The Computer Science of Human Decision Making | Tom Griffiths | TEDxSydney
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- čas přidán 31. 07. 2017
- If you have ever been wracked with indecision over seemingly simple tasks, such as what clothes to wear that day or which restaurant to choose for dinner, then Cognitive and Computer Scientist, Tom Griffiths has the solution - there’s an algorithm for that. In this talk, he offers practical solutions to problems as well as a different way to think about rational decision-making and argues that human choices can be made easier with computer science.
Tom Griffiths is a Professor of Psychology and Cognitive Science at the University of California, Berkeley, where he is also the Director of the Institute of Cognitive and Brain Sciences. His research explores connections between human and machine learning, using ideas from statistics and artificial intelligence to understand how people solve the challenging computational problems they encounter in everyday life.
Tom was an undergraduate at the University of Western Australia, completed his PhD in Psychology at Stanford University in 2005, and taught at Brown University before moving to Berkeley. He has received early career awards for his research from the United States National Science Foundation, the Sloan Foundation, the Society for Mathematical Psychology, the Society for Experimental Psychology, the Association for Psychological Science, and the American Psychological Association.
In 2016, Tom and his friend and collaborator Brian Christian published _Algorithms to live by_, introducing ideas from computer science and cognitive science to a general audience and illustrating how they can be applied to human decision-making. The book was named as one of the Amazon.com “Best Science Books of 2016,” the Forbes “Must-read brain books of 2016,” and the MIT Technology Review “Best books of 2016.”
This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at www.ted.com/tedx
I have always said my desk is perfectly organized to me. Nice to be validated 😁
Deserves more views
You can't control outcome. As long as you have used the best process, you have done the best that you can. These are the concessions that we make when we are not rational, they are rational means
Amen. You can't control outcome.👍❤️
Computer science can help to make us more forgiving of our own limitations
A good book
So if you gonna live for 70 years, you take 37% of your lifetime to make ultimate life roadmap,
it should be around 26 years old
I am going to live for a minimum 200 years and then be a god of my own Metaverse
Good, I too plan to live over 100.
GOOD
You fail most of the time (37%), but that's the best you can do -- optimal strategy
Tough Crowd
It's been five, oh hear I'm watching it on 8th January 2023.
I like how something about Computer Science had 1337 likes, but I just killed that fact and I feel sorry abou that! 😥
But these are assumptions which doesn't consider the complexity of change of human will and feelings or changes in mental states whether by an individual or the person they are interacting with. You might choose a good restaurant based on algorithm but on the day you go to said restaurant another customer insults you and ruins the experience, you only had one chance to go to that restaurant and now your experience of the restaurant is not that great.
He claims that if you were searching for 30 days, that you are ready to act after 11 days but what set that initial search time of 30 days? I don't think the 37% works for time like it does for searching through all options.
This was exactly my thought. In some situations there is a time constraint but what about other times? How do we set the constraint parameters? It would be interesting to hear some techniques about this as well.
We do have initial time constraint in everything we do. For example, 30 years is my initial time constrain from now if I want a house when I’m retired. Hence using the 37% rule, I can spend 11 years to search before decides on a house from 12th years onward for the best among what I’d searched for previous 11 years. This idea helps to optimise to get the highest ratio of input and output, but not for perfection. I’m currently reading the book and it helps me to understand a lot.
Google pay makes it simple to collect all your banking information to monitor your transactions to better predict and sell you what google wants and it’s partners 😃
should not have read this book. most boring book i ve ever read.
😂 🔥🔥
You simply lack understanding
currently reading this book, what makes you think it's boring? is it
I find it boring too. Lack of examples
I managed to get over his boring tone until he made that unpleasant joke about being old and worthless,
Try to pray lord shiva 😀
I was trying to actually learn something.
I just watched this entire video babbling, “ problems problems problems, you can problems problems problems, try problems problems, and then problems problems, failed relationship problems problems problems, math isn’t problems problems.”