This week’s research hero is professor Paul Slovic. Prof. Slovic received his PhD from University of Michigan and has been one of the pioneers in methods to measure risk. He studies fundamental issues such as the influence of affect on judgments and decisions, the factors that underlie perceptions of risk. He has a large number of publications in not only the area of risk but also compassion and genocide. He is the founder and President of Decision Research, and has received numerous awards such as the Distinguished Scientific Contribution Award from the American Psychological Association.
I wish someone had told me at the beginning of my career… Actually, I’m very glad no one did tell me, when I took my first job at the Oregon Research Institute, how hard it would be to live off soft money from grants and contracts for close to 50 years. I might not have taken the job. Despite the challenges, I have no regrets.
I most admire academically… There are many JDMers who I very much admire, including the fine colleagues I have been fortunate to work with. But, like many others, I have a special admiration for Amos Tversky and Danny Kahneman. I always had an interest in applying JDM research to important societal problems and when Amos and Danny began to do their simple but elegant heuristics and biases studies of judgment under uncertainty, I immediately was motivated to extend their findings into the realm of what Sarah Lichtenstein, Baruch Fischhoff, and I later termed “societal risk taking”—in particular nuclear and chemical safety and finance. It was great fun exposing people from other disciplines to this fascinating and important behavioral research and I have continued doing this throughout my career.
My favorite research project… is always the one I’m working on at the moment. But, looking back on many favorites, I have a particular fondness for the preference-reversal studies done with Sarah Lichtenstein. They began serendipitously, when, as part of a larger study, we happened to compare two response modes for evaluating gambles and found they were highly inconsistent. This was only an incidental part of the study we were doing, but we took that finding and ran with it. We then had the exciting opportunity to replicate our research on the floor of the Four Queens Casino in Las Vegas. The results, demonstrating what was later called “a violation of procedure invariance,” greatly threatened and annoyed economists who believed pricing and choice should be equivalent indicators of preference. They launched numerous studies “to discredit the psychologists’ work as applied to economics.” They failed. Over time this research led us to a broader perspective that we named “the construction of preference”.
My worst project… I’ve conducted many studies, some were clunkers. A few that fizzled contained hidden gems (serendipity again), such as the one that evolved into the paper “Preference for Choosing Among Equally Valued Alternatives.” I had been trying hard to construct pairs of two-dimensional stimuli that were exactly equal in value to use in an experiment on context effects. But I found that, when testing for equality, there was always a strong and systemic preference for the option that was best on the more important dimension. So again I took this failure and ran with it (slowly; it took 17 years to come to fruition). Amos Tversky and Shmuel Sattath nicely enhanced my serendipitous findings when they used them as a springboard to “the prominence effect.”
Most memorable experience… Watching Ward Edwards try to impress the manager of the Four Queens Casino in Las Vegas regarding the studies we wanted to run on the casino floor. Ward had a notebook of gamble pairs, simulating an experiment we planned to run on a computer. “Which of these two (very different) gambles would you prefer to play?” asked Ward.
“I’ll take A,” said the casino boss.
“But you didn’t even look at the gambles,” responded Ward, with a mixture of surprise and annoyance.
“I feel lucky with A,” was the reply. Another pair was offered—again an instant choice of A. “I won with A last time, so I went with A again,” was the explanation. So much for rational weighting of probabilities and payoffs by a man in charge of a major gambling enterprise. The manager was not impressed with us academics either, but we were allowed to take up valuable floor space and run several experiments. Despite having no “house advantage”, they were the most unpopular games in the casino because they required players to think and make tradeoffs among the dimensions of gambles.
If I were not doing this… I would be a human-rights activist. There seems no end to the abuses of human beings being perpetrated around the world. And I have come to see that JDM research has relevance for motivating people to care about helping others and for designing procedures, laws, and institutions to aggressively address these abuses when compassion fatigue sets in. I’m working at this now but I wish I were better prepared to employ JDM findings to stop human-rights violations.
The biggest challenge facing the field in the next decade is… maintaining its identity in the face of the ever-increasing fragmentation of disciplines. Will it become subsumed under “behavioral economics”? I hope not. I would not like to see JDM subsumed under behavioral economics because JDM is applicable to all human judgment and decision contexts and is thus broader in scope than economics. Also, in my opinion, psychology is at the core of JDM and I would not like to see that perspective diminished. Another challenge is to demonstrate the centrality of JDM research for yet another emerging discipline, “behavioral public policy” (see, e.g., Eldar Shafir’s new book on that topic).
My advice for young researchers is… run experiments and collect data. Don’t feel you necessarily need an elegant theory or well-identified hypothesis before you can do a study. Having a good question to answer is enough to motivate a study. I have found that collecting and analyzing data is an aid to thinking about a problem. New insights often emerge that one might have come to by thinking hard, but instead emerged from puzzling over data. Theoretical development and hypothesis testing can then take root from those insights. And be alert for incidental findings that may be even more important than what you were originally looking for.