Tag Archives: Personal

My Poll, Explained

So many have continued to ask me the same questions about my recent twitter poll, that I thought I’d try to put all my answers in one place. This topic isn’t that fundamentally interesting, so most you you may want to skip this post.

Recently, Christine Blasey Ford publicly accused US Supreme Court nominee Brett Kavanaugh of a sexual assault. This accusation will have important political consequences, however it is resolved. Congress and the US public are now put in the position of having to evaluate the believability of this accusation, and thus must consider which clues might indicate if the accusation is correct or incorrect.

Immediately after the accusation, many said that the timing of the accusation seemed to them suspicious, occurring exactly when it would most benefit Democrats seeking to derail any nomination until after the election, when they may control the Senate. And it occurred to me that a Bayesian analysis might illuminate this issue. If T = the actual timing, A = accurate accusation, W = wrong accusation, then how much this timing consideration pushes us toward final beliefs is given by the likelihood ratio p(T|W)/p(T|A). A ratio above one pushes against believing the accusation, while a ratio below one pushes for it.

The term P(T|A) seemed to me the most interesting term, and it occurred to me to ask what people thought about it via a Twitter poll. (If there was continued interest, I could ask another question about the other term.) Twitter polls are much cheaper and easier for me to do than other polls. I’ve done dozens of them so far, and rarely has anyone objected. Such polls only allow four options, and you don’t have many characters to explain your question. So I used those characters mainly to make clear a few key aspects of the accusation’s timing:

Many claimed that my wording was misleading because it didn’t include other relevant info that might support the accusation. Like who else the accuser is said to have told when, and what pressures she is said to have faced when to go public. They didn’t complain about my not including info that might lean the other way, such as low detail on the claimed event and a lack of supporting witnesses. But a short tweet just can’t include much relevant info; I barely had enough characters to explain key accusation timing facts.

It is certainly possible that my respondents suffered from cognitive biases, such as assuming too direct a path between accuser feelings and a final accusation. To answer my poll question well, they should have considered many possible complex paths by which an accuser says something to others, who then tell others people, some of which then chose when to bring pressure back on that accuser to make a public accusation. But that’s just the nature of any poll; respondents may well not think carefully enough before answering.

For the purposes of a Twitter poll, I needed to divide the range from 0% to 100% into four bins.
I had high uncertainty about where poll answers would lie, and for the purpose of Bayes rule it is factors that matter most. So I choose three ranges of roughly a factor of 4 to 5, and a leftover bin encompassing an infinite factor. If anything, my choice was biased against answers in the infinite factor bin.

I really didn’t know which way poll answers would go. If most answers were high fractions, that would tend to support the accusation, while if most answers were low fractions, that would tend to question the accusation. Many accused me of posting the poll in order to deny the accusation, but for that to work I would have needed a good guess on the poll answers. Which I didn’t have.

My personal estimate would be somewhere in the top two ranges, and that plausibly biased me to pick bins toward such estimates.  As two-thirds of my poll answers were in the lowest bin I offered, that suggests that I should have offered an even wider range of factors. Some claimed that I biased the results by not putting more bins above 20%. But that fraction is still below the usual four-bin target fraction of 25% per bin.

It is certainly plausible that my pool of poll respondents are not representative of the larger US or world population. And many called it is irresponsible and unscientific to run an unrepresentative poll, especially if one doesn’t carefully show which wordings matter how via A/B testing. But few complain about the thousands of other Twitter polls run every day, or of my dozens of others. And the obvious easy way to show that my pool or wordings matter is to show different answers with another poll where those vary. Yet almost no one even tried that.

Also, people don’t complain about others asking questions in simple public conversations, even though those can be seen as N=1 examples of unrepresentative polls without A/B testing on wordings. It is hard to see how asking thousands of people the same question via a Twitter poll is less informative than just asking one person that same question.

Many people said it is just rude to ask a poll question that insinuates that rape accusations might be wrong, especially when we’ve just seen someone going through all the pain of making one. They say that doing so is pro-rape and discourages the reporting of real rapes, and that this must have been my goal in making this poll. But consider an analogy with discussing gun control just after a shooting. Some say this is rude then to discuss anything but sympathy for victims, but others say this is exactly a good time to discuss gun control. I say that when we must evaluate a specific rape accusation is exactly a good time to think about what clues might indicate in what direction on whether this is an accurate or wrong accusation.

Others say that it is reasonable to conclude that I’m against their side if I didn’t explicitly signal within my poll text  that I’m on their side. That’s just the sort of signaling game equilibrium we are in. And so they are justified in denouncing me for being on the wrong side. But it seems a quite burdensome standard to hold on polls, which already have too few characters to allow an adequate explanation of a question, and it seems obvious that the vast majority of Twitter polls today are not in fact being held to this standard.

Added 24Sep: I thought the poll interesting enough to ask, relative to its costs to me, but I didn’t intend to give it much weight. It was all the negative comments that made it a bigger deal.

Note that, at least in my Twitter world, we see a big difference in attitudes between vocal folks who tweet and those who merely answer polls. That later “silent majority” is more skeptical of the accusation.

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Great Filter, 20 Years On

Twenty years ago today, I introduced the phrase “The Great Filter” in an essay on my personal website. Today Google says 300,000 web pages use this phrase, and 4.3% of those mention my name. This essay has 45 academic citations, and my related math paper has 17 cites.

These citations are a bit over 1% of my total citations, but this phrase accounts for 5% of my press coverage. This press is mostly dumb luck. I happened to coin a phrase on a topic of growing and wide interest, yet others more prestigious than I didn’t (as they often do) bother to replace it with another phrase that would trace back to them.

I have mixed feelings about writing the paper. Back then I was defying the usual academic rule to focus narrowly. I was right that it is possible to contribute to many more different areas than most academics do. But what I didn’t fully realize is that to academic economists non-econ publications don’t exist, and that publication is only the first step to academic influence. If you aren’t around in an area to keep publishing, giving talks, going to meetings, doing referee reports, etc., academics tend to correctly decide that you are politically powerless and thus you and your work can safely be ignored.

So I’m mostly ignored by the academics who’ve continued in this area – don’t get grants, students, or invitations to give talks, to comment on paper drafts, or to referee papers, grants, books, etc. The only time I’ve ever been invited to talk on the subject was a TEDx talk a few years ago. (And I’ve given over 350 talks in my career.) But the worst scenario of being ignored is that it is as if your paper never existed, and so you shouldn’t have bothered writing it. Thankfully I have avoided that outcome, as some of my insights have been taken to heart, both academically and socially. People now accept that finding independent alien life simpler than us would be bad news, that the very hard filter steps should be roughly equally spaced in our history, and that the great filter gives a reason to worry about humanity’s future prospects.

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My Market Board Game

From roughly 1989 to 1992, I explored the concept of prediction markets (which I then called “idea futures”) in part via building and testing a board game. I thought I’d posted details on my game before, but searching I couldn’t find anything. So here is my board game.

The basic idea is simple: people bet on “who done it” while watching a murder mystery. So my game is an add-on to a murder mystery movie or play, or a game like How to Host a Murder. While watching the murder mystery, people stand around a board where they can reach in with their hands to directly and easily make bets on who done it. Players start with the same amount of money, and in the end whoever has the most money wins (or maybe wins in proportion to their winnings).

Together with Ron Fischer (now deceased) I tested this game a half-dozen times with groups of about a dozen. People understood it quickly and easily, and had fun playing. I looked into marketing the game, but was told that game firms do not listen to proposals by strangers, as they fear being sued later if they came out with a similar game. So I set the game aside.

All I really need to explain here is how mechanically to let people bet on who done it. First, you give all players 200 in cash, and from then on they have access to a “bank” where they can always make “change”:

Poker chips of various colors can represent various amounts, like 1, 5, 10, 25, or 100. In addition, you make similar-sized cards that read things like “Pays 100 if Andy is guilty.” There are different cards for different suspects in the murder mystery, each suspect with a different color card. The “bank” allows exchanges like trading two 5 chips for one 10 chip, or trading 100 in chips for a set of all the cards, one for each suspect.

Second, you make a “market board”, which is an array of slots, each of which can hold either chips or a card. If there were six suspects, an initial market board could look like this:

For this board, each column is about one of the six suspects, and each row is about one of these ten prices: 5,10,15,20,25,30,40,50,60,80. Here is a blow-up of one slot in the array:

Every slot holds either the kind of card for that column, or it holds the amount of chips for that row. The one rule of trading is: for any slot, anyone can swap the right card for the right amount of chips, or can make the opposite swap, depending on what is in the slot at the moment. The swap must be immediate; you can’t put your hand over a slot to reserve it while you get your act together.

This could be the market board near the end of the game:

Here the players have settled on Pam as most likely to have done it, and Fred as least likely. At the end, players compute their final score by combining their cash in chips with 100 for each winning card; losing cards are worth nothing. And that’s the game!

For the initial board, fill a row with chips when the number of suspects times the price for that row is less than 100, and fill that row with cards otherwise. Any number of suspects can work for the columns, and any ordered set of prices between 0 and 100 can work for the rows. I made my boards by taping together clear-color M512 boxes from Tap Plastics, and taping printed white paper on tops around the edge.

Added 30Aug: Here are a few observations about game play. 1) Many, perhaps most, players were so engaged by “day trading” in this market that they neglected to watch and think enough about the murder mystery. 2) You can allow players to trade directly with each other, but players show little interest in doing this. 3) Players found it more natural to buy than to sell. As a result, prices drifted upward, and often the sum of the buy prices for all the suspects was over 100. An electronic market maker could ensure that such arbitrage opportunities never arise, but in this mechanical version some players specialized in noticing and correcting this error.

Added 31Aug: A twitter poll picked a name for this game: Murder, She Bet.

Added 9Sep: Expert gamer Zvi Mowshowitz gives a detailed analysis of this game. He correctly notes that incentives for accuracy are lower in the endgame, though I didn’t notice substantial problems with endgame accuracy in the trials I ran.

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Age of Em Paperback

Today is the official U.S. release date for the paperback version of my first book The Age of Em: Work, Love, and Life when Robots Rule the Earth. (U.K. version came out a month ago.) Here is the new preface:

I picked this book topic so it could draw me in, and I would finish. And that worked: I developed an obsession that lasted for years. But once I delivered the “final” version to my publisher on its assigned date, I found that my obsession continued. So I collected a long file of notes on possible additions. And when the time came that a paperback edition was possible, I grabbed my chance. As with the hardback edition, I had many ideas for changes that might make my dense semi-encyclopedia easier for readers to enjoy. But my core obsession again won out: to show that detailed analysis of future scenarios is possible, by showing just how many reasonable conclusions one can draw about this scenario.

Also, as this book did better than I had a right to expect, I wondered: will this be my best book ever? If so, why not make it the best it can be? The result is the book you now hold. It has over 42% more citations, and 18% more words, but it is only a bit easier to read. And now I must wonder: can my obsession stop now, pretty please?

Many are disappointed that I do not more directly declare if I love or hate the em world. But I fear that such a declaration gives an excuse to dismiss all this; critics could say I bias my analysis in order to get my desired value conclusions. I’ve given over 100 talks on this book, and never once has my audience failed to engage value issues. I remain confident that such issues will not be neglected, even if I remain quiet.

These are the only new sections in the paperback: Anthropomorphize, Motivation, Slavery, Foom, After Ems. (I previewed two of them here & here.)  I’ll make these two claims for my book:

  1. There’s at least a 5% chance that my analysis will usefully inform the real future, i.e., that something like brain emulations are actually the first kind of human-level machine intelligence, and my analysis is mostly right on what happens then. If it is worth having twenty books on the future, it is worth having a book with a good analysis of a 5% scenario.
  2. I know of no other analysis of a substantially-different-from-today future scenario that is remotely as thorough as Age of Em. I like to quip, “Age of Em is like science fiction, except there is no plot, no characters, and it all makes sense.” If you often enjoy science fiction but are frustrated that it rarely makes sense on closer examination, then you want more books like Age of Em. The success or not of Age of Em may influence how many future authors try to write such books.
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Our Book’s New Ground

In today’s Wall Street Journal, Matthew Hutson, author of The 7 Laws of Magical Thinking: How Irrational Beliefs Keep Us Happy, Healthy, and Sane, reviews our new book The Elephant in the Brain. He starts and ends with obligatory but irrelevant references to Trump. Quotes from the rest:

The book builds on centuries of writing about self-deception. … I can’t say that the book covers new ground, but it is a smart synthesis and offers several original metaphors. People self-deceive about lots of things. We overestimate our ability to drive. We conveniently forget who started an argument. … Much of what we do, including our most generous behavior, the authors say, is not meant to be helpful. We are, like many other members of the animal kingdom, competitively altruistic—helpful in large part to earn status. … Casual conversations, for instance, often trade in random information. But the point is not to trade facts for facts; what you are actually doing, the book argues, is showing off so people can evaluate your intellectual versatility. …

The authors take particular interest in large-scale social issues and institutions, showing how systems of collective self-deception help explain the odd behavior we see in art, charity, education, medicine, religion and politics. Why do people vote? Not to strengthen the republic. …. Instead, we cheer for our team and participate as a signal of loyalty, hoping for the benefits of inclusion. In education, as many economists have argued, learning is ancillary to accreditation and status. … In many areas of medicine, they note, increased care does not improve outcomes. People offer it to broadcast helpfulness, or demand it to demonstrate how much support they have from others.

“The Elephant in the Brain” is refreshingly frank and penetrating, leaving no stone of presumed human virtue unturned. The authors do not even spare themselves. … It is accessibly erudite, deftly deploying essential technical concepts. … Still, the authors urge hope. … There are ways to leverage our hidden motives in the pursuit of our ideals. The authors offer a few suggestions. … Unfortunately, the book devotes only a few pages to such solutions. “The Elephant in the Brain” does not judge us for hiding selfish motives from ourselves. And to my mind, given that we will always have selfish motives, keeping them concealed might even provide a buffer against naked strife. (more)

All reasonable, except maybe for “can’t say that the book covers new ground.” Yes, scholars of self-deception like Hutson will find plausible both our general thesis and most of our claims about particular areas of life. And yes those specific claims have almost all been published before. Even so, I bet most policy experts will call our claims on their particular area “surprising” and even “extraordinary”, and judge that we have not offered sufficiently extraordinary evidence in support. I’ve heard education policy experts say this on Bryan Caplan’s new book, The Case Against Education. And I’ve heard medicine policy experts say this on our medicine claims, and political system experts say this on our politics claims.

In my view, the key problem is that, to experts in each area, no modest amount of evidence seems sufficient support for claims that sound to them so surprising and extraordinary. Our story isn’t the usual one that people tell, after all. It is only by seeing that substantial if not overwhelming evidence is available for similar claims covering a great many areas of life that each claim can become plausible enough that modest evidence can make these conclusions believable. That is, there’s an intellectual contribution to make by arguing together for a large set of related contrarian-to-experts claims. This is what I suggest is original about our book.

I expect that experts in each policy area X will be much more skeptical about our claims on X than about our claims on the other areas. You might explain this by saying that our arguments are misleading, and only experts can see the holes. But I instead suggest that policy experts in each X are biased because clients prefer them to assume the usual stories. Those who hire education policy experts expect them to talk about better learning the material, and so on. Such biases are weaker for those who study motives and self-deception in general.

Hutson has one specific criticism:

The case for medicine as a hidden act of selfishness may have some truth, but it also has holes. For example, the book does not address why medical spending is so much higher in the U.S. than elsewhere—do Americans care more than others about health care as a status symbol?

We do not offer our thesis as an explanation for all possible variations in these activities! We say that our favored motive is under-acknowledged, but we don’t claim that it is the only motive, nor that motive variations are the only way to explain behavioral variation. The world is far too big and complex for one simple story to explain it all.

Finally, I must point out one error:

“The Elephant in the Brain,” a book about unconscious motives. (The titular pachyderm refers not to the Republican Party but to a metaphor used in 2006 by the social psychologist Jonathan Haidt, in which reason is the rider on the elephant of emotion.)

Actually it is a reference to common idea of “the elephant in the room”, a thing we can all easily see but refuse to admit is there. We say there’s a big one regarding how our brains work.

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When Disciplines Disagree

Our new book, The Elephant in the Brain, can be seen as taking one side in a disagreement between disciplines. On one side are psychologists (among others) who say of course people try to spin their motives as being higher than they are, especially in public forums. People on this side find our basic book thesis, and our many specific examples, so plausible that they fear our book may be too derivative and unoriginal.

On the other side, however, are most experts in concrete policy analysis. They spend their time studying ways that schools could help people to learn more material, hospitals could help people get healthier, charities could better assist people in need, and so on. They thus implicitly accept the usual claims people make about what they are trying to achieve via schools, hospitals, charities, etc. And so the practice of policy experts disagrees a lot with our claims that people actually care more about other ends, and that this is why most people show so little interest in reforms proposed by policy experts. (The world shows great interest in new kinds of physical devices and software, but far less interest in most proposed social reforms.)

My first book The Age of Em can also be seen as expressing disagreement between disciplines. In that book I try to straightforwardly apply standard economics to the scenario where brain emulations are the first kind of AI to displace most all human workers. While the assumption of brain-emulation-based-AI seems completely standard and reasonable among large communities of futurists and technologists, it is seen as radical and doubtful in many other intellectual communities (including economics). And many in disciplines outside of economics are quite skeptical that economists know much of anything that can generalize outside of our particular social world.

Now if you are going to make claims with which whole disciplines of experts disagree, you should probably feel most comfortable doing so when you have at least a whole discipline supporting you. Then it isn’t just you the crazy outlier against a world of experts. Even so, this sort of situation is problematic, in part because disagreements usually don’t become debates. A book on one side of a disagreement between disciplines is usually ignored by the disciplines who disagree. And the disciplines that agree may also ignore it, if the result seems too obvious to them to be worth discussing within their discipline.

This sort of situation seems to me one of the worse failings of our intellectual world. We fail to generate a consistent consensus across the widest scope of topics. Smaller communities of experts often generate a temporary consistent consensus within each community, but these communities often disagree a lot at larger scopes. And then they mostly just ignore each other. Apparently experts and their patrons have little incentive to debate those from other disciplines who disagree.

When two disciplines disagree, you might think they would both turn especially to the people who have become experts in both disciplines. But in fact those people are usually ignored relative to the people who have the highest status within each discipline. If we generated our consensus via prediction markets, it would automatically be consistent across the widest scope of topics. But of course we don’t, and there’s little interest in moving in that direction.

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Elephant in the Brain Reviews

Its now one week after the official hardback release date, and five weeks after the ebook release, of Elephant in the Brain. So I guess its time to respond to the text reviews that have appeared so far. Reviews have appeared at Amazon (9), Goodreads (8), and on individual blogs (5). Most comments expressed are quite positive. But there’s a big selection effect whereby people with negative opinions say nothing, and so readers rationally attend more to explicitly negative comments. And thus so will I. This post is looong. Continue reading "Elephant in the Brain Reviews" »

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Join The Debate

If you’ve laughed at “X is not about Y”, now is the time to take it seriously, as an equal.

Over the years, many seem to have found my “X is not about Y” arguments to be enjoyably mockable. As if I would be equally likely to say “Toasters are not about toast” or “Napkin holders are not about napkins.” Which seems to suggest that while my claims might be important if true, they are too silly to take seriously.

Now I don’t mind people having fun, but I do worry about the human habit to dismiss as unworthy of attention things that have been wittily mocked. (See the movie Ridicule.) If you worry about that too, and if you’ve at least smirked some at “X is not about Y” jokes, then perhaps I can appeal to your guilt or concern to take the time now to engage the argument.

Because as of today, you can download from Kindle for $22 (or Google for $14), the readable and carefully argued book The Elephant in the Brain: Hidden Motives in Everyday Life. by myself and Kevin Simler.

Now publishers and the media usually coordinate to talk about new books near the day when hardback copies are officially released. Which for our book is January 2. Usually ebooks are also withheld until near that date. As a result, usually the only people who can say much about a book at its official release date are elites who have been given special access to pre-release copies. Those who talk about a book weeks or months later are clearly revealed as less elites, and get less attention.

But now for our book all of you can participate more as equals in that release date book conversation. If you read our book now, and then publicly post a review or engage our argument near the release date, and indicate that you’d like us to publicly engage your response, then we will try to do so. When time is limited we will of course focus more on responses that we think are better argued. But we will try to engage as many of you as possible, without giving undue priority to media and other elites.

So please, go read, and then join our debate. Just how often is it plausible that “X is not about Y”?

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My TED/TEDx Talks

My TED video on Age of Em is finally out:

As you can see, the TED folks do great at video editing. I’m hoping this will attract more viewers than the 67K of my first TEDx talk on ems 4 years ago, and the 48K of my TEDx on the Great Filter 3 years ago. As I said back in May:

The TED community seems to come about as as close as I can realistically expect to my ideal religion.

I also have a great TEDx video on Elephant in the Brain: recorded just 3 weeks later:

Added 25 Aug: 280K views of my TED video in the first day!

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I’m In Europe This Week

Catch me at one of six talks I’ll give in Europe this week on Age of Em:

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