Category: Education

New Emergent Ventures winners, 25th cohort

by  Tyler Cowen in

Duncan McClements, 17, incoming at King’s College Cambridge, economics, general career and research support.

Jasmine Wang and team (Jasmine is a repeat winner), Trellis, AI and the book.

Sophia Brown, Berlin/Brooklyn, to study the State Department,and general career development.

Robert Tolan, western Ireland, farmer and math Olympiad winner, YIMBY by street for Ireland.

Conor Durkin, Chicago, to write a Chicago city Substack.

Guido Putignano, Milan/Zurich, to do a summer internship in computation bio for cell therapies, at Harvard/MIT.

Michelle K. Huang, to revitalize Japanese real estate and to enable a creative community in Japan, near Kyoto.

Rasheed Griffith, repeat winner, to found a Caribbean think tank.

The Fitzwilliam, a periodical of ideas, Ireland.  To expand and built it out, Fergus McCullough and Sam Enright, both repeat winners.

Lyn Stoler, Los Angeles, general career development and to develop material for a new pro-growth, pro-green agenda for states and localities.

Gwen Lester, Chicago, to develop a center for abused, battered, and sexually abused women, namely GLC Empowerment Center, also known as Nana’s House.

Sabrina Singh, Ontario, pre-college, to help her study of neurotechnology.

And Emergent Ventures Ukraine:

Isa Hasenko, eastern Ukraine, medical care for eastern Ukraine, performed by a system of digital information, using a real-time tracking system, to trace every allocation.  He works with Fintable.io and MissionKharkiv.com.

Stephan Hosedlo, Lviv, to expand his company selling farm products and herbal products, and to buy a tractor.

Olesya Drashkaba, Kyiv, Sunseed Art, a company to market Ukrainian art posters around the world.

Peter Chernyshov, Edinburgh, mathematician, to run math education project — Kontora Pi — to teach advanced math for talented kids and school teachers in Ukraine.  To produce more math videos and to recruit more teachers around Ukraine.

Andrew Solovei, western Ukraine, to build out a network to compensate small scale Ukrainian volunteers in a scalable and verifiable manner.

Olena Skyrta, Kyiv, to start a for-profit that will tie new scientific innovations to Ukrainian and other businesses.

Yevheniia Vidishcheva, Kyiv, theatrical project to travel around Ukraine.

Alina Beskrovna, Mariupol and Harvard Kennedy School, general career support and to work on the economic reconstruction of Ukraine.

My excellent Conversation with Tom Holland

by  Tyler Cowen in

Here is the transcript, audio, and video.  Here is part of the summary:

Historian Tom Holland joined Tyler to discuss in what ways his Christianity is influenced by Lord Byron, how the Book of Revelation precipitated a revolutionary tradition, which book of the Bible is most foundational for Western liberalism, the political differences between Paul and Jesus, why America is more pro-technology than Europe, why Herodotus is his favorite writer, why the Greeks and Persians didn’t industrialize despite having advanced technology, how he feels about devolution in the United Kingdom and the potential of Irish unification, what existential problem the Church of England faces, how the music of Ennio Morricone helps him write for a popular audience, why Jurassic Park is his favorite movie, and more.

Here is one excerpt:

COWEN: Which Gospel do you view as most foundational for Western liberalism and why?

HOLLAND: I think that that is a treacherous question to ask because it implies that there would be a coherent line of descent from any one text that can be traced like that. I think that the line of descent that leads from the Gospels and from the New Testament and from the Bible and, indeed, from the entire corpus of early Christian texts to modern liberalism is too confused, too much of a swirl of influences for us to trace it back to a particular text.

If I had to choose any one book from the Bible, it wouldn’t be a Gospel. It would probably be Paul’s Letter to the Galatians because Paul’s Letter to the Galatians contains the famous verse that there is no Jew or Greek, there is no slave or free, there is no man or woman in Christ. In a way, that text — even if you bracket out and remove the “in Christ” from it — that idea that, properly, there should be no discrimination between people of different cultural and ethnic backgrounds, based on gender, based on class, remains pretty foundational for liberalism to this day.

I think that liberalism, in so many ways, is a secularized rendering of that extraordinary verse. But I think it’s almost impossible to avoid metaphor when thinking about what the relationship is of these biblical texts, these biblical verses to the present day. I variously compared Paul, in particular in his letters and his writings, rather unoriginally, to an acorn from which a mighty oak grows.

But I think actually, more appropriately, of a depth charge released beneath the vast fabric of classical civilization. And the ripples, the reverberations of it are faint to begin with, and they become louder and louder and more and more disruptive. Those echoes from that depth charge continue to reverberate to this day.

And:

COWEN: In Genesis and Exodus, why does the older son so frequently catch it hard?

HOLLAND: Well, I’m an elder son.

COWEN: I know. Your brother’s younger, and he’s a historian.

HOLLAND: My brother is younger. It’s a question on which I’ve often pondered, because I was going to church.

COWEN: What do you expect from your brother?

HOLLAND: The truth is, I have no idea. I don’t know. I’ve often worried about it.

Quite a good CWT.

Time Passages

by  Alex Tabarrok in

Here’s an interesting idea it wouldn’t have occured to me to ask. What is the length of time described in the average 250 words of narration and how has this changed over time? Most famously James Joyce’s “Ulysses” is a long novel about single day with many pages describing brief experiences in minute detail. In contrast, Olaf Stapledon’s Last and First Men covers 2 billion years in fewer words than Joyce uses to cover a single day.

Using human readers grading 1000 passages, Underwood et al. (2018) finds that the average length of time described in a typical passage has declined substantially since the 1700s, from a day to about an hour so a decline by a factor of 24. Writers have become much more focused on describing individual experiences than events.

In a blog post, Underwood revisits his earlier work but this time comparing human readers with various statistical techniques and also GPT. To use GPT he prompts

Read the following passage of fiction. Then do five things. 1: Briefly summarize the passage. 2: Reason step by step to decide how much time is described in the passage. If the passage doesn’t include any explicit reference to time, you can guess how much time the events described would have taken. Even description can imply the passage of time by describing the earlier history of people or buildings. But characters’ references to the past or future in spoken dialogue should not count as time that passed in the scene. Report the time using units of years, weeks, days, hours, or minutes. Do not say zero or N/A. 3: If you described a range of possible times in step 2 take the midpoint of the range. Then multiply to convert the units into minutes. 4: Report only the number of minutes elapsed, which should match the number in step 3. Do not reply N/A. 5: Given the amount of speculation required in step 2, describe your certainty about the estimate–either high, moderate, or low. The passage follows: <omitting this to save space>

Here’s an example of the analysis:

ABRIDGED PASSAGE FROM Jane Eyre: And signs, for aught we know, may be but the sympathies of Nature with man. When I was a little girl, only six years old, I one night heard Bessie Leaven say to Martha Abbot that she had been dreaming about a little child … Of late I had often recalled this saying and this incident; for during the past week scarcely a night had gone over my couch that had not brought with it a dream of an infant, which I sometimes hushed in my arms, sometimes dandled on my knee, sometimes watched playing with daisies on a lawn, or again, dabbling its hands in running water. It was a wailing child this night, and a laughing one the next: now it nestled close to me, and now it ran from me; but whatever mood the apparition evinced, whatever aspect it wore, it failed not for seven successive nights to meet me the moment I entered the land of slumber.

ASSISTANT REPLIES.

1: The narrator recalls a saying about dreaming of children being a sign of trouble and remembers an incident from her childhood. She then describes her recent dreams of infants over the past week.

2: The passage mentions the narrator’s childhood memory, which happened when she was six years old, and the past week of dreams. The time elapsed in the passage is the week of dreams.

3: 1 week has elapsed. At seven days a week that’s 7 days. 24 hours in a day, so 168 hours. 60 minutes in an hour, so 10080 minutes.

4: 10080 minutes.

5: Moderate confidence, as the childhood memory is not counted as time passing in the scene.

Overall, Underwood finds that GPT-4 is more accurate than previous statistical techniques in that its judgments correlate with those of human readers nearly as much as human readers correlate with themselves.

Addendum: See also my paper with Tyler on how to use GPT models.

What is the single best way of improving your GPT prompts?

by  Tyler Cowen in

I have a nomination, and here is an excerpt from my new paper with Alex:

You often can get a better and more specific answer by asking for an answer in the voice of another person, a third party. Here goes: What are the causes of inflation, as it might be explained by Nobel Laureate Milton Friedman?

By mentioning Friedman you are directing the GPT to look at a more intelligent segment of the potential answer space and this directing will usually get you a better answer than if you just ask “What are the causes of inflation?” Similarly, you want all of the words used in your query to be intelligent-sounding. Of course, you may not agree with the views of Friedman on inflation. Here are a few economists who are well known and have written a lot on a wide variety of issues:

Paul Samuelson
Milton Friedman
Susan Athey
Paul Krugman
Tyler Cowen
Alex Tabarrok

But you don’t have to memorize that list, and it is not long enough anyway. When in doubt, ask GPT itself who might be the relevant experts. How about this?: “I have a question on international trade. Which economists in the last thirty years might be the smartest experts on such questions?” The model will be very happy to tell you, and then you can proceed with your further queries.

Of course this advice generalizes far beyond economics.  A friend of mine queried GPT-4 about Jon Fosse, a Norwegian author, and received a wrong answer.  He retried the same question, but asking also for an answer from a Fosse expert.  The response was then very good.

The title of my paper with Alex is “How to Learn and Teach Economics with Large Language Models, Including GPT,” but again most of the advice is generalizable to education with GPTs more generally.  Recommended, the paper is full of tips for using GPT models in more effective ways.

Imagine if humanity ends up divided into two classes of people: those who are willing/not embarrassed to tack on extra “silly bits” to their prompts, and those who are not so willing.  The differences in capabilities will end up being remarkable.  Are perhaps many elites and academics unwilling to go the extra mile in their prompts?  Do they feel a single sentence question ought to be enough?  Are they in any case constitutionally unused to providing extra context for their requests?

Time will tell.

Teaching and Learning Economics with the AIs

by  Alex Tabarrok in

Tyler and I have a new paper, How to Learn and Teach Economics with Large Language Models, Including GPT:

GPTs, such as ChatGPT and Bing Chat, are capable of answering economics questions, solving specific economic models, creating exams, assisting with research, generating ideas, and enhancing writing, among other tasks. This paper highlights how these innovative tools differ from prior software and necessitate novel methods of interaction. By providing examples, tips, and guidance, we aim to optimize the use of GPTs and LLMs for learning and teaching economics effectively.

Most of the paper is about how to use GPTs effectively but we also make some substantive points that many people are missing:

GPTs are not simply a chatty front end to the internet. Some GPTs like ChatGPT have no ability to search the internet. Others, like Bing Chat, can search the internet and might do so to aid in answering a question, but that is not fundamentally how they work. It is possible to ask a GPT questions that no one has ever asked before. For example, we asked how Fred Flintstone was like Hamlet, and ChatGPT responded (in part):

Fred Flintstone and Hamlet are two vastly different characters from different time periods, cultures, and mediums of storytelling. It is difficult to draw direct comparisons between the two.

However, one possible point of similarity is that both characters face existential dilemmas and struggles with their sense of purpose and identity. Hamlet is plagued by doubts about his ability to avenge his father’s murder, and his own worthiness as a human being. Similarly, Fred Flintstone often grapples with his place in society and his ability to provide for his family and live up to his own expectations.

Not a bad answer for a silly question and one that (as far as we can tell) cannot be found on the internet.

GPTs have “read” or “absorbed” a great amount of text but that text isn’t stored in a database; instead the text was used to weight the billions of parameters in the neural net. It is thus possible to run a GPT on a powerful home computer. It would be very slow, since computing each word requires billions of calculations, but unlike storing the internet on your home computer, it is feasible to run a GPT on a home computer or even (fairly soon) on a mobile device.

GPTs work by predicting the next word in a sequence. If you hear the phrase “the Star-Spangled”, for example, you and a GPT might predict that the word “Banner” is likely to come next. This is what GPTs are doing but it would be a mistake to conclude that GPTs are simply “autocompletes” or even autocompletes on steroids.

Autocompletes are primarily statistical guesses based on previously asked questions. GPTs in contrast have some understanding (recall the as if modifier) of the meaning of words. Thus GPTs understand that Red, Green, and Blue are related concepts that King, Queen, Man and Woman are related in a specific way such that a woman cannot be a King. It also understands that fast and slow are related concepts, such that a car cannot be going fast and slow at the same time but can be fast and red and so forth. Thus GPTs are able to “autocomplete” sentences which have never been written before, as we described earlier.2 More generally, it seems likely that GPTs are building internal models to help them predict the next word in a sentence (e.g. Li et al. 2023).

The paper is a work in progress so comments are welcome.

How will AI transform childhood?

by  Tyler Cowen in

That is the topic of my latest Bloomberg column, here is one excerpt:

In the future, every middle-class kid will grow up with a personalized AI assistant — so long as the parents are OK with that.

As for the children, most of them will be willing if not downright eager. When I was 4 years old, I had an imaginary friend who lived under the refrigerator, called (ironically) Bing Bing. I would talk to him and report his opinions to my parents and sister.

In the near future, such friends will be quite real, albeit automated, and they will talk back to our children as directly as we wish. Having an AI service for your child will be as normal as having a pet, except the AI service will never bite. It will be carried around in something like a tablet, though with a design that is oriented toward the AI.

Recent developments suggest that AI models can be both commoditized and customized more easily and cheaply than expected. So parents will be able to choose what kind of companion they want their kids to have — in contrast to the free-for-all of the internet. The available services likely will include education and tutoring, text or vocalizations of what the family pet might be thinking, dancing cartoon avatars, and much more. Companies will compete to offer products that parents think will be good for their kids. Some of the AIs might even read bedtime stories (in fact, I’ve already heard some of them).

Many parents may be reluctant to let their kids become attached to an AI. But I predict that most families will welcome it. For one, parents will be able to turn off the connection whenever they wish. Simply clicking a button is easier than yanking an iPad out of a kid’s grasp.

Most of all, letting your kid have an AI companion will bring big advantages. Your child will learn to read and write much faster and better, and will do better in school. Or maybe you want your kid to master Spanish or Chinese, but you can’t afford an expensive tutor who comes only twice a week. Do you want your child to learn how to read music? The AI services will be as limited or as expansive as you want them to be.

It is an open question how quickly schools will embrace these new methods of learning. At some point, however, they will become part of the curriculum. Competitive pressures will make parents reluctant to withhold AI from their kids. Even if the AIs are not present in the classroom, some kids will use them to help do their homework, gaining a big advantage, and the practice will likely spread.

Of course children will use these AIs for purposes far beyond what their parents intend. They will become playthings, companions, entertainers and much more. When I was a kid, with no internet and mediocre TV, I created imaginary worlds in the dirt, or with simple household items, and my parents often had no clue. The AI services will become part of this model of spontaneous play, even if parents try to make them purely educational.

What about teenagers? Well, many parents may allow their kids to speak with AI therapists. It might be better than nothing, and perhaps better than many human therapists.

Recommended, and I do discuss some potential risks as well.

Tabarrok on Stranded Technologies Podcast

by  Alex Tabarrok in

I talk with entreprenreur Niklas Anzinger on the Stranded Technlogies Podcast. Niklas summarizes some of the discussion:

  • This episode is an intellectual journey that discovers insights that can be used by entrepreneurs and city developers. We talk about the Baumol effect that Alex uses to explain the now infamous price chart.
  • Alex’s recommendation to new city or governance startups like Prospera, Ciudad Morazan or the Catawba DEZ is to think of city development as a “dance between centralization and decentralization”.
  • Economists have developed concepts that are waiting to be commercialized, e.g. prediction markets. In this episode, we talk about dominant assurance contracts and how they could be used in new city developments and fundraising.

My Conversation with Yasheng Huang

by  Tyler Cowen in

Here is the audio, video, and transcript, Yasheng is a China scholar and a professor at MIT.  Here is part of the episode summary:

Yasheng joined Tyler to discuss China’s lackluster technological innovation, why declining foreign investment is more of a concern than a declining population, why Chinese literacy stagnated in the 19th century, how he believes the imperial exam system deprived China of a thriving civil society, why Chinese succession has been so stable, why the Six Dynasties is his favorite period in Chinese history, why there were so few female emperors, why Chinese and Chinese Americans have less well becoming top CEOs of American companies than Indians and Indian Americans, where he’d send someone on a two week trip to China, what he learned from János Kornai, and more.

And an excerpt:

COWEN: Now, in your book, you write of what you call Tullock’s curse— Gordon Tullock having been my former colleague — namely, embedded succession conflict in an autocracy. Why has Chinese succession been so stable up to now? And will we see Tullock’s curse whenever Xi steps down, passes on, whatever happens there?

HUANG: I do want to modify the word that you use, stable. There are two ways to use that term. One is to describe the succession process itself. If that’s the situation we’re trying to describe, it is not stable at all. If you look at the entire history of the PRC, there have been so many succession plans that failed, and at a catastrophic level. One potential successor was persecuted to death. Another fled and died in a plane crash. Others were unceremoniously dismissed, and one was put under house arrest for almost 15 years, and he died —

COWEN: But no civil war, right?

HUANG: Yes, that’s right.

COWEN: No civil war.

HUANG: That’s right. There’s another way to talk about stability, which is stability at the system level, and that, you are absolutely right. Despite all these problems with these successions, the system as a whole has remained stable. The CCP is in power. There’s no coup, and there were not even demonstrations on the street associated with the succession failures. So, we do need to distinguish between these two kinds of stability. By one criterion, it was not stable. By the other criterion, it is quite stable.

The reason for that is, I think — although it’s a little bit difficult to generalize because we don’t really have many data points — one reason is the charisma power of individual leaders, Mao and Xiaoping. These were founding fathers of the PRC, of the CCP, and they had the prestige and — using Max Weber’s term — charisma, that they could do whatever they wanted while being able to contain the spillover effects of their mistakes. The big uncertain issue now is whether Xi Jinping has that kind of charisma to contain future spillover effects of succession failure.

This is a remarkable statistic: Since 1976, there have been six leaders of the CCP. Of these six leaders, five of them were managed either by Mao or by Deng Xiaoping. Essentially, the vast majority of the successions were handled by these two giants who had oversized charisma, oversized prestige, and unshakeable political capital.

Now we have one leader who doesn’t really have that. He relies mostly on formal power, and that’s why he has accumulated so many titles, whereas he’s making similar succession errors as the previous two leaders.

Obviously, we don’t know — because he hasn’t chosen a successor — we don’t really know what will happen if he chooses a successor. But my bet is that the ability to contain the spillover effect is going to be less, rather than more, down the road, because Xi Jinping does not match, even in a remote sense, the charisma and the prestige of Mao Zedong and Deng Xiaoping. There’s no match there.

Recommended.  And I am happy to recommend Yasheng Huang’s forthcoming book The Rise and Fall of the East.

Pre-order here: https://www.amazon.com/dp/0300266367?ref_=cm_sw_r_cp_ud_dp_CXCHDSQB8JBKEXM4J5BE

On graduate student mental health (from my email)

by  Tyler Cowen in

…we often discuss mental health in terms of treatment and selection effects. While more causal inference is needed, I believe it some points are often overlooked.

Personality plays a role: Many in the field can be characterized as overachievers. This behavior can easily turn pathological if it is driven by a fear of failure or a sense that self-worth is contingent on competence. Moreover in a competitive academic environment. Exit may be psychologically very difficult if your self-worth is on the line.

Policies within graduate programs exacerbate the issue: In my program, if a student drops out, the University will not award them a master’s degree if they already have a similar degree from another university. This policy discourages students exit and may keep them in situations that are not beneficial for their mental health.

Economists tend to overrate the effectiveness of educational signals in selecting prospective grad study: Interviews are often not a part of the selection process, which I believe is a missed opportunity to assess a student’s psychological readiness for a PhD program. For many far less stressful jobs psychological testing is standard. In my experience, I only received interviews from programs that had already accepted me (meant to convince me to accept offers).

From anonymous.

What should I ask David Bentley Hart?

by  Tyler Cowen in

I will be doing a Conversation with him.  David Gordon claims the guy has read more than David Gordon!  Here is Wikipedia:

David Bentley Hart (born 1965) is an American writer, philosopher, religious studies scholar, critic, and Orthodox theologian noted for his distinctive, humorous, pyrotechnic and often combative prose style. With academic works published on Christian metaphysics, philosophy of mind, classics, Asian languages, and literature, Hart received the Templeton Fellowship at the University of Notre Dame Institute for Advanced Study in 2015 and organized a conference focused on the philosophy of mind. His translation of the New Testament was published by Yale in 2017 with a 2nd edition in 2023.

A prolific essayist, Hart has written on topics as diverse as art, baseball, literature, religion, philosophy, consciousness, problem of evil, apocatastasis, theosis, fairies, film, and politics. His fiction includes The Devil and Pierre Gernet: Stories (2012) as well as two books from 2021: Roland in Moonlight and Kenogaia (A Gnostic Tale). Hart also maintains a subscription newsletter called Leaves in the Wind that features original essays and conversations with other writers such as Rainn Wilson, China Miéville, Tariq Goddard, and Salley Vickers. Hart’s friendship and substantial intellectual common ground with John Milbank has been noted several times by both thinkers.

So what should I ask him?

What young people say is driving changes in their mental health

by  Tyler Cowen in

I would stress this point. Most of the explanations for declining teen mental health invoke contagion at one stage of the argument or another. That in turn means the initial causes can be fairly small, relative to the final outcome. Contagion itself is arguably the most important cause.