Cognitive Systems Engineering Issues in the Design of Machine Learning Systems

Abstract

The objective of this panel is to better understand how machine learning (ML) systems influence users and to identify strategies to make such interactions more effective when designing decision support systems and joint cognitive systems for real-time control. The panelists will draw upon their insights from the fields of aviation, defense, ground transportation and medicine, as well as the literature on human-automation and human-AI interaction. The panelists will discuss findings regarding both the positive and negative influences that the design of such systems can have on perceptual, cognitive and decision making processes. They will further provide concrete examples of system designs. Topics for discussion will include: (a) The Ironies of AI Based on Machine Learning: Challenges and New Directions, (b) Understanding the Influences of ML on Joint Cognitive Performance, (c) Mixed Initiative Access to Information, (d) Focusing and Accelerating Decision Making, and (e) Designing the Operational Domain.