Tag Archives: Personal

Join The DAGGRE Team

By Robin Hanson · August 31, 2011 11:55 pm · Comments (18)

A few weeks back Tyler Cowen posted an appeal from Philip Tetlock:

Starting in mid-2011, five teams will compete in a U.S.-government-sponsored forecasting tournament. Each team will develop its own tools for harnessing and improving collective intelligence and will be judged on how well its forecasters predict [government-chosen] major trends and events around the world over the next four years. … [We] will be one of the five teams competing – and we’d like you to consider joining our team as a forecaster.

You may have seen other teams’ appeals as well. Today I can announce that GMU hosts one of the five teams, please join us! Active participants will earn $50 a month, for about two hours of forecasting work. You can sign up here, and start forecasting as soon as you are accepted.

The government sponsor is IARPA (Intelligence Advanced Research Projects Activity), under the ACE (Aggregative Contingent Estimation) program, and our team is DAGGRE (Decomposition-Based Elicitation & Aggregation).

Our approach has three distinctive features, all visible to participants:

  1. We use an edit-based interface – a current consensus on all questions is visible to all participants, and any user may change any part. Each edit is scored on whether it moves the consensus closer to or further from the truth.  (This is equivalent to a market-maker-based prediction market).
  2. For each question IARPA assigns, we “decompose” it by adding related questions, and letting participants forecast both related questions and how they relate to the assigned questions. For example, users can assume answers to some questions, and then forecast other questions conditional on their assumptions. (This is equivalent to a combinatorial prediction market.)
  3. We will sometimes walk users through a special elicitation process that has been shown in field and lab experiments to produce more accurate estimates.

(Items #2,3 might not show for a week or two.) We are eager to see how our approach compares to the other approaches. Come get paid to help us find out!

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Me On FastForward

By Robin Hanson · August 31, 2011 10:00 pm · Comments (6)

I appear in this FastForward Radio interview with John Smart and Vanessa Miemis, supposedly on the distant future. It didn’t go that well. The interviewers asked the questions in the wrong order, first asking what we should do about “it” today in our personal lives, and then only at the end asking us what “it” is. And they didn’t really have us interact, but instead had us each answer the same questions in sequence.

Vanessa mainly seem to care more about expressing hope, caring, and that things must change, than about actually forecasting a distant future. John Smart expressed his view that current growth rates could continue indefinitely because, hey maybe we’ll use black holes well. But even if black holes let us square the available negentropy, that should only roughly double the time over which we could support exponential growth. As I’ve calculated:

An economy that doubled every century for a million years would grow by a factor of 103010. To support this using the 1070 atoms found within a million light years, each atom would have to support an average of 102950 people at our living standard, one person with a standard 102950 times higher, or some mix of those extremes.

To expect such a growth rate to continue for a billion or a trillion years, is well, crazy. Almost surely within a million years, and even more surely within a billion years, growth must greatly slow.

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What We Should Study

By Robin Hanson · August 24, 2011 2:30 pm · Comments (24)

Me a few days ago:

We usually explain human capacity to create and evaluate chains of reasoning in terms of [seeking] truth. … [But] once you give it a bit of thought, you can see many [other] possible and even plausible explanations.

More generally, we humans not only do things, we explain why we do things. Individuals and organizations stand ready to give reasons why we do each of the things we do. While such explanations are often self-serving, they are usually considered the standard default in ordinary conversation, popular media, and in academia.

I have a colleague here at GMU econ who recently expressed to me his feeling that we academics should usually accept such standard explanations unless we see clear strong evidence to the contrary. That is, if an academic journal has a statement of purpose or aim or mission, then we should believe what that statement says about the main social function of that journal in the world — if it says the journal exists to advance knowledge, that is what we should believe. He thinks we should similarly accept official purpose statements of hospitals, universities, charities, and government agencies. (He might not accept mission claims by firms, e.g., “Wal-Mart’s mission is to help people save money so they can live better”; apparently only admired non-profits deserve such deference.)

The most powerful insufficiently-appreciated insight I’ve ever learned is the one intellectual legacy I’d leave, if I could leave only one: we are often wrong about why we do things. Yes it is hardly original, and it might sound trivial, but few appreciate its full depth.

People are way too quick to assume that the main forces shaping the details of common human behaviors and institutions are their standard claimed missions. For example, people assume that the main force shaping doctors and hospitals is their declared mission to make people healthy, that the main force shaping universities and their research patrons is their declared the mission of advancing the frontiers of knowledge, that the main force shaping human capacities to make and evaluate reasons is the estimation of truth, and so on.

Once a social scientist starts to look seriously look for non-standard explanations, however, it is pretty easy to find them. Standard explanations leave many puzzling phenomena poorly explained, phenomena for which non-standard explanations often better account. Yes, there is an unfortunate tendency to latch onto the first plausible non-standard explanation one finds, instead of continuing to search for more possible explanations. I’ve probably been guilty of this myself, such as by perhaps focusing too much on signaling explanations.

But now I understand: today our priority should be a back-to-basics skeptical re-evaluation of human behavior.  That is, we should search for plausible non-standard explanations of our most common behaviors, even those we think “obvious,” and then seek simple matches between the simple robust predictions of each explanation and the puzzling phenomena we need to explain. I’m very interested in participating in such efforts, and uncertain about the best way to proceed.

Within academia, one important obstacle to this project is the tendency of “rigorous” folks like my colleague to insist that non-standard explanations are “extraordinary”, and so require “extraordinary” evidence. They aren’t worth much math modeling until stronger data support is offered, and they aren’t worth collecting much new data to test since they are not yet well supported. (Standard datasets, collected with standard explanations in mind, are usually poorly suited to this task.) Alas the first-cut math models and data analysis appropriate for this first stage of analysis tend to be poor places for academics to signal their math or statistics sophistication.

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My Stossel Clip

By Robin Hanson · August 20, 2011 8:45 pm · Comments (22)

My five minute pro-blackmail segment appeared on the Stossel show Thursday:

 

I gave a simple version of my gossip-plus argument. Alas they cut the part where I made it personal, telling John Stossel that, with legal blackmail, be would personally have to be more careful. A moment of delicious silence followed.

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New Scientist Contest

By Robin Hanson · August 16, 2011 5:30 pm · Comments (17)

New Scientist magazine set up a contest between new prediction techniques, including prediction markets:

We decided to see how the latest techniques would stand up to the task of predicting what people will buy. … Over the past four months, we have set four teams the task of trying to predict the sales of each issue of New Scientist, using some of the most promising and innovative approaches available. … Continue reading "New Scientist Contest" »

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Me On Good Morning America

By Robin Hanson · July 26, 2011 5:10 pm · Comments (11)

Tomorrow morning at 8a EST I’ll appear on ABC’s Good Morning America, talking about cryonics. [Added:] The part on cryonics is at minutes 28:30-33:45 here; I’m at 31:50-32:50. Just my episode can be found here:

Some quotes are here. The show has 4.6 million viewers! So I had about as many TV viewers today as I’ve had blog post visits ever.

Added: Britney Spears is apparently a new cryonics customer.

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Me in New Scientist on Sims

By Robin Hanson · July 25, 2011 4:45 pm · Comments (20)

New Scientist quotes me on the simulation argument:

Although we are unlikely to get proof, we might find some hints about our reality. “I think it might be feasible to get evidence that would at least give weak clues,” says Bostrom.

Economist Robin Hanson of George Mason University in Fairfax, Virginia, is not so sure. If we did find anything out, the operators could just rewind everything back to a point where the clue could be erased. “We won’t ever notice if they don’t want us to,” Hanson says. Anyway, seeking the truth might even be asking for trouble. We could be accused of ruining our creators’ fun and cause them to pull the plug.

Hanson has a slightly different take on the argument. “Small simulations should be far more numerous than large ones,” he says. That’s why he thinks it is far more likely that he lives in a simulation where he is the only conscious, interesting being. In other words, everyone else is an extra: a zombie, if you will. However, he would have no way of knowing, which brings us back to Descartes.

The reporter gets this a bit wrong. If I’m in simulation, I’m more likely to be in a small than a big simluation, but that is not to say I’d be “the only conscious, interesting being.” I’d guess most small simulations with any conscious beings have more than one – humans are social, and most of the interesting things to simulate about humans require more than one of them.

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Tests For Hedgehogs?

By Robin Hanson · July 20, 2011 10:25 am · Comments (8)

Philip Tetlock famously showed that hedgehogs, who focus on one main analytical tool, are less accurate than foxes, who used a wide assortment of analytical tools, on simple long-term forecasts in political economy.

Over at Cato Unbound, two famous hedgehogs recently replied to Tetlock. John Cochrane argued that no one can do well at the unconditional forecasts that Tetlock studied, but that hedgehogs shine at conditional forecasts, such as GDP change given a big stimulus. Bruce Bueno De Mesquita noted that his hedgehoggy use of game theory is liked by the CIA and by peer review.

Today at Cato Unbound, I note that since Tetlock’s data is hardly universal, that leaves room for counter-claims that he missed important ways in which hedgehogs are more accurate. But I find it disappointing, and also a bit suspicious, that neither Cochrane nor De Mesquita express interest in helping to design better studies, much less in participating in such studies. I note that “it is certainly possible to collect and score accuracy on conditional forecasts”, and conclude:

Research patrons eager to fund hedgehoggy research by folks like Cochrane and De Mesquita show little interest in funding forecasting competitions at the scale required to get public participation by such prestigious folks. So hedgehogs like Cochrane and De Mesquita can continue to claim superior accuracy, with little fear of being proven wrong anytime soon. All of which brings us back to our puzzling disinterest in forecast accuracy, which was the subject of my response.

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My Freak On Again

By Robin Hanson · July 10, 2011 11:00 pm · Comments (7)

A few weeks ago I posted on appearing at the end of a Freakonomics radio show on “The Folly Of Prediction.”  I now appear at the end of another Freakonomics radio show, this one on “Hey Baby, Is That a Prius You’re Driving?”, i.e., on signaling:

Managing our appearance is actually a lot of what we humans do. Trying to understand, business, trying to understand jobs, school, even medicine. If you don’t realize that people are trying to manage their image, you miss out on a lot of what’s going on.

I elaborate on how we economists signal:

Economists like to point out there’s almost no chance that your vote is going to determine an election. So one of the things an economists like to do to show off that they’re clever economists is to not vote and to say to everybody, hey I’m smarter than all the rest of you!  See, I understand that by voting, it’s not going to make any difference, anyway. And we do a little of that too often. Say, you might not tip at a restaurant because you say, you know I’m never come back to this restaurant again.  And so economists often think like that, they think through the strategy and they go out of their way of maybe being rude or a little thoughtless, in usual language, in order to show, hey I understand the strategy of this. I’ve got to admit, I do that sometimes. I tip at restaurants, I’ll tell you that, but still—

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Grace-Hanson Podcasts

By Robin Hanson · July 10, 2011 2:00 pm · Comments (9)

Katja Grace was in town recently, so she and I took the opportunity to start an occasional podcast series. Here are the first two episodes:

  1. Signaling
  2. Idealism

Alas we recorded the second one outside, with odd distracting noises, perhaps the wind.

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