligence (AI) and autonomous systems that are changing our personal and the professional lives. In this special issue, we embrace the broad spectrum of research and design efforts that investigate or employ ML for improving Human Factors (HF) and usability of intelligent systems and consumer products. The central objective of this special issue is to provoke an active debate on theory, methods, and practice of designing for interactive AI. The issue seeks to clarify the roles of HF in contributing to a humanist perspective that considers the social, political, ethical, cultural, and environmental factors of implementing AI into daily human-to-computer interactions. https://lnkd.in/gmxRP4X

1. Call for Papers: Machine Learning, Artificial Intelligence, and Human Factors Design
Submissions are invited for a special issue in Ergonomics in Design (EID)
Machine learning (ML) is enabling a new generation of artificial intelligence (AI) and autonomous
systems that are changing our personal and the professional lives. In this special issue, we embrace the
broad spectrum of research and design efforts that investigate or employ ML for improving Human
Factors (HF) and usability of intelligent systems and consumer products. The central objective of this
special issue is to provoke an active debate on theory, methods, and practice of designing for interactive
AI. The issue seeks to clarify the roles of HF in contributing to a humanist perspective that considers the
social, political, ethical, cultural, and environmental factors of implementing AI into daily human-to-
computer interactions.
Potential topics of interest for this special issue include, but are not limited to, the following:
1. Explainable AI 2. Prototyping tools for ML or AI
3. Case studies of HF design with ML 4. Approaches, tools and design for data
annotation and transcription for supervised
learning
5. Industrial case studies where ML is used
for analysis of human-centered data
6. Approach to machine learning vs. approach to
(conventional) automation
7. HF and designer roles in the intelligent
product era
8. Human-centered design methods for generation
of training data
9. How Human Factors can influence the
development of new AI technologies
10. Methods of exploring the consequences of
design choices when creating AI systems
11. What and how to teach about ML and AI in
Human Factors education
12. Sociotechnical impact of ML and AI:
algorithmic fairness, bias, discrimination, trust,
& transparency.13. Human-centered interactive AI-enabled
products
TENTATIVE DEADLINES
Submissions* due: May 1, 2019
Decision letters sent: July 31, 2019
Revised manuscripts due: September 30, 2019
Special Issue for publication: January 2020
*Long feature articles should be between 1,500 and 3,000 words, Short articles should be limited to
between 1,000 and 1,500 words, and Commentaries on the topic should be limited to 500 words.
Prospective authors should follow the EID journal guidelines for preparing their manuscripts, view
publication policies and sample articles, and then submit your article via the EID submission site.
The web-based submission must accompany a cover-letter heading, “Machine Learning, Artificial
Intelligence, and Human Factors Design”. For questions, please contact any of the following:
Guest Editors
Nathan Lau, PhD
Virginia Tech
Blacksburg, VA 24061, USA
Email: nathan.lau@vt.edu
Myounghoon Jeon, PhD
Virginia Tech
Blacksburg, VA 24061, USA
Email: myounghoonjeon@vt.edu
Michael Hildebrandt
Institute for Energy Technology
Halden, Norway
Email: Michael.Hildebrandt@ife.no