M. Granger Morgan (March 17, 1941) is an American scientist, academic, and engineer who is the Hamerschlag University Professor of Engineering at Carnegie Mellon University. Over his career, Morgan has led the development of the area of engineering and public policy.

Early Life

While concentrating in physics at Harvard, Morgan became interested in a broad range of issues in history and social science, and spent the summer of his junior year doing data analysis at the Jicamarka Radio Observatory, outside of Lima, Peru, during which time he became deeply interested in issues of development in Latin America. After completing his MS in Astronomy and Space Science at Cornell, where he did field work at the Arecibo Ionospheric Observatory, he moved to the University of California at Berkeley where he began a graduate program in Latin American history. Concluding that he wanted a career in the area of technology and policy, and to continue his technical education, he became one of the first two PhD students to join Henry Booker’s newly established Department of Applied Electrophysics (now Electrical and Computer Engineering) at the University of California, San Diego. His UCSD thesis in applied physics and information science is titled A Laboratory Model for Radio Star Scintillation and Other Diffraction Phenomena. While completing the experimental work for his PhD he arranged a course on computers and programming for a group of underserved high school students who the neighborhood youth corps placed on campus for the summer. After graduation this experience led to his developing a program called Computer Jobs Through Training. Morgan also created an undergraduate course at UCSD in technology and public policy. In 1972 he moved to Washington to become a program officer in the NSF Office of Computer Research, building a new program on the social impacts of computing. While at NSF he also participated in work on energy. He left NSF in 1974 to continue work with Samuel Morris and others on energy issues at Brookhaven National Laboratory.

M. Granger Morgan

Career

Morgan was appointed as an Assistant Professor at Carnegie Mellon University in Electrical Engineering and Engineering and Public Policy (EPP) in 1974, with the charge of coordinating the development of EPP’s Graduate Program. He worked with Robert Dunlap and others to develop and obtain approval and funding for the PhD program in Engineering and Public Policy (EPP). The program has now graduated over 400 PhDs, all of whom came to the department with a background in science or engineering and pursued research on problems in technology and policy in which the technical details were important. EPP became an academic department in the engineering college at Carnegie Mellon University in 1976. Morgan became the founding Department Head and continued in that role through 2014, holding the position for 38 years.

M. Granger Morgan

Educated in applied physics, a field in which no result is published without a characterization of associated uncertainty, Morgan was dismayed to find that in the early 1970s this was not the norm in quantitative policy analysis. Through his work, initially on the health effects of coal-fired power plants and then on a variety of other topics in risk assessment, Morgan developed and demonstrated methods for characterizing and incorporating uncertainty in quantitative policy analysis. This work led to an extended collaboration with Max Henrion and the publication of the book Uncertainty: A guide to dealing with uncertainty in quantitative risk and policy analysis (Cambridge, 1990).

M. Granger Morgan

The 1980s saw growing concerns about improving risk communication. Working with economist Lester B. Lave and psychologist Baruch Fischhoff and a group of PhD students, they developed and demonstrated the mental model approach to risk communication. This work lead to the publication of the book Risk Communication: A mental models approach (Cambridge 2002). Morgan, Lave, Fischhoff and their PhD students then went on to develop and demonstrate a variety of methods to support systematic risk ranking.