Tag Archives: Personal

My Two May Em Talks

You are invited to attend two unusual conferences where I’ll speak in May:

1. INSTED: Agitate! Los Angeles, May 2, 10am-10pm. $25 if you act fast. I talk at time TBD:

The Age Of Em: Envisioning Brain Emulation Societies

Tired of all the wining and boasting on the latest tech & politics trends? See it all shrink to insignificance as we contemplate the next revolution on the scale of the farming and industrial revolutions. The Age of Em will start sometime in the next century; in it, brain emulations could change almost everything.

2. Building The New World Conference, May 28-31, Radford University in Virginia,  $375 for 4 days includes food & room. I talk at 3:30pm May 30 on:

When Men Become Machines: Meaning, Identity, and Ethics at the Advent of a Trans-Human Era and Emulation-Based Singularity.

The three most disruptive transitions in history were the introduction of humans, farming, and industry. Another transition lies ahead: Artificial Intelligence in the form of whole brain emulations – “ems” – sometime in the next century. We will explore the upcoming Trans-Human Era, which will include ems, using a broad synthesis of standard academic consensus, and we will outline a baseline scenario for this “Singularity.” Lastly, we will consider not only the economics of this new world, but also the meaning and identity that human residents will experience during this unprecedented shift.

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‘About’ Isn’t About You

Imagine you told people:

  1. What looks like the sky above is actually the roof of a cave, and trees hold it up.
  2. The food we eat doesn’t give us nutrition; we get nutrition by rubbing rocks.
  3. The reason we wear clothes isn’t for modesty or protection from weather, but instead to keep cave frogs from jumping on our skin.

Imagine that you offered plausible evidence for these claims. But imagine further that people mostly took your claims as personal accusations, and responded defensively:

“Don’t look at me. I’ve always been a big supporter of trees, I’ve always warned against the dangers of frogs, and I make sure to rub rocks regularly.”

Other than being defensive, however, people showed little interest in these revelations. How would that make you feel?

That is how I feel about typical responses to my saying politics isn’t about policy, medicine isn’t about health, charity isn’t about helping, etc. People usually focus on proving that even if I’m right about others, they are the rare exceptions. They offer specific evidence on their personal behavior to prove that for them politics is about policy, medicine is about health, charity is about helping, etc. But aside from that, they show little interest in what such hypotheses might imply about the world in which they live. (They are, however, often eager to point out that I may have illicit motivations for pointing all this out.)

To which I respond: really, “X is not about Y” is not about you. Yes, your forager ancestors were hyper-sensitive to being singled out by public accusations of norm violations, and in fact much of our reasoning and story abilities may have evolved to help us defend against such accusations, and to make such accusations against others. So yes your instincts naturally push you to react this way.

But I’m talking about ways that we all violate the norms to which we all give lip service. I’m not trying to shame some of us, or even all of us, into trying harder to live up to our professed ideals. I’m focused first and foremost on making sense of our world. If I really believed that the sky might really be the roof of a cave held up by trees, or that we wear clothes to protect against frogs, I wouldn’t focus first on making sure that I was very publicly pro-tree and anti-frog; I’d instead ask what else I must rethink, given such revelations.

Once we better understand the basics of what we are doing in areas like policy, medicine, charity, etc. then we might start to ask if we should be doing more or less of those things, and if invoking norms, and shaming norm violators, will help or hurt on net. But first someone needs to figure out the basics of what we are doing in these areas of life. I implore some of you to join me in this noble quest.

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Oxford To Publish The Age Of Em

Eighteen months ago I asked here for readers to criticize my Em Econ book draft, then 62K words. (137 of you sent comments – thanks!) Today I announce that Oxford University Press will publish its descendant (now 212K words) in Spring 2016. Tentative title, summary, outline:

The Age Of Em: Envisioning Brain Emulation Societies

Author Robin Hanson takes an oft-mentioned disruptive future tech, brain emulations, and expertly analyzes its social consequences in unprecedented breadth and detail. His book is intended to prove: we can foresee our social future, not just by projecting trends, but also by analyzing the detailed social consequences of particular disruptive future technologies.

I. Basics
1. Start: Contents, Preface, Introduction, Summary
2. Modes: Precedents, Factors, Dreamtime, Limits
3. Mechanics: Emulations, Opacity, Hardware, Security
II. Physics
4. Scales: Time, Space, Reversing
5. Infrastructure: Climate, Cooling, Buildings
6. Existence: Virtuality, Views, Fakery, Copying, Darkness
7. Farewells: Fragility, Retirement, Death
III. Economics
8. Labor: Wages, Selection, Enough
9. Efficiency: Competition, Eliteness, Spurs, Power
10. Business: Institutions, Growth, Finance, Manufacturing
11. Lifecycle: Careers, Age, Preparation, Training
IV. Organization
12. Clumping: Cities, Speeds, Transport
13. Extremes: Software, Inequality, War
14. Groups: Clans, Nepotism, Firms, Teams
15. Conflict: Governance, Law, Innovation
V. Sociology
16. Connection: Mating, Signaling, Identity, Ritual
17. Collaboration: Conversation, Synchronization, Coalitions
18. Society: Profanity, Divisions, Culture, Stories
19. Minds: Humans, Unhumans, Intelligence, Psychology
VI. Implications
20. Variations: Trends, Alternatives, Transition, Aliens
21. Choices: Evaluation, Policy, Charity, Success
22. Finale: Critics, Conclusion, References, Thanks
23. Appendix: Motivation, Method, Biases

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Am I A Moralist?

Imagine that a “musicalist” is someone who makes good and persuasive musical arguments. One might define this broadly, by saying that any act is musical if it influences the physical world so as to change the distribution of sound, as most sound has musical elements. Here anyone who makes good and persuasive arguments that influence physical acts is a good “musicalist.”

Or one might try to define “musicalist” more narrowly, by requiring that the acts argued for have an especially strong effect on the especially musical aspects of the physical world, that musical concepts and premises often be central to the arguments. Far fewer people would be see as good “musicalists” here.

The concept of “moralist” can also be defined broadly or narrowly. Defined broadly, a “moralist” might be anyone who makes good and persuasive arguments about acts for which anyone thinks moral considerations to be relevant. This could be because the acts influence morally-relevant outcomes, or because the acts are encouraged or discouraged by some moral rules.

Defining narrowly, however, one might require that the acts influenced have especially strong moral impacts, and that moral concepts and premises often be central to the arguments. Far fewer people are good “moralists” by this definition.

Bryan Caplan recently praised me as a “moralist”:

Robin … excels as a moralist – in three distinct ways.

Robin often constructs sound original moral arguments.  His arguments against cuckoldry and for cryonics are just two that come to mind.  Yes, part of his project is to understand why most people are forgiving of cuckoldry and hostile to cryonics.  But the punchline is that the standard moral position on these issue is indefensible.

Second, Robin’s moral arguments actually persuade people.  I’ve met many of his acolytes in person, and see vastly more online.  This doesn’t mean, of course, that Robin’s moral arguments persuade most readers.  Any moral philosopher will tell you that changing minds is like pulling teeth.  My point is that Robin has probably changed the moral convictions of hundreds.  And that’s hundreds more than most moralists have changed.

Third, Robin takes some classical virtues far beyond the point of prudence.  Consider his legendary candor.

I accept (and am grateful for) Bryan’s praise relative to a broad interpretation of “moralist.” Yes, I try to create good and persuasive arguments on many topics relevant to actions, and according to many concepts of morality most acts have substantial moral impact. Since moral considerations are so ubiquitous, most anyone who is a good arguer must also be a good moralist.

But what if we define “moralist” narrowly, so that the acts must be unusually potent morally, and the concepts and premises invoked must be explicitly moral ones? In this case, I don’t see that I qualify, since I don’t focus much on especially moral concepts, premises, rules, or consequences.

Bryan gave two examples, and his readers gave two more. Here are quick summaries:

  • I argue that cryonics might work, that it only needs a >~5% of working to make sense, and that your wanting to do it triggers abandonment feelings in others exactly because they think you think it might work.
  • I argue that with simple precautions betting on terror acts won’t cause terror acts, but could help to predict and prevent such attacks.
  • I argue that the kinds of inequality we talk most about are only a small fraction of all inequality, but we talk about them most because they can justify us grabbing stuff that is more easily grabbed.
  • I argue that cuckoldry (which results in kids) causes many men great emotional and preference harm, plausibly comparable to the harm women get from being raped.

I agree that these arguments address actions about which many people have moral feelings. But I don’t see myself as focused on moral concepts or premises; I see my discussions as focused on other issues.

Yes, most people have moral wants. These aren’t all or even most of what people want, but moral considerations do influence what people (including me) want. Yes, these moral wants are relevant for many acts. But people disagree about the weight and even direction that moral considerations push on many of these acts, and I don’t see myself as especially good at or interested taking sides in arguments about such weights and directions. I instead mostly seek other simple robust considerations to influence beliefs and wants about acts.

Bryan seems to think that my being a good moralist by his lights argues against my “dealism” focus on identifying social policies that can get most everyone more of what they want, instead of taking sides in defined moral battles, wherein opposing sides make conflicting and often uncompromising demands. It seems to me that I in fact do work better by not aligning myself clearly with particular sides of established tug-o-wars, but instead seeking considerations that can appeal broadly to people on both sides of existing conflicts.

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Me At NIPS Workshop

Tomorrow I’ll present on prediction markets and disagreement, in Montreal at the NIPS Workshop on Transactional Machine Learning and E-Commerce. A video will be available later.

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Thank You GMU Econ!

Ten years ago today the GMU economics department voted to award me tenure. With that vote, I won my academic gamble. I can’t be sure what my odds reasonably were, so I can’t be sure it was a gamble worth taking. And I’m not sure tenure is overall good for the world. But I am sure that I’m very glad that I achieved tenure.

Many spend part of their tenure dividend on leisure. Many spend part on continuing to gain academic prestige as they did before. Many switch to more senior roles in the academic prestige game. And some spend tenure on riskier research agendas, agendas that are foolish for folks seeing tenure.

Though some may disagree, I see myself as primarily in this last category.  And since that would not be possible without tenure, I bow in sincere supplication, and thank my colleagues for this treasured honor. THANK YOU for my tenure.

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AI Boom Bet Offers

A month ago I mentioned that lots of folks are now saying “this time is different” – we’ll soon see a big increase in jobs lost to automation, even though we’ve heard such warnings every few decades for centuries. Recently Elon Musk joined in:

The risk of something seriously dangerous happening is in the five year timeframe … 10 years at most.

If new software will soon let computers take over many more jobs, that should greatly increase the demand for such software. And it should greatly increase the demand for computer hardware, which is a strong complement to software. So we should see a big increase in the quantity of computer hardware purchased. The US BEA has been tracking the fraction of the US economy devoted to computer and electronics hardware. That fraction was 2.3% in 1997, 1.7% in 2003, and 1.58% in 2008, and 1.56% in 2012. I offer to bet that this number won’t rise above 5% by 2025. And I’ll give 20-1 odds! So far, I have no takers.

The US BLS tracks the US labor share of income, which has fallen from 64% to 58% in the last decade, a clear deviation from prior trends. I don’t think this fall is mainly due to automation, and I think it may continue to fall for those other reasons. Even so, I think this figure rather unlikely to fall below 40% by 2025. So I bet Chris Hallquist at 12-1 odds against this (my $1200 to his $100).

Yes it would be better to bet on software demand directly, and on world stats, not just US stats. But these stats seem hard to find.

Added 3p: US CS/Eng college majors were: 6.5% in ’70, 9.7% in ’80, 9.6% in ’90, 9.4% in ’00, 7.9% in ’10. I’ll give 8-1 odds against > 15% by 2025. US CS majors were: 2.4K in ’70, 15K in ’80, 25K in ’90, 44K in ’00, 59K in ’03, 43K in ’10 (out of 1716K total grads). I’ll give 10-1 against > 200K by 2025.

Added 9Dec: On twitter @harryh accepted my 20-1 bet for $50. And Sam beats my offer: 

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On Stossel Tonight

I should be on tonight’s (9pm EST) episode of Stossel, on Fox Business TV, talking about biases.

Added 8Dec: I was wrong; the show should air Thursday Dec. 11

Added 28 Dec: Here is a video of the episode

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Hanson Loves Moose Caca

Warning: this post touches on sensitive topics.

In the movie “My Big Fat Greek Wedding,” when Toula was a little girl, she sat alone in the school cafeteria, frizzy haired, big nosed, and unpopular. The blonde girls at the next table asked her what she was eating, and Toula quietly said “moussaka.” The popular girls laughed cruelly, saying “Ewwww, ”moose caca!”” (more)

Imagine that those cruel girls had gone on to tell other kids “Toula says she loves to eat moose caca!” That is how I feel when Noah Smith says:

Why is it that the sciences look like a feminist nirvana compared with the economics profession, which seems to have a built-in bias that prevents women from advancing?

Consider this 2011 blog post by George Mason University economist Robin Hanson. Hanson writes that “gentle, silent rape” of a woman by a man causes less harm than a wife cuckolding her husband:

I [am puzzled] over why our law punishes rape far more than cuckoldry…[M]ost men would rather be raped than cuckolded…Imagine a woman was drugged into unconsciousness and then gently raped, so that she suffered no noticeable physical harm nor any memory of the event, and the rapist tried to keep the event secret…Now compare the two cases, cuckoldry and gentle silent rape.

There was no outcry whatsoever over these remarks, nor any retraction that I could find. (more)

Now I’ve admitted as far back as 2006 that academia, economics included, is biased against women. (Having been in both physics and computer science before, I doubt the situation is much worse in econ.) This one post of mine that Smith points to did induce many negative responses in comments and elsewhere, and of my thousands of blog posts I’d be surprised if much more than a dozen had induced any blog responses by economists whatsoever. And I suggested that we consider that the harms of rape and cuckoldry might be similar; I didn’t claim I knew one to be definitely larger.

But more fundamentally, Noah Smith is plenty smart enough to understand that I was not at all minimizing the harm of rape when I used rape as a reference to ask if other harms might be even bigger. Just as people who accuse others of being like Hitler do not usually intend to praise Hitler, people who compare other harms to rape usually intend to emphasize how big are those other harms, not how small is rape.

But I’m pretty sure Smith knows that. Yet, like the girls who taunted Toula, Smith finds it suits him better to pretend to misunderstand.

Added noon: Steve Sailer weighs in.

Added 2p: Noah Smith and I have been having a twitter conversation on this.

Added 4p: My topic was the relative harm of cuckoldry & rape. Noah Smith says that this topic itself is innately offensive to most women, who think cuckoldry to be of such low harm that comparing it with rape suggests rape to be low harm. He is further offended that I would talk on a topic if I knew it might offend in this way. I said his presuming cuckoldry is of very low harm offends the many men who think it very high harm. He disagrees that there are many such men, and would bet on a poll on the subject, but thinks it offensive to make such a poll, and won’t help with that.

Added 10a Sunday: Heartiste has a poll with over 3700 respondents so far on preferring rape or cuckoldry. Express your opinion there, or start a new poll somewhere.

Added Tuesday: Now Noah Smith wonders out loud if I’m a fake nerd, who pretends not to understand political correctness so I can have an excuse to offend people. Cause people so admire nerds that of course everyone wants to look like one …

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This Time Isn’t Different

~1983 I read two articles that inspired me to change my career. One was by Ted Nelson on hypertext publishing, and the other by Doug Lenat on artificial intelligence. So I quit my U. of Chicago physics Ph.D. program and headed to Silicon Valley, for a job doing AI at Lockheed, and a hobby doing hypertext with Nelson’s Xanadu group.

A few years later, ~1986, I penned the following parable on AI research:

COMPLETE FICTION by Robin Hanson

Once upon a time, in a kingdom nothing like our own, gold was very scarce, forcing jewelers to try and sell little tiny gold rings and bracelets. Then one day a PROSPECTOR came into the capitol sporting a large gold nugget he found in a hill to the west. As the word went out that there was “gold in them thar hills”, the king decided to take an active management role. He appointed a “gold task force” which one year later told the king “you must spend lots of money to find gold, lest your enemies get richer than you.”

So a “gold center” was formed, staffed with many spiffy looking Ph.D types who had recently published papers on gold (remarkably similar to their earlier papers on silver). Experienced prospectors had been interviewed, but they smelled and did not have a good grasp of gold theory.

The center bought a large number of state of the art bulldozers and took them to a large field they had found that was both easy to drive on and freeway accessible. After a week of sore rumps, getting dirty, and not finding anything, they decided they could best help the gold cause by researching better tools.

So they set up some demo sand hills in clear view of the king’s castle and stuffed them with nicely polished gold bars. Then they split into various research projects, such as “bigger diggers”, for handling gold boulders if they found any, and “timber-gold alloys’, for making houses from the stuff when gold eventually became plentiful.

After a while the town barons complained loud enough and also got some gold research money. The lion’s share was allocated to the most politically powerful barons, who assigned it to looking for gold in places where it would be very convenient to find it, such as in rich jewelers’ backyards. A few bulldozers, bought from smiling bulldozer salespeople wearing “Gold is the Future” buttons, were time shared across the land. Searchers who, in their alloted three days per month of bulldozer time, could just not find anything in the backyards of “gold committed” jewelers were admonished to search harder next month.

The smart money understood that bulldozers were the best digging tool, even though they were expensive and hard to use. Some backward prospector types, however, persisted in panning for gold in secluded streams. Though they did have some success, gold theorists knew that this was due to dumb luck and the incorporation of advanced bulldozer research ideas in later pan designs.

After many years of little success, the king got fed up and cut off all gold funding. The center people quickly unearthed their papers which had said so all along. The end.

P.S. There really was gold in them thar hills. Still is.

As you can see, I had become disillusioned on academic research, but still suffered youthful over-optimism on near-term A.I. prospects.

I’ve since learned that we’ve seen “booms” like the one I was caught up in then every few decades for centuries. In each boom many loudly declare high expectations and concern regarding rapid near-term progress in automation. “The machines are finally going to soon put everyone out of work!” Which of course they don’t. We’ve instead seen a pretty slow & steady rate of humans displaced by machines on jobs.

Today we are in another such boom. For example, David Brooks recently parroted Kevin Kelley saying this time is different because now we have cheaper hardware, better algorithms, and more data. But those facts were also true in most of the previous booms; nothing has fundamentally changed! In truth, we remain a very long way from being able to automate all jobs, and we should expect the slow steady rate of job displacement to long continue.

One way to understand this is in terms of the distribution over human jobs of how good machines need to be to displace humans. If this parameter is distributed somewhat evenly over many orders of magnitude, then continued steady exponential progress in machine abilities should continue to translate into only slow incremental displacement of human jobs. Yes machines are vastly better than they were before, but they must get far more vastly better to displace most human workers.

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