Larry Lessig should really stop speaking to the press. He routinely says things as bafflingly ridiculous as this. https://www.newyorker.com/magazine/2023/10/09/they-studied-dishonesty-was-their-work-a-lie “Trust me” is one of the biggest red flags you can ever utter.
All these Ariely stories remind me of the Innovator’s Dilemma guy, Clayton Christensen. He has his whole story about milkshakes, doing a job for truckers that has been told and retold in varying watts, and doesn’t seem to be based on reality. Nobody’s ever called him out for it. All of these behavioralists who consult seem to me to be myth makers.
Completely unrelated, I used to work alongside several pathological liars (either 2 or 4, depending on definitions; all 4 were liars), and you get to know the tells really really well. No story is ever told the same way twice even to the same person. When questioned, the teller comes up with an entirely different explanation instead of ever admitting the thing didn’t happen.
Listen, I was once friends with Mike Daisey. When shit came out, I was not “No, despite all evidence, Mike is absolutely an honest person,” because, you know, he was not. (In fact, when he started talking about Chinese manufacturing, I had a distinct whiff of ordure.)
One of the most remarkable things to me about all these studies that turn out to have misused data, etc., is that most researchers apparently keep incredibly poor records; there's no audit history for changes; Excel is somehow the gold standard. I guess that's true in business, but I somehow thought there would be university, journal, and professional standards that required very specific one-way archiving of data, etc.
@glennf FYI, check out the RSE movement, Research Software Engineer(s|ing) an attempt to make research software and data more controlled. Too much software used in research is used once, then lost when it comes time to review. Or researchers leave an organisation and the data is orphaned.

@mattw @glennf

Even in industry, there are a lot of "researchers" who build prototype systems in unsustainable, irreproducible ways and then move on to the next new shiny without investing in reproducible builds, testing, or instrumentation,

leaving UX, QA, reliability and maintenance engineers to wonder "how did this ever work?"

@trochee @glennf True enough. IT is a bit ripe for abuse. Too expensive to do properly when starting up, then 5 years later your company accounts are still done from an Excel spreadsheet that’s “too hard” to replace with something else.