(I could be wrong and would be happy to be proven so. Just not a fan of the all-or-nothing attitude people apply toward this book when that doesn't seem warranted.)
(I could be wrong and would be happy to be proven so. Just not a fan of the all-or-nothing attitude people apply toward this book when that doesn't seem warranted.)
Besides, why go through all that trouble if there are heaps of good psychology books out there that aren't plagued with errors as this one? Since our time is so limited, I think it is a good heuristic to avoid any non-fiction book that it is known to contain errors.
That's kind of the same problem that a psychology researcher faces; some of their data is going to be wrong.
The question winds-up being how "robust" your claim is, can you survive having some points being wrong? For Thinking Slow And Fast, the robustness of the claims is kind of a mixed bag imo.
All of psychology has suffered in the replication crisis, but my understanding is that Kahneman & Tversky's stuff is better than most. Their work was mostly solid and in a different era. The real bullshit began in the era of celebrities doing TED talks.
Edit it would be better for me to distinguish Kahneman & Tversky's own work from the work of others described in the book. Eg there is stuff in the book on priming which is definitely TED-era and doesn't replicate.
However, I don't think this justifies dismissing the entire book. "I'm not sure which studies weren't reproducible and I don't feel like looking them up," is a very different statement than, "This whole book is bullshit." There's really no reason to make that latter overstatement.
If you take with the first implication, it's plausible, useful as one more datum. But it seems like replication problems make the hard distinction approach more problematic.
I've yet to read the book, but I've listened to him on several podcasts, and I've never gotten the sense that he wouldn't see it as a continuum, didn't he even say something early in the interview that the "1 & 2" is more of a metaphor? (his answer to that question starts at 9:00). System 1 is trainable, for example, and I can't imagine he'd suggest that isn't highly dimensional.