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 (https://journals.sagepub.com/home/erg) for preparing their manuscripts, view publication policies and sample articles, and then submit your article via https://mc.manuscriptcentral.com/ergonomicsindesign. The web-based submission must accompany a cover-letter heading, “Special Issue: Machine Learning, Artificial Intelligence, and Human Factors Design”. For questions about submissions, 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