In the latest episode of Elucidations, Sam Enright (Progress Ireland, The Fitzwilliam) instructs us in the delicate art of learning forever.

If you’re one of those people who responds well to formal education, chances are you’ve spent 10-20 years of your life as a student. When you finally graduate, it can feel jarring, like you’re kissing all this efficient infrastructure for mastering difficult skills goodbye. How are you going to keep learning, without a teacher you can pester with questions in the classroom, without regular feedback on homework assignments, and without exams? Sam Enright is here to tell you that just because you’re moving into the next phase of your life, that doesn’t mean you need to turn your back on the learning experience.

In this episode, he discusses his study regimen, which ranges over philosophy, history, economics, math, and computer science, via a couple different formats that are easier to integrate into your everyday life than full-time study in the classroom. The first is something called spaced repetition. This is a method that involves repeating your study practice less and less frequently over time, in order to maximize your direct recall ability. The version that our guest practices involves using software that leans into quizzing you more often on whatever you have the most trouble with, and less often on whatever you have the least trouble with. The quiz questions are of your design, and every time you answer one, you’re given the opportunity to revise it for the future. This allows you to update your study materials over time in light of the expertise you accrue.

Another method Sam Enright recommends is reading groups. Echoing similar recommendations from the Elucidations podcast in Episode 126, our guest tells us about a recurring reading group he runs in Ireland that spans a wide variety of disciplines. The key here is to select reading material that is too difficult for you to fully make sense of on your own, and to establish a culture of staying on topic. Sam Enright’s reading group has been in existence for years now and attracts researchers from all over.

Finally, our guest discusses how he is able to use AI chatbots to supplement the reading process and drill deeper. In addition to traditional techniques such as notetaking, being able to upload an entire text into a chatbot’s context window and then ask it questions about what you’re reading allows you to explore the terrain it opens up interactively. You can restate your understanding of what you just read, invite the chatbot to identify mistakes in your summary, revisit the parts of the original text that are relevant to those mistakes, and so forth. Interestingly, he even reports having success when the platform he is using hallucinates a little, because trying to sniff those hallucations out allows him to cultivate the kind of skeptical attitude that makes reading itself a bit more like the classroom experience.

It was a tremendously fun discussion for me to have, and I hope you enjoy it.

Matt Teichman

Hosted on Acast. See acast.com/privacy for more information.

This time around, Matt talks to Luca Gattoni-Celli about why it’s so expensive to buy a house.

In the 80s, people from all sorts of socioeconomic backgrounds were able to afford apartments and houses in places like New York City, San Francisco, or London. Now, on the other hand, even many wealthy people are getting priced out of the city. And indeed, the issue is no longer specific to urban areas: the problem of seemingly infinitely increasing real estate prices would appear to be creeping into the rest of the US, and into many other areas that were typically regarded as affordable in the recent past.

Why is this the case? In this episode, Luca Gattoni-Celli discusses three factors that have artifically inflated housing prices far beyond the equilibrium point between supply and demand. One is zoning regulations, which impose limits on how maximum building size in a given area, how many people can live on a single property, and so forth. Another is permitting, which has the effect of introducing delays into the building process that make it financially infeasible and thus effectively block it from happening. The third is building codes, many of which were introduced for the purposes of making buildings safer to inhabit, but which have the perverse effect of preventing the construction of new buildings that would be safer than the old buildings that are currently in use.

Our guest also makes the argument that zoning regulations have a sordid racist and classist past, which you can see, to an extent, in some of the original proposals that led to some of the original policies. More broadly, the claim is that population density is the way that low-income people band together to be able to afford real estate for which there is high demand, and that a push to block density effectively amounts to a push to keep lower-income people out.

I found the discussion quite stimulating; I hope you enjoy it.

Matt Teichman

Hosted on Acast. See acast.com/privacy for more information.

Note: this episode was recorded in August of 2022.

In the latest Elucidation, Matt talks to Witold Więcek about the difficulties that come up for researchers who would like to draw upon statistics.

Lots of academic fields need to draw heavily on statistics, whether it’s economics, psychology, sociologym, linguistics, computer science, or data science. This means that a lot of people coming from different backgrounds often need to learn basic statistics in order to investigate whatever question they’re investigating. But as we’ve discussed on this podcast, statistical reasoning is easy for beginners to mess up, and it’s also easy for bad faith parties to tamper with in undetectable ways. They can straight up fabricate data, they can cherry pick it, they can keep changing the hypothesis they are testing until they find one that is supported by a trend in the data they have. So what should we do? We can’t give up on statistics; it is simply too useful a tool.

Witold Więcek argues that researchers have to be mindful of “p-hacking”. Statistical significance, the golden standard of academic publishing, can easily be guaranteed by unscrupulous research or motivated reasoning: statistically speaking, even noise can look like signal if we keep asking more and more questions of our data. Modern statistical workflows require us to either adjust the results for number of hypotheses tested or to follow principles of Bayesian inference. As a broader strategy, Więcek recommends that every research project making significant use of statistical arguments bring in in an external consultant, who can productively stress test those arguments in an adversarial way, given that they aren’t part of the main team.

It was a great conversation! I hope you enjoy it.

Matt Teichman

Hosted on Acast. See acast.com/privacy for more information.