AI & Fundamentals

Human-Centered Artificial Intelligence: Trusted, Reliable and Safe - Ben Shneiderman, Emeritus Distinguished University Professor, University of Maryland; Founding Director of the Human-Computer Interaction Laboratory

Abstract:

Well-designed technologies that offer high levels of human control and high levels of computer automation can increase human performance, leading to wider adoption. The Human-Centered Artificial Intelligence (HCAI) model clarifies how to (1) design for high levels of human control and high levels of computer automation so as to increase human performance, (2) understand the situations in which full human control or full computer control are necessary, and (3) avoid the dangers of excessive human control or excessive computer control. The new goal of HCA is more likely to produce designs that are Trusted, Reliable & Safe (TRS). Achieving these goals will dramatically increase human performance, while supporting human self-efficacy, mastery, creativity, and responsibility. 

Design guidelines and independent oversight mechanisms for prospective design reviews and retrospective analyses of failures will clarify the role of human responsibility, even as automation increases.  Examples of failures, such as the Boeing 737 MAX, will be complemented by positive examples such as elevators, digital cameras, medical devices, and TRS cars.

Paper available at: https://arxiv.org/abs/2002.04087v1 

Bio:

BEN SHNEIDERMAN (http://www.cs.umd.edu/~ben) is an Emeritus Distinguished University Professor in the Department of Computer Science, Founding Director (1983-2000) of the Human-Computer Interaction Laboratory (http://hcil.umd.edu), and a Member of the UM Institute for Advanced Computer Studies (UMIACS) at the University of Maryland.  He is a Fellow of the AAAS, ACM, IEEE, and NAI, and a Member of the National Academy of Engineering, in recognition of his pioneering contributions to human-computer interaction and information visualization. His widely-used contributions include the clickable highlighted web-links, high-precision touchscreen keyboards for mobile devices, and tagging for photos.  Shneiderman’s information visualization innovations include dynamic query sliders for Spotfire, development of treemaps for viewing hierarchical data, novel network visualizations for NodeXL, and event sequence analysis for electronic health records.

Ben is the co-author with Catherine Plaisant of Designing the User Interface: Strategies for Effective Human-Computer Interaction (6th ed., 2016).  He co-authored Readings in Information Visualization: Using Vision to Think (1999) and Analyzing Social Media Networks with NodeXL (2^nd edition, 2019).  His book Leonardo’s Laptop (MIT Press) won the IEEE book award for Distinguished Literary Contribution. The New ABCs of Research: Achieving Breakthrough Collaborations (Oxford, 2016) describes how research can produce higher impacts.