Joshua Gans

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Joshua Gans

Joshua Gans

@joshgans

Professor at the Rotman School of Management, University of Toronto. Chief Economist of Creative Destruction Lab https://t.co/a9ZbnBauCF

Toronto, Ontario Katılım Kasım 2008
737 Takip Edilen18.9K Takipçiler
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Soumaya Keynes
Soumaya Keynes@SoumayaKeynes·
And one final chart shows that so far AI tools haven’t led to an explosion of submissions to several of the top 5 economics journals.
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Soumaya Keynes
Soumaya Keynes@SoumayaKeynes·
Note: I looked into whether this was an effect of economists talking about “artificial intelligence” more (long words) and it didn’t seem to be that. Though there has been an explosion in AI related terms as economists have caught the AI bug -
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Joshua Gans
Joshua Gans@joshgans·
Project Hail Mary was excellent.
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Joshua Gans
Joshua Gans@joshgans·
This oil price shock is likely to prove quite the EV promoter. Possibility more than the subsidies.
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Joshua Gans
Joshua Gans@joshgans·
Somehow, we glided past the 250th anniversary of The Wealth of Nations with no notice. I blame @tylercowen, who we rely on for these things.
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Joshua Gans
Joshua Gans@joshgans·
Why do we call AI agents "co-workers" when they are really slaves or, more politely, underlings?
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Kevin A. Bryan
Kevin A. Bryan@Afinetheorem·
Adaptive question ordering helps. So does "force students to explain to the tutor/AI what you're thinking when they get things wrong." This is exactly what we set up with @alldaytahelps's "Intelligent Quiz". It's such a sensible way to improve learning. 1/2
Ethan Mollick@emollick

AI really can help education: Randomized controlled experiment on high school students found a GPT-4o powered tutor that personalized problems for students raised final test scores by .15 SD, "equivalent to as much as six to nine months of additional schooling by some estimates"

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Jess Hoel
Jess Hoel@Jess_Hoel·
THIS is how AI can improve human cognition. Amazing. Totally going to do this in my next upper-level econ elective class. And in my own research right now!
Abdul Șhakoor@abxxai

I found a way to read a research paper the way academics actually read them. A friend of mine at Cambridge showed me her Claude workflow. I thought she was just fast. Then I watched her pull apart a methodology section in twenty minutes that her seminar group had spent a week discussing without fully understanding. Here's exactly what she did: First: she didn't ask Claude to summarise the paper. That's what everyone does. They paste in a paper and ask for a summary. They get a clean paragraph. They feel like they've read it. They move on. That's not reading. That's skimming with extra steps. She did something completely different. She read the paper herself first. All of it. Without Claude. Then she asked: "Based on the methodology and results sections alone, what can and cannot be legitimately concluded from this study? Now read the abstract and tell me where the authors overreach." She wasn't asking Claude to read the paper for her. She was using it to test whether the paper was actually saying what it claimed to be saying. The gap between those two things is where most students get lost. They read what the authors claim and treat it as what the authors found. An experienced academic never does that. She learned not to in twenty minutes. But the next part is what I keep thinking about. She asked: "What did this study not measure that would have significantly strengthened or weakened the central claim? What is the authors' methodology quietly assuming without ever stating it?" Most students read a methodology section to understand what the researchers did. She read it to find what they didn't do and what they hoped nobody would notice. Those are completely different acts of reading. One produces a student who can describe a study. The other produces a researcher who can evaluate one. Her seminar group spent a week on the same paper and never reached that question. Then she did something most students never think to do. She tested the paper against itself. "If I tried to replicate this study with a different population in a different context, what would most likely change about the results? What does that tell me about how far the authors' conclusions actually travel?" Most published claims are presented as general. Most are actually specific. That question finds the line between the two every time. Once you see it you cannot read a paper without looking for it. It changes what you take from every study you ever read after that. Then she mapped the paper's place in the conversation. She asked: "What debate is this paper entering? Who wrote the work this paper is responding to and what would those authors say back? Where does this paper sit in the argument that was already happening before it was written?" She stopped reading papers as standalone objects that day. Every paper is a reply to something. Most students never find out what. She found out in five minutes and it changed the way the paper meant something entirely. A paper you understand in isolation is information. A paper you understand inside its conversation is knowledge. Then she ran the final check. Before closing the paper she asked: "What is the single most important citation missing from this paper that every serious researcher in this field would consider essential? What conversation is this author not in that they should be?" She found a foundational paper the authors had never cited. Not because they were careless. Because they came from a slightly different tradition and had a blind spot they weren't aware of. That blind spot explained a gap in their argument she hadn't been able to name until that moment. She walked into the seminar and named it. Her supervisor stopped the discussion and asked her to explain how she'd found it. She told him she'd asked the right questions of the paper instead of just reading it. He told her that was exactly what twenty years in academia teaches you to do. She'd been doing it for three weeks. Here is the actual workflow. Five questions. In order. Question one: what can and cannot be legitimately concluded from the methodology and results alone? Where does the abstract overreach? Question two: what did this study not measure that would have changed what it found? What is the methodology quietly assuming it never defends? Question three: if you replicated this with a different population or context, what changes? How far do the conclusions actually travel? Question four: what debate is this paper entering? Who is it responding to and what would those people say back? Question five: what is the most important paper missing from the bibliography? What conversation is this author not in? Most students spend three years at university reading papers from the outside. Those five questions put you on the inside in twenty minutes. Claude didn't read the paper for her. It taught her the questions that experienced academics ask automatically after years in a field. She just learned them earlier. The papers didn't change. The questions did. Most students finish a paper feeling like they've understood it. She finished a paper knowing exactly what it proved, what it didn't prove, where it sat in the field, and what it was quietly hoping nobody would ask. That is not a faster way to read. It's a completely different thing to do with a paper. And almost nobody teaches it directly.

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Joshua Gans
Joshua Gans@joshgans·
This paper should be written.
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Joshua Gans
Joshua Gans@joshgans·
@ATabarrok Thanks for the pointer. Didn't know about this, but his target was just the GPA and not the more fundamental identification problem we deal with.
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Alex Tabarrok
Alex Tabarrok@ATabarrok·
A reminder that Valen Johnson solved the Grade Inflation problem decades ago by creating a cross-university Achievement Index that also does not penalize students for taking hard classes chatgpt.com/share/698a394a…
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Luis Garicano 🇪🇺🇺🇦
This seems to me the right answer to the grade inflation problem, and it can be implemented very simply! Think of the Brin/Page PageRank algorithm: an important web page is one that other important pages link to and so on. Imagine a course is taken by a student taking hard courses and doing well and a student only taking easy courses. They both get an A. The course does not separate ability- a strong indicator of inflation. A hard course is chosen by the high "graderank/eigengrade" students. We already use this kind of system for publication impact, to rank NFL courses, and of course to rank search results. Lets use it for grade inflation! Views @ben_golub?
Joshua Gans@joshgans

Behold Eigengrades! @skominers and I have a new preliminary paper out that looks at the issues of cross-course comparability in grades. This was a project motivated by Harvard's proposal to cap the number of As in each course to counter grade inflation. 👇

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