The Best Books of My 2015

I read about 125 books this year, and these are the ones that come to mind when I think of the word “best”. They are very different, and you won’t like all of them, but they all do something well.

To quote my book-review post from last year:

I’ve sorted this list into a series of “bests”: a Best Graphic Novel for people who like those, a Best Book About Selling Stuff for people who like those, and so on. Whoever you are, I’d probably recommend many of these books to you. And some of them are free!

For a list of every book I remember reading, check out my Goodreads account.

 

Best List of All the Books

These are in alphabetical order, save for the first four, which I liked most of all.

  1. Sapiens
  2. The Neapolitan Quartet (series, all four books)
  3. The Book of Disquiet
  4. Negima! Magister Negi Magi
  5. A Civil Action
  6. Azumanga Daioh
  7. Behind the Beautiful Forevers
  8. Digger (free!)
  9. Great (free!)
  10. Gone Girl
  11. Parable of the Sower
  12. Strangers Drowning
  13. Strong Female Protagonist (free!)
  14. The Road to Wigan Pier (free!)
  15. The Vision of the Anointed
  16. The Yale Book of Quotations
  17. Them: Adventures with Extremists
  18. We Learn Nothing

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The Good Judgment Project: My Experience

Are You Smarter Than a Coin-Flipping Monkey?

30 years ago, a man named Philip Tetlock decided to figure out whether the people we pay to make predictions about politics were actually good at predicting things.

He picked two hundred and eighty-four people who made their living “commenting or offering advice on political and economic trends,” and he started asking them to assess the probability that various things would or would not come to pass, both in the areas of the world in which they specialized and in areas about which they were not expert. Would there be a nonviolent end to apartheid in South Africa? Would Gorbachev be ousted in a coup? Would the United States go to war in the Persian Gulf?

–Louis Menand, Everybody’s An Expert

Tetlock’s discovery: On average, the commentators were slightly less accurate than a monkey flipping a coin with “yes” printed on one face and “no” on the other. They’d have been better off if they’d made completely random predictions!

What’s more, being an expert on a topic didn’t help much. At some point, more expertise even led to more faulty predictions.

 

Can We Do Any Better?

There are lots of reasons we make bad guesses about the future. But Philip Tetlock’s particular interest was in figuring out how to do better. 

Prediction, after all, is one of the most important things a person can ever do: Will I divorce this person if I marry them? Will I be happy in a year if I accept this job offer? It’s also an important skill for governments: How much will the Iraq War cost? Will this gun-control bill really lower the crime rate?

But if political experts aren’t good at prediction, who is?

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Privileging the Story // Do I Trust Journalism?

My friend Jack Newshama reporter on The Boston Globe, asked a good question on Facebook the other day:

Question for my non-journalist friends: why don’t you trust us? (“Us” being journalists in general. Because poll after poll shows that the overwhelming majority of you don’t.)

My answer turned out long enough for a blog post.

I trust journalists. That is, I trust most people, and I don’t see journalists as being very different from most people on average. I would trust a journalist to watch my laptop in a cafe while I used the bathroom or water my plants when I went on vacation.

Journalism isn’t a person. It is a product, produced by journalists. And as it is practiced, I only half-trust journalism.

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My Senior Thesis: How Can Great Charities Raise More Money?

I haven’t written a blog post for nearly a full season.

One-third of this phenomenon is the fault of my senior thesis:

Charitable Fundraising and Smart Giving: How can charities use behavioral science to drive donations?

It’s a very long thesis, and you probably shouldn’t read the whole thing. I conducted my final round of editing over the course of 38 hours in late April, during which I did not sleep. It’s kind of a slog.

Here’s a PDF of the five pages where I summarize everything I learned and make recommendations to charities:

The Part of the Thesis You Should Actually Read

 

In the rest of this post, I’ve explained my motivation for actually writing this thing, and squeezed my key findings into a pair of summaries: One that’s a hundred words long, one that’s quite a bit longer.

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Alpha Gamma Reviews: Edge 2015

Each year, Edge.org asks a few hundred very smart people how they’d answer a certain question. The results are always a mixed bag, but it’s one of the most exciting mixed bags in the intellectual world.

This year’s question dug into one of my own interests: “What do you think about machines that think?” 

In other words: What does the increasing power of artificial intelligence (AI) mean for humans, for the universe, and for the machines themselves? What will happen if and when AI becomes “general” or “superintelligent”, outperforming humans at almost every task?

The answers to this question would fill a book (and will, since Edge publishes one book each year). But even if you don’t have time to read a book, you should sample the content, because there’s always a ton of interesting material.

This post is my attempt to gather up some of the best answers and individual quotes, while addressing some of the mistakes that many different thinkers made.

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Seventeen Years of Amazon Shareholder Letters

On the advice of Bing Gordon, I recently spent an afternoon reading through the last 17 years’ worth of Amazon shareholder letters, written by the somewhat strange and mostly wonderful Jeff Bezos. This was an interesting experience; if you like entrepreneurship, or business in general, I highly recommend it!

Here are some of my favorite excerpts.

1997

Humble beginnings:

“We brought [customers] much more selection than was possible in a physical store (our store would now occupy 6 football fields).”

1998

“I constantly remind our employees to be afraid, to wake up every morning terrified. Not of our competition, but of our customers.”

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Life in the Slums of Liberia

I try to use raw statistics to get a sense of what life is like in other places. This helps me avoid the selective nature of stories, though stories have their place after the numbers are in.

Here, a startling overview from Chris Blattman et al, in a survey of young Liberian men thought to be engaged in criminal behavior:

“On average the men were age 25, had nearly eight years of schooling, earned about $40 in the past month working 46 hours per week (mainly in low skill labor and illicit work), and had $34 saved. 38% were members of an armed group during the two civil wars that ravaged the country between 1989 and 2003. 20% reported selling drugs, 44% reported daily marijuana use, 15% reported daily use of hard drugs, 53% reported stealing something in the past two weeks, and 24% reported they were homeless.”

Measuring the Measurement Error: A Method to Qualitatively Validate Sensitive Survey Data

The entire paper is worth reading, and quite readable. Turns out that people are very honest in answering survey questions about “sensitive” behaviors when those behaviors are the norm within their social groups.

(The paper also provides a good lens for looking at cash transfers. In the hands of a man with $34 in the bank, who earns $40 a month, $500 might be enough to prevent multiple acts of theft or purchase a stable home. On the other hand, I’d guess that these men are more likely to spend some of the money on hard drugs than are families in rural villages.)

Ten Big Questions

At a recent symposium, social scientists gathered to create a list of “big questions” that might serve as a driving focus for academics in the years to come—inspired in part by David Hilbert’s (largely successful) use of this technique to guide mathematicians.

More on the symposium here. The final list of questions is highly informal, but gives us a good idea of what problems are on the minds of very smart people:

1. How can we induce people to look after their health?

2. How do societies create effective and resilient institutions, such as governments?

3. How can humanity increase its collective wisdom?

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