Robert Hoffman

Senior Research Scientist Emeritus

Robert R. Hoffman, Ph.D. is a recognized world leader in cognitive systems engineering and Human-Centered Computing. He is a Senior Member of the Association for the Advancement of Artificial Intelligence, Senior Member of the Institute of Electrical and Electronics and Engineers, Fellow of the Association for Psychological Science, Fellow of the Human Factors and Ergonomics Society, and a Fulbright Scholar. He has been Principal Investigator, Co-Principal Investigator, Principal Scientist, Senior Research Scientist, Principal Author, or Principle Subcontractor on over 60 grants and contracts totaling over $16M. He has led efforts including large, multi-partner, multi-year grant collaborations, contracted alliances of university and private sector partners, and multi-university research initiatives. His Ph.D. is in experimental psychology from the University of Cincinnati, where he received McMicken Scholar, Psi Chi, and Delta Tau Kappa Honors. Following a Postdoctoral Associateship at the Center for Research on Human Learning at the University of Minnesota, he joined the faculty of the Institute for Advanced Psychological Studies at Adelphi University. Hoffman has been recognized internationally in cognitive systems engineering, applied psychology, artificial intelligence, and human factors engineering—for his research on the methodology of cognitive task analysis and human-centering issues for human-systems integration systems technology. He has co-authored and co-edited 18 scholarly books and is co-author on over 100 publications in peer-reviewed journals. For twenty years, he served as Co-Editor for the Department on Human-Centered Computing in IEEE: Intelligent Systems. In this Department, Hoffman published 70 essays on human-centered computing. He was a co-founder of The Journal of Cognitive Engineering and Decision Making. His current research focuses on methodological and measurement issues in the analysis of complex systems, and performance measurement for complex work systems. A full vita and all of his publications are available upon request to []

Most Recent Books

Ericsson, K.A., Hoffman, R.R., Kozbelt, A., and Williams, M. (2018). Cambridge handbook of expertise and expert performance (2nd. ed.). Cambridge: Cambridge University Press.

White, R.A.,  Çoltekin, A., and Hoffman, R.R. (Eds.) (2018). Remote sensing and cognition: Human factors in image interpretation. Boca Raton, FL: CRC Press.

Hoffman, R.R., et al.  (2017). Minding the weather: How expert forecasters think.  Cambridge, MA: MIT Press.

Hoffman, R.R. and Smith, P. (2017). Cognitive Systems Engineering: The Future for a Changing World. Boca Raton, FL: Taylor & Francis.

Hoffman, R.R., et al. (2014). Accelerated Expertise: Training for High Proficiency in a Complex World. Boca Raton, FL: Taylor and Francis/CRC Press.

Hoffman, R.R. (Au., Ed.) (2012). Collected Essays on Human-Centered Computing, 2001-2011. New York: IEEE Computer Society Press.

Hoffman, R.R. and Militello, L.G. (2008). Perspectives on Cognitive Task Analysis: Historical Origins and Modern Communities of Practice. Boca Raton, FL: Taylor and Francis.

Crandall, B., Klein, G., and Hoffman R.R. (2006). Working Minds: A Practitioner’s Guide to Cognitive Task Analysis.  Cambridge, MA: MIT Press.

Selected Recent Publications

Hoffman, R.R., Jalaeian, M., Tate, C., Klein, G., & Mueller, S .T. (2023, May). Evaluating machine-generated explanations: A “Scorecard” method for AI measurement science. Frontiers in Computer Science, 5.[]

Hoffman, R.R., Mueller, S.T., Klein, G., Jalaeian, M., & Tate, C. (2023, August). Explainable AI: roles and stakeholders, desirements and challenges.  Frontiers in Computer Science, 5. []

Klein, G., Hoffman, R.R., Clancey, W.J., Muller, S.Y., Jentsch, F., and Jalaeian, M. (2023). “Minimum Necessary Rigor” in empirically evaluating human-AI work systems.  The AI Magazine. [ ]

Hoffman, R.R., Miller, T. Klein, G.,. Mueller, C.T. and Clancey, W.J. (2023). Increasing the value of XAI for users: A psychological perspective. Kunstliche Intelligenz. []

Hoffman, R.R., Jalaeian, M., Tate, C., Klein, G., & Mueller, S .T. (2023, May). Evaluating machine-generated explanations: A “Scorecard” method for AI measurement science. Frontiers in Computer Science, 5[]

Hoffman, R.R., Mueller, S.T., Klein, G. & Litman, J. (2023). Measures for explainable AI: Explanation goodness, user satisfaction, mental models, curiosity, trust, and human-AI performance. Frontiers in Computer Science.[]

Trent, S., Hoffman, R.R., Merritt, D., & Smith, S.J. (2019, Spring). Modelling the cognitive work of Cyber Protection Teams. Cyber Defense Review, 4 (1), 125-138.

Hoffman, R.R. (2019, Spring). The Concept of a “Campaign of Experimentation” for cyber operations. Cyber Defense Review, 4 (1),75-84.

Hoffman, R.R., Miller, T. & Clancey, W.J. (2022). Psychology and AI at a crossroads: How might complex systems explain themselves? American Journal of Psychology, 135, 365-378.

Hoffman, R.R. & Johnson, M. (2019). The quest for alternatives to “Levels of Automation” and “Task Allocation.” In M. Mouloua & P.A. Hancock (Eds.) Human performance in automated and autonomous systems (pp. 43-68). Boca Raton, FL: CRC Press.

Hoffman, R.R., Mueller, T., Mueller, S.T., Klein, G., and Clancey, W.J. (2018, May/June). Explaining Explanation Part 4: A Deep Dive on Deep Nets. IEEE: Intelligent Systems, pp. 87-95.

Hoffman, R.R., Mueller, S. T., and Klein, G. (2017, July/August). Explaining Explanation, Part 2: Empirical Foundations. IEEE Intelligent Systems, pp. 78-86.

Hoffman, R.R., and Klein, G. (2017, May/June). Explaining Explanation, Part 1: Theoretical

Foundations. IEEE Intelligent Systems, pp. 68-73.

Hoffman, R.R. and Hancock, P.A. (2017). Measuring resilience.  Human Factors, 59, 564-581.

McBride, N., and Hoffman, R.R. (2016, September/October). Bridging the ethical gap: From human principles to robot instructions. IEEE Intelligent Systems, pp. 76-82.

Bunch, L., Bradshaw, J.M., Hoffman, R.R., and Johnson, M. (May/June 2015) Principles for human-centered interaction design, Part 2: Can humans and machines think together? IEEE: Intelligent Systems, pp. 68-75.

Bradshaw, J.M., Hoffman, R.R., Johnson, M., and Woods, D.D. (2013, May/June). The seven deadly myths of  “autonomous systems.”  IEEE: Intelligent Systems, pp. 54-61.