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Thinking Fast and Slow, Deep Learning, and AI [video]

lexfridman.com

11–20 of 104 posts

Re: Thinking Fast and Slow, Deep Learning, and AI [video]

#11

The few times I've tried to read Kahneman's book I must admit that I stopped pretty early. I found his writing style too authoritative, without presenting much evidence for the theories he lays out.

And you're well served with this response, as the actual work he did is basically not reproducible. No matter how many best selling books made into movies; it's still bullshit. https://replicationindex.com/category/thinking-fast-and-slow... https://slate.com/technology/2016/12/kahneman-and-tversky-re... https://jasoncollins.blog/2016/06/29/re-reading-kahnemans-th... I read it on advice of a good pal, and it sure seem…

Add to that list "grit" and "fixed vs. growth mindset" -- has any solid, interesting work in sociology or behavioral science been done recently?

Re: Thinking Fast and Slow, Deep Learning, and AI [video]

#12
post #7
post #6

The quality of the guests is amazing but the host is extremely off-putting and difficult to listen to.

Those are very strong words. Why?

The deadpan delivery and lack of personality, the arrogant attitude, the poor quality of the questions that he asks, the fact that he reads questions from a sheet in front of him instead of listening to his guests and having a real conversation with them, the way in which he comes across as disingenuous in most interactions... I could go on (and I know that a lot of this is subjective).

Re: Thinking Fast and Slow, Deep Learning, and AI [video]

#14

The few times I've tried to read Kahneman's book I must admit that I stopped pretty early. I found his writing style too authoritative, without presenting much evidence for the theories he lays out.

And you're well served with this response, as the actual work he did is basically not reproducible. No matter how many best selling books made into movies; it's still bullshit. https://replicationindex.com/category/thinking-fast-and-slow... https://slate.com/technology/2016/12/kahneman-and-tversky-re... https://jasoncollins.blog/2016/06/29/re-reading-kahnemans-th... I read it on advice of a good pal, and it sure seem…

As far as I understand it, only a small part of his book is based on distrusted research (and was that even his work or did he just write it up? Cannot remember).

Most of the book is still considered correct.

Plus, he readily admitted to the faulty parts and made a very strong request to the affected research teams to clean up their act and pretty much re-do all experiments multiple times, by multiple labs, with external oversight.

Re: Thinking Fast and Slow, Deep Learning, and AI [video]

#15

The few times I've tried to read Kahneman's book I must admit that I stopped pretty early. I found his writing style too authoritative, without presenting much evidence for the theories he lays out.

I can see where you might feel this way. I recommend giving it another try and come at from two considerations. The first is observing their experimental designs. They are very clever and well described. The second is the extent to which these experiments have been replicated with consistent results using populations with a range of socioeconomic and cultural differences.

Given the consistency of these experimental outcomes, may help to explain his authoritative tone. After all, he won a Nobel prize in economics which is completely outside his domain expertise.

If that is not enough to entice you to give it another go, consider the book, The Undoing Project, by Michael Lewis. Lewis, in his highly researched and using detailed anecdotes describes how Kahnemans and Tversky collaboration initially began as a collaboration around understanding the decision making process in circumstances where there is a high degree of uncertainty and acquiring additional information is not feasible. The Khanamen/Tversky collaboration is described as a deep collaboration where neither man claims credit for their respective contributions. Only both minds together could have produced their research findings.

Lewis also describes how many reviewers of his book, Moneyball, expressed the many parallels between Kahnemans/Tversky's research and themes covered in Moneyball. Lewis was not familiar with this research when he wrote Moneyball. It was not until others pointed out these parallels that Lewis decided he should engage with Kahneman to write The Undoing Project.

Re: Thinking Fast and Slow, Deep Learning, and AI [video]

#16
post #6

The quality of the guests is amazing but the host is extremely off-putting and difficult to listen to.

I find that Lex often side-steps technical depth and wanders into the philosophical side of things. He has the opportunity to ask diving questions but he simply scratches the surface with nearly every guest. It's not entirely his fault, he's under time constraints but I'd hope for more intellectual stimulation. That said, I do appreciate his efforts and he seems like a genuinely nice fella.

Re: Thinking Fast and Slow, Deep Learning, and AI [video]

#17

The few times I've tried to read Kahneman's book I must admit that I stopped pretty early. I found his writing style too authoritative, without presenting much evidence for the theories he lays out.

And you're well served with this response, as the actual work he did is basically not reproducible. No matter how many best selling books made into movies; it's still bullshit. https://replicationindex.com/category/thinking-fast-and-slow... https://slate.com/technology/2016/12/kahneman-and-tversky-re... https://jasoncollins.blog/2016/06/29/re-reading-kahnemans-th... I read it on advice of a good pal, and it sure seem…

This is a book that really, really needs a second edition.

Re: Thinking Fast and Slow, Deep Learning, and AI [video]

#18
post #14

Earlier quoted context omitted.

And you're well served with this response, as the actual work he did is basically not reproducible. No matter how many best selling books made into movies; it's still bullshit. https://replicationindex.com/category/thinking-fast-and-slow... https://slate.com/technology/2016/12/kahneman-and-tversky-re... https://jasoncollins.blog/2016/06/29/re-reading-kahnemans-th... I read it on advice of a good pal, and it sure seem…

As far as I understand it, only a small part of his book is based on distrusted research (and was that even his work or did he just write it up? Cannot remember). Most of the book is still considered correct. Plus, he readily admitted to the faulty parts and made a very strong request to the affected research teams to clean up their act and pretty much re-do all experiments multiple times, by multiple labs, with exte…

The things Kahneman worked on himself all did pretty well out of the replication crisis as far as I can tell. The fact that his findings got so much pushback when introduced probably helped a lot with making them more rigorous. And Kahneman didn't dig in his heels when the crisis hit. But there is an awful lots of stuff that needs to be expunged from his book because it was based on what turned out to be bad science.

Re: Thinking Fast and Slow, Deep Learning, and AI [video]

#19
post #6

The quality of the guests is amazing but the host is extremely off-putting and difficult to listen to.

Interesting, I find Lex to be one of the best podcast hosts I've listened to. I like his mix of philosophical and technical conversation. Most of his guests seem to genuinely enjoy and engage in the conversation.

Re: Thinking Fast and Slow, Deep Learning, and AI [video]

#20
post #16
post #6

The quality of the guests is amazing but the host is extremely off-putting and difficult to listen to.

I find that Lex often side-steps technical depth and wanders into the philosophical side of things. He has the opportunity to ask diving questions but he simply scratches the surface with nearly every guest. It's not entirely his fault, he's under time constraints but I'd hope for more intellectual stimulation. That said, I do appreciate his efforts and he seems like a genuinely nice fella.

Yeah I have an issue with that as well. He gets some great guests on the show and spends most of the time pushing a philosophical debate about AGI and futurism instead of letting the guests talk about their areas of expertise. I'd even argue that it's dangerous because it might give the casual listener an impression that ML/AI is much further ahead than it really is if all of these top minds are discussing AGI.

I'd much rather hear LeCun, Goodfellow, Schmidhuber and Bengio talk about what they're currently working on and where they think the field will go in the next year or two instead of their wild guesses about AGI. I guess the futurism crowd is much larger audience though.

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