Books Do Furnish a Life, by Richard Dawkins

Yep, I am catching up with book reviews. I have read several this year, although not at the same pace as last year, so there’s a lot of work to do. Let’s dive in.

Richard Dawkins, the eminent British biologist, just published a book, Books Do Furnish a Life, that collects many of his writings and conversations. These include book reviews, forewords, afterwords, and conversations with other thinkers on various topics such as biology, the role of science, secularism.

I must admit that, as much as I admire Dawkins, this is the first book I read by him. The Selfish Gene is in my bookcase looking down on me, both figuratively and literally, as if saying: you don’t have what it takes, do you? Apparently not, or at least not yet. However, Books Do Furnish a Life has been useful in expanding my reading on biology, so much so that I am starting to think about taking up the challenge of his first book. Even since I was a teenager I had very little difficulty in reading popular astrophysics and particle physics books: I devoured all Stephen Hawking‘s books, and I still recall the impact that Just Six Numbers, by Martin Rees, had on me; all before I finished high-school.

But biology is a different matter. Maybe it is the broader range of specific vocabulary. Maybe it is my inner interest in the topic. Maybe it is a combination of different factors. But I’ve always found it difficult. It is also, by the way, because evolution by natural selection is not extremely intuitive. I mean, the mechanism is intuitive; what it is difficult to grasp is the timescale at which it has worked. Not also this: the role of the genes, and how the genes manifest themselves in different behaviours that can even change the environment leading to higher survival changes—the extended phenotype. But then again, quantum mechanics is not the most intuitive phenomenon either.

The short writings collected in this book are very useful to further the knowledge on these topics. The way that Dawkins writes, providing analogies to the various mechanisms at work especially in evolution by natural selection, is a delight. I can’t emphasise this enough: the clarity, and the beauty, and intuitiveness—they are superb. And the enthusiasm! You can tell that Dawkins feels fascinated by what we have learned in the recent decades about how we came to be. The sheer breath of knowledge at the service of educating the reader is a gift for all of us. He follows the advise of Steve Pinker in The Sense of Style: write as if your reader is as intelligent as you are but lacks the particular knowledge of the topic.

And then we have the conversations with other thinkers. One of them is the aforementioned Pinker, someone I also greatly admire, talking about Darwin and evolutionary psychology. Others include Neil deGrasse Tyson, Matt Ridley, and the one and only Christopher Hitchens—for The Hitch that was the last interview he gave before his death, published in the NewStatesman: Never Be Afraid of Stridence. Interesting and absorbing in equal parts, these conversations introduce each section of the book.

I don’t think there’s an equal to Dawkins on science popular writing. Maybe Carlo Rovelli, writing about physics, gets close to him. But the amount of writing by Dawkins far exceeds that by Rovelli. Anyone interested in biology, evolution by natural selection, and secularism, will find this collection of short writings incredibly absorbing. Highly, highly, highly recommended.

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Loan evergreening

Loan evergreening is a situation where banks provide loans to firms in order to ensure that firms keep repaying the existing (previous) loans. It is a concept related to zombie lending, broadly defined as lending to non-viable firms. Loan evergreening is a usual strategy to provide zombie lending, although it can be used in other circumstances.

In the recent years, there has been an increase in economic research trying to understand zombie lending and its consequences. Some blame zombie lending for the low productivity in some European countries. But less attention has been put on loan evergreening. Partly, this reflects an issue with data availability: it is easier to obtain data on firms (and hence proxy for which firms appear non-viable or very weak) rather than loan-level information.

And even if one has loan-level information, how do you detect loan evergreening? It is not like banks tell us why they are providing the loan. In many cases, they can provide loan evergreening before any problems, such as repayment delays, arise in the firm. This is an issue that we aim to tackle in a very recent paper with Cecilia Dassatti and Rodrigo Lluberas from the Banco Central del Uruguay.

Let’s imagine the following situation. A firm has an amortising loan, that is, a loan that has to be repaid periodically. But the firm is facing some trouble that may lead it to delay a loan repayment. Banks do not like that: they face increased credit risk—the firm might outright default—and, even more importantly, the regulator makes them provision for a potential loss. Provisions are very annoying for bankers: they come right before computing profits, and therefore they have a direct—negative, in this case—impact on bonuses.

What can the bank do? Well, the bank could provide a bullet loan to the firm—that is, a loan that is repaid only at the end of its maturity—so that the firm is not delayed. This seems a clear case of loan evergreening. But how can we detect such cases? A possibility is to flag every time a bank provides a bullet loan to a firm that already has an amortizing loan. However, firms might need bullet loans for reasons other than repaying the previous loan.

What about flagging situations in which the amount of a new bullet loan is very similar to the amount that the firm repays of the existing loan? For instance, a situation in which a firm receives $100 in the form of a bullet loan from a bank and repays in the same month $100 of the existing loan with the same bank. If we can detect these situations, it seems that we have found cases of loan evergreening.

But are these cases common? To answer this question, we compare the amount received in a new bullet loan with the amount repaid of the existing amortizing loan. We plot the histogram of the ratio in the figure below. As you can see, there is a spike of values very close to 1; that is, situations in which the two amounts are very similar.

From Dassatti et al. (2021)

In the paper, which is in its last minutes in the oven, we proceed to understand which bank characteristics are more linked to the provision of loan evergreening (spoiler alert: solvency), what happens with credit supply after engaging in this strategy, whether this strategy makes firms more or less likely to default, and what this means for other firms. But a post about the results will come once the paper is out.

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So we are Bayes Business School now

Yesterday, The Business School (formerly Cass), which used to be—yes, you guessed it—Cass Business School, and that also used to be City University Business School, became Bayes Business School.

You may recall that, in the wake of the killing of George Floyd, it was revealed that Sir John Cass had been actively involved in slave trading back in his time (1661-1718). I don’t think that was a super-hidden secret; I mean, of course I didn’t know about it, but I didn’t know a single thing about the guy. Yet it is difficult to imagine that when the School decided to adopt this name (2004 or so) they did not encounter this information. Those were different times—the early 2000s I mean—but I think slavery was already considered immoral.

Anyway. As a result, we (and by we, I mean the University and the Business School) decided to change our name. After almost a year, we chose Bayes Business School. Our links with Thomas Bayes, who first formulated the Bayes’ Theorem, are “extremely strong”: the dude is buried in front of the Business School, in Bunhill Fields. And that would be it. I mean, the Bayes’ Theorem is very important in finance, but I guess that applies to any finance department.

How do I feel about the name, you asked? Well, I think it is a fantastic name. It is better than Cass Business School even if John Cass had been an exemplary man. In fact, it is a name that is better than the business school, at least in its current state. But I guess this is what you want, right? I name that points to where you want to reach, what you want to achieve. It is easier to revert a frankly negative trend with a name that is inspiring. Although it is still difficult, so let’s see how it goes!

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The Scout Mindset, by Julia Galef

I have known about Julia Galef for a while, as she hosts the podcast Rationally Speaking. I have talked about this podcast in the past. She used to co-host it with Massimo Pigliucci, a philosopher and authors of several books, including Live Like a Stoic. But that was years ago. And, truth to be told, I think she hosts much better by herself. She listens to the arguments of the others and engages with them—not with a strawman version of them, but with them. And she mentions how she changed her mind after the interviews, even if just slightly. She has a scout mindset. And now she has written a book about it, titled, yes, The Scout Mindset.

So what is a scout mindset? Julia uses this term as opposed to a soldier mindset. The soldier’s goal is to win. The scout’s goal is to obtain a more precise representation of reality. Many times, when we discuss heated topics, we enter into a soldier mindset. I mean, not me, of course, but everybody else does. Apparently, it is difficult to realise—or at least it is not straightforward—when you are in soldier mode. Yet if we really want to find out the truth, the soldier mindset is counterproductive. We should be willing to change our mind. The scout might think or hope that there is a bridge to cross the river; but if there is not, then he or she will update their map accordingly.

But, do we really want to find out the truth? Some might argue that we do not. Those that insist in being precise, in being as truthful as possible, in knowing all the facts, those people are just not willing to solve the problems. Let’s see an example where this reasoning can be applied:

Maybe we still have a couple of decades to adjust our CO2 emissions before a significant increase in temperature is irreversible. Maybe not. Would waiting for all the answers—being a scout—be the right approach, given what’s at stake? Or is it better to say that unless we act TODAY, the world is going to end this century?

Some people will say the latter is a better option. People have to react, and unless they feel the thread is imminent, they will not. Maybe. But maybe making strong statements that are not fully backed by the science also discredits a movement. Maybe discovering that scientists skeptic about climate change in the early part of this century (“climategate“) were shut down by other scientists made hesitant public opinion even more hesitant. To the extent one does not control the information that people can access, being truthful seems to pay off almost always.

A part of the book that I found particularly appealing is about “holding your identity lightly”. A problem when you strongly identify with a particular movement is that push back against the movement actions, for example, feel extremely personal to oneself. Even by people that share the ultimate goals. Or even more by these people. Validating oneself might become more important than the ultimate goal. Dunking on someone with a different opinion might feel very well—I am good, the other is bad—but might do very little to advance the cause. It can actually push other people towards the other side.

But at least we can rely on education and intelligence to avoid our soldier biases, right? Not really. Even though one could expect that the more educated one gets, the more one is able to formulate logically sound arguments without getting into fallacies, this appears to be wrong. One reason might be that better educated people are better able to rationalise—even if ex post—their actions, or be aware of some “evidence” that seems to confirm their beliefs. Anyone knows highly educated people that do not seem capable of changing their mind on certain issues, irrespective of the evidence. But to think that this is not the exception, but in a way the rule, that’s striking. The chart below, from Kahan et al. (2017), shows how many agree with the statement that “there is solid evidence of recent global warming due mostly to human activity such as burning fossil fuels“. In low levels of “ordinary science intelligence” (this is determined by a series of questions that participants have to answer before), there is no disagreement between liberals and conservatives. As their science intelligence increases, they diverge substantially. Whatever you think the right answer is (spoiler alert: it’s AGREE), at least one group moves away from it as they are more “intelligent”. Funny enough, this does not happen when we measure the science curiosity of the participants, which we could see as a proxy of having a scout mindset; if anything, both groups tend towards the right answer the more scientifically curious they are.

Kahan et al. (2017). Available at:

To wrap up, Julia has written a wonderful book, with funny anecdotes, great advice to be more of a scout, and a very positive attitude. She has been talking to several people about the book (and other things, such as the rationalist community). Here are some of her appearances: The Wright Show, Mindscape with Sean Carroll, and Julia’s YouTube channel. Recommended.

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30 books in 2020

So I read 30 books in 2020. I’m not sure how I did it, but I did it. You don’t believe me? Look at my Goodreads notification:

Almost 23 pages per day, which is around one hour of reading. I am happy with the achievement, but I don’t think I am going to repeat it this year. I might try to go for fewer books but a more detailed reading. Let’s see how it goes. But anyway, I just wanted to mention the five books that I consider to be more interesting:

  • Moral Tribes. Emotion, Reason, and the Gap between Us and Them. Joshua Greene.
  • Utilitarism. A Very Short Introduction. Katarzyna de Lazari-Radek and Peter Singer.
  • Self-portrait in Black and White. Unlearning Race. Thomas Chatterton-Williams.
  • The Precipice. Existential Risk and the Future of Humanity. Toby Ord.
  • Everybody Lies. What the Internet Can Tell Us About Who We Really Are. Seth Stephens-Davidowitz.

I even read a book in science fiction! The Three-Body Problem, by Cixin Liu. It was a gift, but I read it quite fast. I will try to add more fiction in my list… although the one I would like to read is The Doors of Stone. No news on that front yet…

For 2021, as I said, my goal is more modest: 12 non-fiction books, one per month, trying to write a bit about each of them. I won’t provide a tentative list to avoid the dopamine release that makes it less likely that I end up reading them.

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Draft No. 4, by John McPhee

It takes what it takes” (William Shawn, former editor of The New Yorker)

Get that boy from the Old Vic” (Winston Churchill, referring to Richard Burton)

Write on subjects in which you have enough interest on your own to see you through all the stops, starts, hesitations, and other impediments along the way” (John McPhee)

Draft No. 4. On the Writing Process is a must-read—an overly-used adjective that nevertheless finds a worthy subject here—for anyone that writes non-fiction. McPhee, its author, is an American writer considered one of the pioneers of creative non-fiction. He has been writing for The New Yorker since the 1960s.

In Draft No. 4, he explores different aspects of writing—structure, editors, omission, and more—drawing on his vast experience and with his unique style. It’s like peeping behind a magician’s stage, glimpsing, and even understanding, albeit just superficially, how the trick is done. Yes, I understand that you take the card and place it in your pocket; I am still unable to do it myself though.

Trying to say anything more would be doing a disservice to this book. Read it. Read it even if you do not know—I did not—who John McPhee is. Read it even if you are not very familiar—I am not—with The New Yorker. This book brings the concept of craft to a different level. Reading through the way McPhee composes a piece, one realises how much there is to improve. It is, in a sense, reassuring: there is no need to worry about reaching the destination any time in this life.

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Arbitrage in SME lending

One of the big concerns of the aftermath of the Covid-19 crisis is that the recovery might take much longer because many firms, particularly small and medium (SMEs), will have closed down for good. From the very beginning, different actions by governments and central banks tried to make sure that SMEs did not suffer a reduction in credit. For instance, the Bank of England put in place a Term Funding Scheme (TFS) to provide cheap funding to banks, and the amount that banks can borrow from this scheme is proportional to the amount of lending that they provide to SMEs. The idea is then that banks can borrow very cheap from the central bank if they in turn provide credit to SMEs.

But of course there are limits to this policy. Even if banks keep lending to SMEs, these firms will suffer losses—many of them are temporarily closed—and hence the risk that they are unable to pay back the credit, even when this credit stays constant, increases as the lockdown remains. Banks have to consider these risks: their provisions and capital should go up to cover the increase in potential losses. This has been a source of concern at the Bank of England.

Nevertheless, the UK government has introduced a different scheme, Bounce Back Loans. These loans provided by banks but fully guaranteed by the government—if firms cannot repay, the government will. Given the maximum size of the loans, £50,000, they are designed for small firms. These are, hence, additional incentives for banks to lend to SMEs.

How do both schemes interact? Well, in the last days the Bank of England has provided some interesting information on this regard. First, bounce back loans can have a maturity up to six years, while, originally, the maximum term in the TFS was four years; the Bank of England has announced that it will be possible to extend the funding to match the maturity of the bounce back loans.

This way, banks can borrow very cheaply from the Bank of England scheme and provide bounce back loans to small firms. But what about capital requirements? There is a part of capital regulation that covers credit risk mitigation, which is the situation where the borrower obtains guarantees from a third party to repay the loans. Exactly as bounce back loans. Again, here the Bank of England has clarified that this can be done and hence banks can provide these loans at essentially zero risk weights; in other words, these loans carry no capital requirements.

Yet the 2007-08 financial crisis showed the limits of risk-based capital regulation; for this reason, policy makers around the world introduced the leverage ratio, a capital regulation that does not depend on the riskiness of bank’s assets, only on its size. I have talked about it extensively (here, here, here, here). Even if risk weights on these loans are zero, they would still affect the leverage ratio. However, the Bank of England has announced that these loans will be exempt from this regulation; more precisely, these loans will not be added to the “Leverage Exposure Measure”, which is the denominator of the leverage ratio.

Therefore, banks have a fantastic arbitrage strategy that consists on providing loans to SMEs with the full guarantee of the government and fund these loans using funding from the Bank of England just slightly above the Bank Rate (at the moment, the Bank Rate is at 0.1%). The only limit to this strategy is the amount of eligible collateral of the bank. Other than that, capital and leverage requirements are not binding, and from the point of view of liquidity requirements, this strategy is also neutral (the funding is quite long-term).

What are the risks? For the banking sector, none, as long as the UK government maintains its solvency. And this is key. The current framework assumes that the main problem of non-financial corporations is liquidity, not solvency. But this is not at all clear. For sure, liquidity is an issue, but so is solvency, especially for some sectors. What happens if a big part of these guarantees end up realising? The government debt would increase even more. It is not unthinkable that the UK might lose the double-A credit rating in the near future. And all this while negotiating the new deal with the EU.

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Limiting borrowers leverage

In the last post I talked about the countercyclical capital buffer (CCyB), a new regulatory tool to increase banks’ capital requirements that most countries have not used but that could have been effective to mitigate the Covid-19 crisis. As I mentioned there, the UK did use it, albeit not to the full extent. But the UK has used other tools to try to limit the buildup of risks; one of the most important ones is a tool limiting the number of high loan-to-income mortgages.

Loan-to-income (LTI) indicates how big is the mortgage debt relative to the annual income of the borrower. If someone earning £60,000 a year takes a £240,000 mortgage to buy a house, then the LTI is 4. The higher the LTI, the higher the leverage borrowers are taking. And the higher the amount borrowed with respect to income, the more consumption responds to changes in aggregate conditions. The reason is that borrowers adjust their consumption in order to reduce the possibility of default, especially in countries with full-recourse, such as the UK. The chart below presents evidence that higher LTIs were associated with stronger reductions in consumption during the financial crisis (even when normalising by income). The chart is taken from the Bank of England’s December 2019 Financial Stability Report.


Therefore, reducing mortgages with high LTIs should lead to a smaller adjustment during a crisis. I am not going to discuss here the differences between the Covid-19 and the financial crises—for instance, consumption is going down mostly because of the quarantine, not because unemployment is going up. The point is to highlight another measure introduced by the Bank of England in 2014: a limit on the number of mortgages with LTI equal or above 4.5 that lenders can grant. If this measure indeed limited this type of mortgages, then this might improve consumption during the Covid-19 crisis.

The evidence from the distribution of LTIs before and after the policy was introduced is consistent with the idea that it limited high LTI mortgage lending. In the chart below (taken from the July 2016 FSR) we can see that although the distribution has shifted right (compared to 2014Q1), the frequency of mortgages with LTI above 4.5 has decreased. To the extent that this reduction would not have happened without the policy (luckily we will share some evidence backing this claim up soon) then the adjustment in consumption during this crisis might be lower than what would have happened without the policy.


In general, one of the issues with this type of intervention (which we broadly call “macroprudential policy”), is that one can only empirically assess the “costs” while the economy is growing well; costs, for instance, would be a reduction in mortgage lending. It is precisely only during a crisis, or at least a change in the cycle, where the benefits of this policy start to show. This is one of the reasons why we see a weakening of the regulatory framework as the economy recovers and grows healthily. This Covid-19 crisis might in fact stop this trend and reinforce the importance of macroprudential regulation.

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Countercyclical capital buffers and regulatory discretion

One of the main regulations that banks have to comply with are capital requirements; in particular, banks need to hold a minimum amount of capital depending on the composition of their investments (assets). Actually, the use of the word “hold”, although quite common, is slightly misleading: capital is a source of funding for the bank—to be precise, an internal source of funding—so it is not something that banks hold, like cash. This short video discusses the concept.

There are several rationales for subjecting banks to such regulation. An obvious one is the fact that bank defaults (what happens when they run out of capital) impose very high costs to the economy; in other words, there are negative externalities that banks do not internalise. The way to design capital requirements, however, is far from obvious. In fact, just in 2007, right before the financial crisis, banks look sufficiently capitalised, at least according to the regulatory framework in place at that time. But they were not. Lack of liquidity, for instance, can lead to insolvency. Off-balance sheet exposures might become on-balance sheet very fast. Another lesson learned from the crisis was that risks build up during the boom and then materialise in the bust. Therefore, requirements should be increased during a boom—although it looks like risks are low—to protect the banking sector, and the real economy, when things go south.

One of the main new tools to deal with this time-varying dimension of financial risks is the Countercyclical Capital Buffer (CCyB). The idea is exactly as stated below: the macroprudential authority of the country should increase the buffer when the economy is doing well and reduce it in the opposite case. This post in the St. Louis Fed explains it well. For instance, right now, with the Covid-19 pandemic, is the moment to reduce it. The problem faced by many countries, however, is that they had not even activated in the first place. And this points towards a strong limitation of this tool that hopefully could be reformed in the near future.

As of October 2019, only 10 out of the 31 countries in Europe had positive CCyB. 6 of them had it at 1% or less. Only Sweden had a CCyB at its maximum level under European legislation, 2.5%, while Norway had it at 2%. UK had set it at 1%. The UK is, in fact, a good example to illustrate how the decisions to increase and decrease it are taken.

In its meeting in March 2016, the FPC—the macroprudential regulator in the UK—decided to increase the CCyB from 0% to 0.5%. Because it takes one year to become effective, the increase would take place in March 2017. However, after the EU referendum in June 2016, the FPC decided to bring it back to 0%. The reduction, contrary to the increase, is immediate. In other words, the CCyB never moved. There were no changes until July 2017, when the FPC increased it to 0.5% (effective July 2018) Then, in November 2017, it was decided to increase it to 1% (effective November 2018).

So what was the actual CCyB since January 2016 until March 2020? Well, it increased to 0.5% in July 2018 and to 1% in November 2018, coming back to 0% last month due to the pandemic. Hence, in the last four years, the UK had positive CCyB for just over a year and a half. And this in a period where credit was growing well…


… and lending spreads were at their lowest since the financial crisis.


And the UK is one of the (few) countries that appears interested in using this tool. This situation looks quite opposite to the stance that regulators took early in the Basel III discussion times. In December 2009, the BCBS published a document presenting the proposals from the committee to strengthen the resilience of the banking sector. One of the points was dedicated to reducing the pro-cyclicality of the financial sector.

The financial sector can be very pro-cyclical. What that means is that, during a boom, the growth of the economy if even higher since the financial sector provides cheap credit; however, during the bust, the recession is deeper because the financial sector stops lending and potentially hoards cash. It turns out that some parts of the banking regulation actually increase this pro-cyclicality. Hence, it appeared important to re-design some aspects of it as well as providing some tools to mitigate the pro-cyclicality.

Among the potential re-designs there are things such as making the minimum capital requirements—i.e., those that are not increased or decreased through the cycle—less pro-cyclical. Repullo and co-authors showed that capital requirements for the same mortgage portfolio can vary up to 50% through the cycle. Although some changes have been introduced in Basel III—for instance, input floors—which should reduce pro-cyclicality, this was not their main goal.

Another proposal was the use of dynamic provisioning. This is a regulation that was introduced in Spain in the year 2000, and even though it was not enough to fully protect the banking sector, the consensus is that it saved a substantial amount of tax-payer’s money. Unfortunately, this idea was dropped early on at Basel, likely due to the strong heterogeneity among member countries regarding provisioning practices.

At last, we ended up with just countercyclical capital buffers, and with sever limitations. The maximum amount is 2.5% over RWAs. Yet, banks face at least a 7% requirement at all times—plus any supervisory addition—so the CCyB represents at most increasing requirements by a third. Given the volatility of credit cycles, coupled with the huge costs from financial crises, it is strange that this requirement is less than, say, 50% of total requirements.

But the other limitation is probably more serious: national authorities have discretion over when to activate it. Although it is difficult to come up with a set of rules about when to raise or reduce it, discretion has led to most countries having it at 0% before the Covid-19 pandemic, even though several countries in the EU were growing relatively well in the recent years.

How different would have been if, say, the CCyB could go up to 4-5% of RWA and national authorities would be required to increase it when credit is growing well? Many banking regulators would have room to free up bank capital which could be used to keep lending to firms with problems to repay, even if this increases credit risk. The opposite of what we have.

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Moralities of everyday life

What is morality? Why do we feel disgust towards certain actions? Does everyone have a different morality? Should we be moral? How should we determine what is the moral thing to do? These and other questions are discussed in the course “Moralities of everyday life“, which can be taken for free in Coursera. The instructor is the wonderful Paul Bloom, Professor in Psychology at Yale. I knew Paul from his recurrent chats with Sam Harris at the Making Sense podcast first, and then from reading his book Against Empathy. But I have rediscovered him as a teacher, and a great one at that.

Bloom starts by introducing two main sides of the morality debate: utilitarians and Kantians. He does not talk much about Aristotle, which one could think of as the “third” camp, although he does mention him. He does a great job of mentioning the shortcomings of both approaches, although he, like me, is more in the utilitarian—or consequentialist—side. He talks about the role of emotions in morality, empathy, psychopathy, evolution of morality, …the course is extraordinarily rich, and I am only in Week 3 of 6.

The readings for the course are very interesting as well. While the lectures mention several scientific studies—I particularly like the one on how inducing disgust via smell leads to judging certain acts as less moral—the readings are more for a general audience. The authors are people such as Steven Pinker (who was his PhD advisor), Sam Harris (his Ted Talk on the Moral Landscape), Jonathan Haidt, Peter Singer, Dan Ariely, Jon Ronson, Richard Dawkins, Robert Wright, or Steve Levitt. All these authors are incredible communicators of science.

I cannot recommend this course enough. The first reason is because it is completely free; the second because some people might have a lot of time now that we can barely leave our homes. But the third and most important one is the need for us, humans, to understand where morality comes from; to understand why we feel outrage, why we see others as enemies; and to learn how to let this feeling subside and think about ethics and morality more rationally.

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