A Tribute to Daniel Kahneman: Three Things I Learned from Danny

A tribute to Daniel Kahneman: Three things I learned from Danny.

I met Danny in the summer of 1999. He was Daniel Kahneman to me then. I was a PhD student at Ohio State University working with Barbara Mellers. She had known Danny from their time at UC Berkeley. At the time, he was a professor at Princeton University. However, he would spend his summers in Berkeley, where he and his wife, Anne, maintained a residence.

He was on a tight deadline preparing a couple of chapters for Choices, Values, and Frames, his edited book with Amos Tversky, which was to be published the following year. Because he was away from Princeton, he did not have his typical research assistance. So he asked Barb if she knew a grad student who could help.

She volunteered me.

I remember the next part very distinctly: Barb sat me down and said, “You can ignore all the work that we’re doing. Just help Danny. He’s a genius.”

I helped him edit those chapters. (We will return to them shortly.) Three years later, I finished my PhD in what is now known as behavioral economics. After striking out on the job market, I emailed him and said I was interested in the post doc. I asked if it was available. He wrote back, “It’s yours.”

I arrived on the Princeton campus in August of 2002. We went to have lunch that day to talk about research ideas. He pitched me some project ideas, and I picked one on loss aversion. (We will return to that paper later.)

A week later, Danny won the Nobel Prize in economics. I jokingly reminded him that prior to my arrival on campus, he had no Nobel Prize. I spent two wonderful years at Princeton, which set me up for my current position as a professor at the University of Colorado Boulder.

I was reflecting on Danny’s passing yesterday and thinking about what I learned from the opportunity to  interact closely with him. Obviously, his research has influenced many, many people. But here are three personal observations you may appreciate.

“Easy reading is hard writing.” While Nathaniel Hawthorne said that, Danny embodied it. When you read his wonderful writing, it is easy to think, “Wow, he has talent.” Yes, Danny was a talented writer, but his secret was his persistence.

During that summer in ’99 as I was assisting with that deadline, I got to work with him up close on the editing process. We would spend hours sitting in his living room, each of us had a laptop taking turns reading passages out loud. At the end of a passage, I would often say, “Sounds good. Makes sense.” He would say, “No, it’s terrible.” and rewrite it in front of me. Upon reading it out loud again, I would reply, “Oh, yeah, it’s better.” And he would often say, “No, not good enough.” And rewrite it. This may go on a couple more times, with each iteration making the writing a little bit better.

He was in his mid-sixties. I was in my late twenties. He wore me out. At the end of the session, I was exhausted.

Consistent with this anecdote, there is lore in the academic community that Danny and Amos Tversky debated each word in their now famous 1979 Econometrica paper. If you know this to be true or not, please let me know.

Personally, it took me many years to get serious about my writing. As I was struggling to get better, I would harken back to those days as solace.

“Naming things is important.” Danny said that to me offhandedly, one day while chatting in his office.

At the time, there were two competing ideas in the literature. One which was based on work by Tim Wilson and Dan Gilbert was called “affective forecasting.” The other was the “focusing illusion,” which he published with David Schkade (and others). In hindsight, it is easy to see which was better received.

Regarding taking his own advice, I would give Danny mixed grades. Unless you are super into behavioral econ, “prospect theory” doesn’t make a lot of sense. “Loss aversion,” on the other hand, is a winner.

I kept that idea in mind when I was forming a lab to study humor. It took just a little extra time, but when I landed on the “The Humor Research Lab”—or “HuRL”—I knew I had a winner. That name created extra media attention that helped get the word out about this ambitious project to crack the humor code.

“Welcome Type II error.” This final lesson has to do with his approach to scholarship. Danny’s citation count is incredible. However, he was not uber productive. One reason was that Danny was hard on ideas. While many scholars are super hard on ideas because they just like criticizing for the sake of criticizing, he was so hard on ideas to make sure they  were right.

Type I error occurs when a true null hypothesis is incorrectly rejected, essentially finding a false positive. For example, concluding that a new medication is effective when it is not. Type II error happens when a false null hypothesis is incorrectly accepted, leading to a false negative, such as concluding that a medication is ineffective when it actually works. Danny’s rigorous approach to research aimed to minimize Type I errors, even at the cost of potentially committing more Type II errors.

For a young scholar, the inclination towards committing a Type I error might stem from the pressure to produce significant results. Achieving statistically significant outcomes can accelerate the publication process and enhance career prospects. This incentive aligns with the publish-or-perish culture in academia.

In contrast to this common inclination, I learned that in the long run, you want to embrace Type II errors—finding effects that stand the test of time. Working with Danny, I realized that he was so hard on ideas that he committed almost no Type I errors, but lots of Type II errors. That is, he rarely ever published a paper that was wrong, but he failed to publish lots of other ideas that would likely have been right.

To give you a sense of how hard he could be on ideas with the goal of getting things right, the paper that we started in August of 2002 took nine years and two additional co-authors to get published. Yet, I am confident that those effects will stand up to scrutiny from researchers attempting to replicate the findings, often referred to as the “replicability police.”

In closing this tribute, I have a lot of affection for Danny. He was tough on ideas and not always a warm personality, but he was kind to me. In particular, I appreciate his thoughtfulness in helping me with the transition from psychology to working as a marketing professor. I remember how happy he was for me when I got the job at the University of Colorado Boulder.

Danny was also generous with me. As we were settling into a collaboration, he had just won the Nobel Prize in economics—yet he let me share an office with him for two years. I had been offered a pretty terrible office, and rather than have me take a better office in an adjacent building, he said, “Well, I’m not in the office much. If you tidy up here, you can make yourself at home. And when I have a meeting here or there, you can just leave. It’ll give us a chance to make sure we get to work closely together.”

What a glorious opportunity to be able to share an office at this exciting time in his life. The opportunity to “tidy up” his office was fascinating. His office was filled with papers from many, many years. I went through all of them and created three piles. One was a “no” pile, to be recycled. The other was a “maybe” pile with papers that I could not tell if he wanted or not. (He had to go through them but never did–probably because “maybe” means “no.”)

There was a final pile–a “yes” pile. One of the very cool things that was in the “yes” pile, that the behavioral economists can appreciate, were original preprints of the 1979 Prospect Theory paper in Econometrica.

If I went through my files, I have a hunch that somewhere in there would be a folder labeled “Kahneman.” In that folder would be a 1979 pre-print of that important paper–a paper that serves as a lovely reminder of his contributions and supportiveness.

Thank you, Danny.


Peter McGraw