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1/ I beg to differ. For readers interested in my unbiased opinion, this review is ill-informed, ill-motivated and misleading. Bent on showing that "there is more to it than #Bookofwhy", sweating hard and unsuccessfully to find any such "more to it", the reviewers neglect to tell
2/ readers what they would miss not reading the book. The quote: "causal inquiry cannot be reduced to a mathematical exercise nor automatized." is truly indicative of the occult "more to it" agenda of the review, and its failure to appreciate how much has been automated already.
3/ Another unbiased opinion I have regarding "the particular value of randomized experiments". I challenge anyone to show me a clearer/deeper exposition of RCTs and their "particular value" than that given in #Bookofwhy ch. 4, The Skillful Interrogation of Nature, Why RCTs Work?
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Judea Pearl
@yudapearl
1/ I'm glad, Sean, that our brief exchange has resulted in your great clarification of the issues, from which I have learned a lot. Two thoughts come immediately to mind: (1) It is a blessing that we can enjoy a division of labor between CI and statistics, the former generates
2/ causal estimands, the latter estimate them. Note though that the former is not totally oblivious to the type of data available. Different types of data will result in different estimands. eg.,experimental vs. observational, corrupted by missingness or by proxies or by
3/ differential selection etc. (2) I don't buy the mystification of "collecting adequate data". I am in the business of automating a scientist, so, if there is human judgement involved in the data collection task, we do not stop here and surrender it to humans. We see it as an
Read 4 tweets
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Judea Pearl
@yudapearl
1/ Legality aside, I would assess how likely I am to encounter a complication never seen by the AI surgeon, which a human surgeon can handle through her knowledge of anatomy. It actually happened to me, when a famous surgeon quoted us 90% success record but, when asked
2/ how many cases like THAT have you seen? He said: "None. I have never seen a lung as bad a lung as this." We cancelled the surgery, and my wife is still alive. Remarkably, counterfactual logic permits us to bound the probability that a given patient will benefit from a given
3/ treatment, once we have a combination of both experimental and observational data. See tight bounds on PNS (prob. of necessary and sufficient causation) in ucla.in/2Nfphba. Thus, smart ML algorithms will be able to tell a patient how trustworthy they are. #Bookofwhy
Read 3 tweets
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Judea Pearl
@yudapearl
I summarize this discussion thus: Progress in our
century amounts to building computational models of mental processes that have escaped scrutiny under slippery terms such as "design" "discovery" "background knowledge"
"familiarity" "fieldwork". etc. Saying "DAGs are not enough"
2/ produces no progress until one is prepared to propose a mathematical model for what IS enough. The IV criterion I presented is necessary for justification, so keep it in mind and teach it to natural experimentalists who should be jubilant seeing their IV's justified. 2/3
3/3 We should always be open to extensions and refinements, but mystification holds us back. We had enough of that in the 20th century. #Bookofwhy
Read 3 tweets

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Kevin G. Schmidt
@kevingschmidt
#OPINION

A thread on key findings within US House of Representives #CoronavirusStimulusBill
Read 14 tweets
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dcaffrey
@DCaff93
Ill be making a thread for class about this research done by @nytimes, here is the link docs.google.com/presentation/d… #kellyclass
The things we consume on a daily basis (podcasts, news stories, videos, tv shows, movies) all come with a bunch of recommendations. A never-ending stream of content vying for our attention. But nothing attracts consumers as well as real-life personal recommendations. #kellyclass
No amount of streaming content has the same online activity as scheduled programming. The conversation around weekly shows like "Game of Thrones" engages people who fear missing out. Shows available to binge don't connect people in the same way as scheduled showings. #kellyclass
Read 13 tweets
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Dimiter Toshkov
@DToshkov
I recently finished 'The Book of Why' by @yudapearl
I would highly recommend it to everyone interested in causality and scientific explanations. /THREAD
amzn.to/2OW9v0Q
#bookofwhy
The book is rather accessible, so you don't need to be a #causalinference nerd to follow the arguments. At the same time, there is a lot to learn even if you have struggled your way through Causality (CUP, 2009) and the technical papers
amzn.to/2OSmzEb
I have been an early converter and have used the 'structural' approach to causality to organize my own book on research design in political science.
Now I am glad I have an accessible book to point students to for more info and background.
amzn.to/2KfX3Iy
Read 10 tweets
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Pauli Ohukainen
@POhukainen
Thread alert! Atherosclerosis (official journal of @society_eas) publishes a #review on #TraditionalChineseMedicine (#TCM). It's simultaneously a bit frightening and hilarious (1/16)

atherosclerosis-journal.com/article/S0021-…
First of all, TCM is BS. It may have been useful thousands of years ago when nothing was known about science but nowadays we know better. Besides, "modern TCM" was pretty much invented by Chairman Mao in the 50's: slate.com/articles/healt… (2/16)
Look at this terrifying aim of the review! "WHAT IS NECESSARY FOR TCM TO SPREAD TO WESTERN SOCIETIES". Ideological bias, much? (3/16)
Read 16 tweets

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