Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy

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) framework 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 methods of HCAI are more likely to produce designs that are Reliable, Safe & Trustworthy (RST). Achieving these goals will dramatically increase human performance, while supporting human self-efficacy, mastery, creativity, and responsibility.

Acknowledgments

Thanks to Michael Bernstein, Linda Candy, Ryan Carrier, Jianming Dong, Bonnie Dorr, Ernest Edmonds, Robert Fraser, Harry Hochheiser, Robert Hoffman, Eric Hughes, Gary Klein, Alan Mackworth, Doug Oard, Catherine Plaisant, Jennifer Preece, Robin Murphy, Steven M. Rosen, Arnon Rosenthal, Gavriel Salvendy, Ariel Sarid, Ben Sawyer, Thomas Sheridan, Mark Smith, Constantine Stephanidis, Harold Thimbleby, Fernanda Viegas, Jamie Waese, Martin Wattenberg, and David D. Woods for comments on early drafts.

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Ben Shneiderman

Ben Shneiderman 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.