Tag Archives: Personal

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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The Elephant in the Brain

One of the most frustrating things about writing physical books is the long time delays. It has been 17 months since I mentioned my upcoming book here, and now, 8.5 months after we submitted the full book for review, & over 4 months after 7 out of 7 referees said “great book, as it is”, I can finally announce that The Elephant in the Brain: Hidden Motives in Everyday Life, coauthored with Kevin Simler, will officially be published January 1, 2018. Sigh. See summary & detailed outline at the book’s website.

A related sad fact is that the usual book publicity equilibrium adds to intellectual inequality. Since most readers want to read books about which they’ve heard much publicity lately from multiple sources, publishers try to concentrate publicity into a narrow time period around the official publication date. Which makes sense.

But to create that burst of publicity, one must circulate the book well in advance privately among “thought leaders”, who might blurb or review it, invite the authors to talk on it, or recommend it to others who might do these things. So people who plausibly fit these descriptions get to read such books long before others. This lets early readers seem to be wise judges of future popular talk directions. Not because they actually have better judgement, but because they get inside info.

Alas, I’m stuck in this same equilibrium. I have a full copy of my final book, except for minor copy-editing changes, and I can share it privately with possible publicity helpers. And when the relative cost to send an email is small relative to possible gains, a small chance may be enough. I’ll also give in to some requests based on friendship or prior help given me (as on my last book), especially when combined with promises to buy the book when it comes out.

But just as grading is the worst part of teaching, I hate being put in the role of bouncer, deciding who is cool enough to be let into my book club, or who has enough favors to trade. At least when teaching I’m expert in whatever topic I’m grading. But here I’m much less expert on deciding who can help book publicity. I’d really prefer the intellectual world to be more of an open competition without favoritism for those with inside connections. But here I am, forced to play favorites.

These are a few of the prices one pays today to publish books. But still, books remain an unparalleled way to call attention to ideas that need more space to explain than an article can offer. And for a relatively unknown author, established publishers still offer more attention than you could generate on your own. But maybe, just maybe, I can do something different with my third book, whatever that may be on.

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Trade Engagement?

First, let me invite readers, especially longtime/frequent readers, to suggest topics for me to blog on. I try to pick topics that are important, neglected, and where I can find something original and insightful to say. But I also like to please readers, and maybe I’m forgetting/missing topics that you could point out.

Second, many of my intellectual projects remain limited by a lack of engagement. I can write books, papers, and blog posts, but to have larger intellectual impact I need people to engage my ideas. Not to agree or disagree with them, but to dive into and critique the details of my arguments, and then publicly describe their findings. (Yes, journal referees engage submissions to some extent, but it isn’t remotely enough.)

This is more useful to me when such engagers have more relevant ability, popularity, and/or status. Since I also have modest ability, popularity, and status, at least in some areas, this suggests the possibility of mutually beneficial trade. I engage your neglected ideas and you engage mine. Of course there are many details to work out to arrange such trade.

First, there’s timing. I don’t want to put in lots of work engaging your ideas based on a promise that you’ll later engage mine, and then have you renege. So we may need to start small, back and forth. Or you can go first.

Second, there’s the issue of relative price. If we have differing levels of ability, popularity, and status, then we should agree to differing relative efforts to reflect those differences. If you are more able than I, maybe I should engage several ideas of yours in trade for your only engaging one of mine.

Third, we may disagree about our relevant differences. While it may be easy to quickly demonstrate one’s popularity, status, and overall intelligence, it can be harder to demonstrate one’s other abilities relevant to a particular topic. Yes if I read a bunch of your papers I might be able to see that your ability is higher than your status would suggest, but I might not have time for that.

Fourth, we may each fear adverse selection. Why should I be so stupid as to join a club that would stoop so low as to consider me as a member? The fact that you are seeking to trade for engagement, and willing to consider me as a trading partner, makes me suspect that your ideas, ability, and status are worse than they appear.

Fifth, we might prefer to disguise our engagement trade. When engagement is often a side effect of other processes, then it might look bad to go out of your way to trade engagements. (Trading engagement for money or sex probably looks even worse.) So people may prefer to hide their engagement trades within other process that give plausible deniability about such trades. I just happened to invite you to talk at my seminar series after you invited me to talk at yours; move along, no trade to see here.

These are substantial obstacles, and may together explain the lack of observed engagement trades. Even so, I suspect people haven’t tried very hard to overcome such obstacles, and in the spirit of innovation I’m willing to explore such possibilities, at least a bit. My neglected ideas include em futures, hidden motives, decision markets, irrational disagreement, mangled worlds, and more.

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My Play

In social play, an animal again waits until safe and satisfied, and feels pleasure from a large variety of safe behavior within a distinct space and time. The difference is that now they explore behavior that interacts with other animals, seeking equilibria that adjust well to changes in other animals’ behavior. (more)

Over the course of their lives Kahneman and Tversky don’t seem to have actually made many big decisions. The major trajectories of their lives were determined by historical events, random coincidences, their own psychological needs and irresistible impulsions. .. Their lives weren’t so much shaped by decisions as by rapture. They were held rapt by each other’s minds. (more)

When tested in national surveys against such seemingly crucial factors as intelligence, ability, and salary, level of motivation proves to be a more significant component in predicting career success. While level of motivation is highly correlated with success, importantly, the source of motivation varies greatly among individuals and is unrelated to success. (more)

In recent posts I said that play is ancient and robust, and I outlined what play consists of. I claimed that play is a powerful concept, but I haven’t supported that claim much. Today, I’ll consider some personal examples.

As a kid I was a severe nerd. I was beaten up sometimes, and for years spent each recess being chased around the school yard. This made me quite cautious and defensive socially. Later I was terrified of girls and acted cautiously toward them too, which they didn’t take as a positive sign. In college I gave up on girls for a while, and then was surprised to find women attracted by my chatting sincerely about physics at the physics club.

Being good at school-work, I was more willing to take chances there, and focused more on what interested me. In college when I learned that the second two years of physics covered the same material as the first two years, just with more math, I stopped doing homework and played with the equations instead, and aced the exams. I went to grad school in philosophy of science because that interested me at the time, and then switched back to physics because I’d found good enough answers to my philosophy questions.

I left school for silicon valley when topics out there sounded more interesting, and a few years later switched to only working 30 hours a week so I could spend more time studying what I wanted. I started a PhD program at age 34, with two kids aged 0 and 2, and allowed myself to dabble in many topics not on the shortest path to tenure. Post tenure I’ve paid even less attention to the usual career rewards. I choose as my first book topic not the most marketable, impressive, or important topic, but the one that would most suck me in with fascinating detail. (I’d heard half the authors with a book contract don’t finish a book.)

So I must admit that much of my personal success in life has resulted less from econ-style conscious calculation, and more from play. Feeling safe enough to move into play mode freed me enough from anxiety to get things done. And even though my goals in more playful modes tended more to cuteness, curiosity, and glory, my acts there better achieved my long term goals than has conscious planning toward such ends. Yes, I did moderate my playful urges based on conscious thought, and that probably helped overall. Even so, I must admit that my personal experience raises doubts about the value of conscious planning.

My experience is somewhat unusual, but I still see play helping a lot in the successes of those I know and respect. While conscious planning can at times be important, what tends to matter more is finding a strong motivation, any strong motivation, to really get into whatever it is you are doing. And to feel comfortable enough to just explore even if none of your options seem especially promising and you face real career and resource pressures.

Playful motives are near and myopic but strong, while conscious planning can be accurate but far. Near beats far it seems. I’ll continue to ponder play, and hopefully find more to say.

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10 Year Blog Anniversary

Ten years ago today this blog began with this post. Since then we’ve had 3,772 posts, 104 thousand comments, & over 15 million page views. This started as a group blog, and later became my personal blog, and I’ve been posting less the last few years as I focused on writing books.

I still have mixed feelings about putting in effort to write blog posts, relative to longer more academic articles and books. I agree that a blog post can communicate a useful and original insight in just a few paragraphs to thousands, while an academic article or book might be read by only tens or hundreds. But a much higher fraction of academic readers will try to build on my insight in a way that becomes part of our shared accumulating edifice of human insight. My hope is even if the fraction of blog readers who also do this is small, it is large enough to make a comparable total number. Because if not, I fear blogging is mostly a waste.

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Chronicle Review Profile

I’m deeply honored to be the subject of a cover profile this week in The Chronicle Review:


By David Wescott, the profile is titled Is This Economist Too Far Ahead of His Time?, October 16, 2016.

In academic journal articles where the author has an intended answer to a yes or no question, that answer is more often yes, and I think that applies here as well. The profile includes a lot about my book The Age of Em on a far future, and its title suggests that anyone who’d study a far future must be too far ahead of their time. But, when else would one study the far future other than well ahead of time? It seems to me that even in a rational world where everyone was of their time, some people would study other times. But perhaps the implied message is that we don’t live in such a world.

I’m honored to have been profiled, and broad ranging profiles tend to be imprecisely impressionistic. I think David Wescott did a good job overall, but since these impressions are about me, I’ll bother to comment on some (and signal my taste for precision). Here goes.

You inhabit a robotic body, and you stand roughly two millimeters tall. This is the world Robin Hanson is sketching out to a room of baffled undergraduates at George Mason University on a bright April morning.

Honestly, “baffled” is how most undergrads look to most professors during lectures.

Hanson is .. determined to promote his theories in an academy he finds deeply flawed; a doggedly rational thinker prone to intentionally provocative ideas that test the limits of what typically passes as scholarship.

Not sure I’m any more determined to self-promote than a typical academic. I try to be rational, but of course I fail. I seek the possibility of new useful info, and so use the surprise of a claim as a sign of its interestingness. Surprise correlates with “provocative”, and my innate social-cluelessness means I’ll neglect the usual social signs to “avoid this topic!” I question if I’m “intentionally provocative” beyond these two factors.

Hanson, deeply skeptical of conventional intellectual discourse,

I’m deeply skeptical of all discourse, intellectual or not, conventional or not.

At Caltech he found that economists based their ideas on simple models, which worked well in experiments but often failed to capture the complexities of the real world.

That is true of simple models in all fields, not just economics, and it is a feature not a bug. Models can be understood, while the full complexity of reality cannot.

But out of 3600 words, that’s all I have to correct, so good job David Wescott.

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Grace-Hanson Podcasts

Katja Grace and I recorded two more podcasts:

This adds to our nine previous podcasts:

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AI As Software Grant

While I’ve been part of grants before, and had research support, I’ve never had support for my futurist work, including the years I spent writing Age of Em. That now changes:

The Open Philanthropy Project awarded a grant of $264,525 over three years to Robin Hanson (Associate Professor of Economics, George Mason University) to analyze potential scenarios in the future development of artificial intelligence (AI). Professor Hanson plans to focus on scenarios in which AI is developed through the steady accumulation of individual pieces of software and leads to a “multipolar” outcome. .. This grant falls within our work on potential risks from advanced artificial intelligence, one of our focus areas within global catastrophic risks. (more)

Who is Open Philanthropy? From their summary:

Good Ventures is a philanthropic foundation whose mission is to help humanity thrive. Good Ventures was created by Dustin Moskovitz (co-founder of Facebook and Asana) and Cari Tuna, who have pledged to give the majority of their wealth to charity. .. GiveWell is a nonprofit that finds outstanding giving opportunities and publishes the full details of its analysis to help donors decide where to give. .. The Open Philanthropy Project is a collaboration between Good Ventures and GiveWell in which we identify outstanding giving opportunities, make grants, follow the results, and publish our findings.

A key paragraph from my proposal:

Robin Hanson proposes to take three years to conduct a broad positive analysis of the multipolar scenario wherein AI results from relatively steady accumulation of software tools. That is, he proposes to assume that human level AI will result mainly from the continued accumulation of software tools and packages, with distributions of cost and value correlations similar to those seen so far in software practice, in an environment where no one actor dominates the process of creating or fielding such software. He will attempt a mostly positive analysis of the social consequences of these assumptions, both during and after a transition to a world dominated by AI. While this is hardly the universe of all desired analyses, it does seem to cover a non-trivial fraction of interesting cases.

I and they see value in such an analysis even if AI software ends up differing systematically from the software we’ve seen so far:

While we do not believe that the class of scenarios that Professor Hanson will be analyzing is necessarily the most likely way for future AI development to play out, we expect his research to contribute a significant amount of useful data collection and analysis that might be valuable to our thinking about AI more generally, as well as provide a model for other people to follow when performing similar analyses of other AI scenarios of interest.

My idea is to extract from our decades of experience with software a more detailed description of the basic economics of software production and use. To distinguish, as time allows, many different kinds of inputs to production, styles of production, parts of produced products, and types of uses. And then to sketch out different rough “production functions” appropriate to different cases. That is, to begin to translate basic software engineering insight into economics language.

The simple assumption that software doesn’t fundamentally change in the future is the baseline scenario, to be fed into standard economic models to see what happens when such a more richly described software sector slowly grows to take over the economy. But a richer more detailed description of software economics can also give people a vocabulary for describing their alternative hypotheses about how software will change. And then this analysis framework can be adjusted to explore such alternative hypotheses.

So right from the start I’d like to offer this challenge:

Do you believe that the software that will let machines eventually do pretty much all jobs better than humans (or ems) will differ in foreseeable systematic ways from the software we have seen in the last seventy years of software practice? If so, please express your difference hypothesis as clearly as possible in terminology that would be understandable and familiar to software engineers and/or economists.

I will try to stretch the economic descriptions of software that I develop in the direction of encompassing the most common such hypotheses I find.

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Me Soon In Bay Area, DC, NYC

Folks near New York City, Washington DC, or the California Bay Area, consider seeing an upcoming Age of Em talk. (I’ll add more specific links as I get them.)

CA Bay Area

July 9, 10a-7p, Oakland, BIL Oakland
Aug 1, 1p, Mountain View, Benghazi Tech Talk, Google
Aug 2, 5p, Mountain View, RethinkDB
Aug 3, 7p, Oakland, Oakland Futurists
Aug 5-7, Berkeley, Effective Altruism Global
Aug 8, 7p, Palo Alto, Stanford Effective Altruism

Washington DC

July 23, 8a, World Future Society
July 26, 6p, Prosperity Caucus

New York City

July 12, 4:35p, Brooklyn, TTI/Vanguard
July 13, 7p, Brooklyn, Loft67

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