Hacker News new | past | comments | ask | show | jobs | submit login

Intuitive argument against suggestions that Ariely might have faked the data... It seems unlikely to me that someone of Ariely's mathematical knowledge and research experience would fake data in such an obvious manner.

(Full disclosure: I've met with Ariely a couple times, 20 years ago, about cross-disciplinary research, and have a favorable impression of his character.)




This seems like a "It's too obvious" defense. I tend to think that very obvious explanations are usually right. Besides, contrary to the fraud being too obvious, it went undetected for a decade.

From what I can tell the data was faked by Ariely or the insurance company. Why would the insurance company fake data to support Ariely's hypothesis? What do they gain from that? Presumably, the insurance company is trying to find interventions to make customers behave more honestly - faking data to get spurious answers seems counter productive.

Ariely on the other hand has clear benefits from faking the data. He has the means, motive, and opportunity. On top of that, there's no other plausible suspect.


What sounds obvious (from how it was described in one of the articles) is that the data is fake. And that someone fabricated data that anyone who hadn't slept through the first day of Stats 101 would understand is fake data.

If I'm being creative for a moment, I can totally imagine a few other plausible scenarios, which also seem more likely than Ariely knowingly publishing obviously fake data.

I'm not going to mention those scenarios, because, in the kind of court of public opinion/speculation like we're seeing even in this very HN post, people are effectively convicted and executed upon speculation.

These are real people, consider they might be innocent, and therefore treat them as we'd like to be treated, were we innocent yet suddenly fell into the crosshairs of the Twittersphere loose canons.




Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: