RONALD A. HOWARD (1934-2024)

BY ROSS D. SHACHTER AND STEPHEN L. DERBY
SUBMITTED BY THE NAE HOME SECRETARY

RONALD ARTHUR HOWARD, a pioneer in decision analysis theory and practice, died Oct. 6, 2024, at age 90. Ron was professor emeritus of management science and engineering at Stanford University when he retired in 2014 at age 80 after 49 years on the Stanford faculty, though he continued teaching for several more years.

Born in Brooklyn, New York, on Aug. 27, 1934, Ron was the son of William M. and Susan Howard, immigrants from Northern Ireland. He attended the Massachusetts Institute of Technology (MIT) on a Grumman scholarship, earning bachelor’s degrees in economics and electrical engineering in 1955. He worked with George E. Kimball and Philip M. Morse (NAE 1985) to earn an Sc.D. in electrical engineering, with a minor in mathematics, from MIT in 1958. Upon graduation, he joined the MIT faculty, earning tenure in the electrical engineering department and the Sloan School of Management in 1962.

Ron’s dissertation was published as a monograph, Dynamic Programming and Markov Processes (MIT Press, 1960). He expanded on that work with a two-volume textbook,¹ Dynamic Probabilistic Systems, focusing on Markov decision processes, dynamic programming, and methods for decision-making under uncertainty. Those contributions continue to be cited, forming the theoretical foundations for state-of-the-art research in artificial intelligence and reinforcement learning.

In 1964, at the urging of William Linvill (NAE 1979), a former mentor from MIT, Ron became a visiting professor at Stanford. He remained there and became a professor in 1965. He helped found the Department of Engineering-Economic Systems, one of three departments that merged into the Management Science and Engineering Department in 2000.

Ron and Howard Raiffa (NAE 2005) spearheaded an academic effort in the 1960s to apply the theories of games, decisions, and Bayesian probability to normative decision-making under uncertainty for individuals and organizations. His 1966 papers, “Decision Analysis: Applied Decision Theory”² and “Information Value Theory,”³ and his 1968 paper, “Foundations of Decision Analysis,”⁴ defined the field as it is known today. Initially considering the term “decision engineering,” he chose “decision analysis” to avoid any connotation of manipulation.

In 1966, Ron created the Decision Analysis Group at Stanford Research Institute International, which later became the Strategic Decisions Group in 1980, where he served as founding director and chairman. As an effective counselor to decision-makers, he earned their trust by developing concepts, tools, and terminology to enable the practical use of decision analysis. Many of his past colleagues and students continue those practices today.

A major innovation in professional practice was the influence diagram, a compact graphical representation of decision problems that he introduced with his friend and colleague, James Matheson.⁵ Influence diagrams improved communication about complex decisions in organizations and inspired the development of Bayesian belief networks, widely used in managing uncertainty in artificial intelligence.⁶

Ron’s work also extended into the ethics of decision-making. After being asked by a client to manipulate an analysis, he began exploring the moral responsibilities associated with advising others, culminating in a course and a co-authored textbook with Clint Korver, Ethics for the Real World.⁷

His ethics research inspired his analysis of life-and-death decisions, leading him to introduce the concept of the “micromort value,” which quantifies the tradeoff between money and a one-in-a-million chance of dying.⁸ This innovation transformed the focus of economic analysis from estimating the cost of lives lost in the future to determining the present value of imposed risk so those threats can be reduced today.

Ron served as president of the Institute for Management Science in 1967. The Decision Analysis Society awarded him the Frank P. Ramsey Medal for distinguished contributions in decision analysis in 1986. In 1998, the Institute for Operations Research and the Management Sciences (INFORMS) honored him as the inaugural recipient of the Prize for the Teaching of the OR/MS Practice.

His most enduring legacy lies in his teaching, textbooks, seminal papers, and mentorship of more than 100 Ph.D. students, along with tens of thousands of graduate students who fondly recall his probability and decision analysis courses, where he combined engineering mathematics with philosophy. Known for his Socratic teaching method, he inspired students to embrace uncertainty as an opportunity rather than a threat. His decision analysis teachings are captured in his textbook, Foundations of Decision Analysis (Pearson, 2015), co-authored with Ali Abbas.

Ron’s contributions to decision analysis continue to influence the field, guiding researchers and practitioners in making better decisions under uncertainty.

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¹Howard RA. 1971. Dynamic Probabilistic Systems, Volume I: Markov Models. Dynamic Probabilistic Systems, Volume II: Semi-Markov and Decision Processes. John Wiley and Sons.
²Howard RA. 1966. Decision Analysis: Applied Decision Theory. Stanford Research Institute.
³Howard RA. 1966. Information value theory. IEEE Trans. Systems Science and Cybernetics 2(1):22-26.
⁴Howard RA. 1968. The foundations of decision analysis. IEEE Transactions on Systems Science and Cybernetics 4(3):211-19.
⁵Howard, RA, Matheson JE. 2005. Influence diagrams. Decision Analysis 2(3):127-43.
⁶Howard, RA, Matheson JE. 2005. Influence diagrams. Decision Analysis 2(3):127-43.
⁷Howard RA, Korver CD. 2008. Ethics for the Real World: Creating a Personal Code to Guide Decisions in Work and Life. Harvard Business Review Press.
⁸Howard RA. 1978. Life and Death Decision Analysis, Second Lawrence Symposium on Systems and Decision Sciences, Berkeley, California, Oct; Howard RA. 1984. On fates comparable to death. Management Science 30(4):407-22.