nhaliday + automation + contrarianism   19

The Hanson-Yudkowsky AI-Foom Debate - Machine Intelligence Research Institute
How Deviant Recent AI Progress Lumpiness?: http://www.overcomingbias.com/2018/03/how-deviant-recent-ai-progress-lumpiness.html
I seem to disagree with most people working on artificial intelligence (AI) risk. While with them I expect rapid change once AI is powerful enough to replace most all human workers, I expect this change to be spread across the world, not concentrated in one main localized AI system. The efforts of AI risk folks to design AI systems whose values won’t drift might stop global AI value drift if there is just one main AI system. But doing so in a world of many AI systems at similar abilities levels requires strong global governance of AI systems, which is a tall order anytime soon. Their continued focus on preventing single system drift suggests that they expect a single main AI system.

The main reason that I understand to expect relatively local AI progress is if AI progress is unusually lumpy, i.e., arriving in unusually fewer larger packages rather than in the usual many smaller packages. If one AI team finds a big lump, it might jump way ahead of the other teams.

However, we have a vast literature on the lumpiness of research and innovation more generally, which clearly says that usually most of the value in innovation is found in many small innovations. We have also so far seen this in computer science (CS) and AI. Even if there have been historical examples where much value was found in particular big innovations, such as nuclear weapons or the origin of humans.

Apparently many people associated with AI risk, including the star machine learning (ML) researchers that they often idolize, find it intuitively plausible that AI and ML progress is exceptionally lumpy. Such researchers often say, “My project is ‘huge’, and will soon do it all!” A decade ago my ex-co-blogger Eliezer Yudkowsky and I argued here on this blog about our differing estimates of AI progress lumpiness. He recently offered Alpha Go Zero as evidence of AI lumpiness:

...

In this post, let me give another example (beyond two big lumps in a row) of what could change my mind. I offer a clear observable indicator, for which data should have available now: deviant citation lumpiness in recent ML research. One standard measure of research impact is citations; bigger lumpier developments gain more citations that smaller ones. And it turns out that the lumpiness of citations is remarkably constant across research fields! See this March 3 paper in Science:

I Still Don’t Get Foom: http://www.overcomingbias.com/2014/07/30855.html
All of which makes it look like I’m the one with the problem; everyone else gets it. Even so, I’m gonna try to explain my problem again, in the hope that someone can explain where I’m going wrong. Here goes.

“Intelligence” just means an ability to do mental/calculation tasks, averaged over many tasks. I’ve always found it plausible that machines will continue to do more kinds of mental tasks better, and eventually be better at pretty much all of them. But what I’ve found it hard to accept is a “local explosion.” This is where a single machine, built by a single project using only a tiny fraction of world resources, goes in a short time (e.g., weeks) from being so weak that it is usually beat by a single human with the usual tools, to so powerful that it easily takes over the entire world. Yes, smarter machines may greatly increase overall economic growth rates, and yes such growth may be uneven. But this degree of unevenness seems implausibly extreme. Let me explain.

If we count by economic value, humans now do most of the mental tasks worth doing. Evolution has given us a brain chock-full of useful well-honed modules. And the fact that most mental tasks require the use of many modules is enough to explain why some of us are smarter than others. (There’d be a common “g” factor in task performance even with independent module variation.) Our modules aren’t that different from those of other primates, but because ours are different enough to allow lots of cultural transmission of innovation, we’ve out-competed other primates handily.

We’ve had computers for over seventy years, and have slowly build up libraries of software modules for them. Like brains, computers do mental tasks by combining modules. An important mental task is software innovation: improving these modules, adding new ones, and finding new ways to combine them. Ideas for new modules are sometimes inspired by the modules we see in our brains. When an innovation team finds an improvement, they usually sell access to it, which gives them resources for new projects, and lets others take advantage of their innovation.

...

In Bostrom’s graph above the line for an initially small project and system has a much higher slope, which means that it becomes in a short time vastly better at software innovation. Better than the entire rest of the world put together. And my key question is: how could it plausibly do that? Since the rest of the world is already trying the best it can to usefully innovate, and to abstract to promote such innovation, what exactly gives one small project such a huge advantage to let it innovate so much faster?

...

In fact, most software innovation seems to be driven by hardware advances, instead of innovator creativity. Apparently, good ideas are available but must usually wait until hardware is cheap enough to support them.

Yes, sometimes architectural choices have wider impacts. But I was an artificial intelligence researcher for nine years, ending twenty years ago, and I never saw an architecture choice make a huge difference, relative to other reasonable architecture choices. For most big systems, overall architecture matters a lot less than getting lots of detail right. Researchers have long wandered the space of architectures, mostly rediscovering variations on what others found before.

Some hope that a small project could be much better at innovation because it specializes in that topic, and much better understands new theoretical insights into the basic nature of innovation or intelligence. But I don’t think those are actually topics where one can usefully specialize much, or where we’ll find much useful new theory. To be much better at learning, the project would instead have to be much better at hundreds of specific kinds of learning. Which is very hard to do in a small project.

What does Bostrom say? Alas, not much. He distinguishes several advantages of digital over human minds, but all software shares those advantages. Bostrom also distinguishes five paths: better software, brain emulation (i.e., ems), biological enhancement of humans, brain-computer interfaces, and better human organizations. He doesn’t think interfaces would work, and sees organizations and better biology as only playing supporting roles.

...

Similarly, while you might imagine someday standing in awe in front of a super intelligence that embodies all the power of a new age, superintelligence just isn’t the sort of thing that one project could invent. As “intelligence” is just the name we give to being better at many mental tasks by using many good mental modules, there’s no one place to improve it. So I can’t see a plausible way one project could increase its intelligence vastly faster than could the rest of the world.

Takeoff speeds: https://sideways-view.com/2018/02/24/takeoff-speeds/
Futurists have argued for years about whether the development of AGI will look more like a breakthrough within a small group (“fast takeoff”), or a continuous acceleration distributed across the broader economy or a large firm (“slow takeoff”).

I currently think a slow takeoff is significantly more likely. This post explains some of my reasoning and why I think it matters. Mostly the post lists arguments I often hear for a fast takeoff and explains why I don’t find them compelling.

(Note: this is not a post about whether an intelligence explosion will occur. That seems very likely to me. Quantitatively I expect it to go along these lines. So e.g. while I disagree with many of the claims and assumptions in Intelligence Explosion Microeconomics, I don’t disagree with the central thesis or with most of the arguments.)
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april 2018 by nhaliday
Reid Hofmann and Peter Thiel and technology and politics - Marginal REVOLUTION
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february 2018 by nhaliday
The China Shock: Learning from Labor-Market Adjustment to Large Changes in Trade
Adjustment in local labor markets is remarkably slow, with wages and labor-force participation rates remaining depressed and unemployment rates remaining elevated for at least a full decade after the China trade shock commences. Exposed workers experience greater job churning and reduced lifetime income. At the national level, employment has fallen in the US industries more exposed to import competition, as expected, but offsetting employment gains in other industries have yet to materialize.

Slicing the Pie: Quantifying the Aggregate and Distributional Effects of Trade: http://www.nber.org/papers/w23737
We find that the China shock increases average welfare but some groups experience losses as high as five times the average gain. Adjusted for plausible measures of inequality aversion, gains in social welfare are positive and only slightly lower than with the standard aggregation.

The Surprisingly Swift Decline of US Manufacturing Employment: https://www.aeaweb.org/articles?id=10.1257/aer.20131578
- Justin R. Pierce, Peter K. Schott
This paper links the sharp drop in US manufacturing employment after 2000 to a change in US trade policy that eliminated potential tariff increases on Chinese imports. Industries more exposed to the change experience greater employment loss, increased imports from China, and higher entry by US importers and foreign-owned Chinese exporters. At the plant level, shifts toward less labor-intensive production and exposure to the policy via input-output linkages also contribute to the decline in employment. Results are robust to other potential explanations of employment loss, and there is no similar reaction in the European Union, where policy did not change.

China-Like Wages Now Part Of U.S. Employment Boom: https://www.forbes.com/sites/kenrapoza/2017/08/04/china-like-wages-now-part-of-u-s-employment-boom/

U.S. Companies Were Hurt by Trade With China Too: https://www.bloomberg.com/view/articles/2016-12-12/u-s-companies-were-hurt-by-trade-with-china-too
David Autor and David Dorn are two human wrecking balls smashing the edifice of economics consensus. For decades, the one big thing economists could agree on was that free trade, on balance, was good for the U.S. economy. Now, in a series of papers with a variety of co-authors, Autor and Dorn have shown that the dramatic increase in U.S. trade with China in the 2000s was a different and far more destructive beast -- a phenomenon commonly called the China Shock.

The first of these papers showed that the China Shock left deep and lasting scars on huge swathes of the American workforce. The second demonstrated that the China Shock increased political polarization. Now, together with Gordon Hanson, Pian Shu, and Gary Pisano, the wrecking-ball duo have a third paper, showing that the China Shock decreased U.S. corporate innovation.

Importing Political Polarization?: The Electoral Consequences of Rising Trade Exposure: http://economics.mit.edu/files/11499
Trade-exposed districts with an initial majority white population or initially in Republican hands became substantially more likely to elect a conservative Republican, while trade-exposed districts with an initial majority-minority population or initially in Democratic hands became more likely to elect a liberal Democrat.

The China Shock was Matched by a China Boom: http://marginalrevolution.com/marginalrevolution/2018/01/china-shock-matched-china-boom.html
Our results fit the textbook story that job opportunities in exports make up for jobs lost in import-competing industries, or nearly so. Once we consider the export side, the negative employment effect of trade is much smaller than is implied in the previous literature. Although our analysis finds net job losses in the manufacturing sector for the US, there are remarkable job gains in services, suggesting that international trade has an impact on the labour market according to comparative advantage. The US has comparative advantages in services, so that overall trade led to higher employment through the increased demand for service jobs.
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august 2017 by nhaliday
Assortive mating and income inequality | West Hunter
More than in the past, we have doctors marrying other doctors, rather than nurses, basically because of an increase in assortative mating for education. Ceteris paribus, this would tend to cause greater income equality among families. Is it the main driver of increasing income inequality?

Not at all. Most of the increase over the last 30 years has been among business executives and people working in finance. Since 1979, 58% of the expansion of income of the top 1% of households has this origin. For the top 0.1% of households, it’s been 67%.

...

Now I’m about to say something a little dangerous – so get your nitroglycerin pills ready.

Maybe those finance guys and CEOs are delivering enormously more value than they did in the 1950s!

For those remaining readers that haven’t died laughing, increased assortative mating probably has contributed to income inequality. Just not very much. Changes in the tax code, outsourcing, automation, smothering the board of directors in cream, and inattentive stockholders all matter more.

capital gains: https://westhunt.wordpress.com/2014/03/21/assortive-mating-and-income-inequality/#comment-24318
http://www.theamericanconservative.com/millman/assortative-mating-and-income-inequality/
Educational Homogamy and Assortative Mating Have Not Increased: http://sci-hub.tw/http://www.nber.org/papers/w22927.pdf
1960-2010, so all post WW2
https://twitter.com/whyvert/status/840379325908049920
Highly educated women partner more often “downwards” and medium educated women partner less often “upwards”
The new assortative mating (phenotypical, perhaps no change in genotypical assortative mating) due to women outnumbering men at university
If this means less genotypic assortative mating, then BAD NEWS: the smart fraction will shrink, and #decline will accelerate
Counterrevolutionary and reactionary elements warned it was a mistake to debauch higher education by over-expansion. Maybe they were right?
https://link.springer.com/article/10.1007/s10680-016-9407-z
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may 2017 by nhaliday
Sending Jobs Overseas
*The Great Convergence*: http://marginalrevolution.com/marginalrevolution/2016/11/the-great-convergence.html

Richard Baldwin on the New Globalization: https://marginalrevolution.com/marginalrevolution/2018/04/the-new-globalization.html
To really understand how this changed the nature of globalization, consider a sports analogy. Suppose we have two football teams, one that needs a quarterback but has too many linebackers, and one that needs a linebacker but has too many quarterbacks. If they sit down and trade players, both teams win. It’s arbitrage in players. Each team gets rid of players they need less of and gets players they need more of. That’s the old globalization: exchange of goods.

Now let’s take a different kind of exchange, where the coach of the better team goes to the field of the worse team and starts training those players in the off-season. This is very good for the coach because he gets to sell his knowledge in two places. You can be sure that the quality of the league will rise, all the games will get more competitive, and the team that’s being trained up will enjoy the whole thing. But it’s not at all certain that the players of the better team will benefit from this exchange because the source of their advantage is now being traded.

In this analogy, the better team is, of course, the G7, and not surprisingly this has led to some resentment of globalization in those countries. The new globalization breaks the monopoly that G7 labor had on G7 know-how…

good reviews here:
The Great Convergence: Information Technology and the New Globalization: https://www.amazon.com/Great-Convergence-Information-Technology-Globalization/dp/067466048X
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may 2017 by nhaliday
Educational Romanticism & Economic Development | pseudoerasmus
https://twitter.com/GarettJones/status/852339296358940672
deleeted

https://twitter.com/GarettJones/status/943238170312929280
https://archive.is/p5hRA

Did Nations that Boosted Education Grow Faster?: http://econlog.econlib.org/archives/2012/10/did_nations_tha.html
On average, no relationship. The trendline points down slightly, but for the time being let's just call it a draw. It's a well-known fact that countries that started the 1960's with high education levels grew faster (example), but this graph is about something different. This graph shows that countries that increased their education levels did not grow faster.

Where has all the education gone?: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.1016.2704&rep=rep1&type=pdf

https://twitter.com/GarettJones/status/948052794681966593
https://archive.is/kjxqp

https://twitter.com/GarettJones/status/950952412503822337
https://archive.is/3YPic

https://twitter.com/pseudoerasmus/status/862961420065001472
http://hanushek.stanford.edu/publications/schooling-educational-achievement-and-latin-american-growth-puzzle

The Case Against Education: What's Taking So Long, Bryan Caplan: http://econlog.econlib.org/archives/2015/03/the_case_agains_9.html

The World Might Be Better Off Without College for Everyone: https://www.theatlantic.com/magazine/archive/2018/01/whats-college-good-for/546590/
Students don't seem to be getting much out of higher education.
- Bryan Caplan

College: Capital or Signal?: http://www.economicmanblog.com/2017/02/25/college-capital-or-signal/
After his review of the literature, Caplan concludes that roughly 80% of the earnings effect from college comes from signalling, with only 20% the result of skill building. Put this together with his earlier observations about the private returns to college education, along with its exploding cost, and Caplan thinks that the social returns are negative. The policy implications of this will come as very bitter medicine for friends of Bernie Sanders.

Doubting the Null Hypothesis: http://www.arnoldkling.com/blog/doubting-the-null-hypothesis/

Is higher education/college in the US more about skill-building or about signaling?: https://www.quora.com/Is-higher-education-college-in-the-US-more-about-skill-building-or-about-signaling
ballpark: 50% signaling, 30% selection, 20% addition to human capital
more signaling in art history, more human capital in engineering, more selection in philosophy

Econ Duel! Is Education Signaling or Skill Building?: http://marginalrevolution.com/marginalrevolution/2016/03/econ-duel-is-education-signaling-or-skill-building.html
Marginal Revolution University has a brand new feature, Econ Duel! Our first Econ Duel features Tyler and me debating the question, Is education more about signaling or skill building?

Against Tulip Subsidies: https://slatestarcodex.com/2015/06/06/against-tulip-subsidies/

https://www.overcomingbias.com/2018/01/read-the-case-against-education.html

https://nintil.com/2018/02/05/notes-on-the-case-against-education/

https://www.nationalreview.com/magazine/2018-02-19-0000/bryan-caplan-case-against-education-review

https://spottedtoad.wordpress.com/2018/02/12/the-case-against-education/
Most American public school kids are low-income; about half are non-white; most are fairly low skilled academically. For most American kids, the majority of the waking hours they spend not engaged with electronic media are at school; the majority of their in-person relationships are at school; the most important relationships they have with an adult who is not their parent is with their teacher. For their parents, the most important in-person source of community is also their kids’ school. Young people need adult mirrors, models, mentors, and in an earlier era these might have been provided by extended families, but in our own era this all falls upon schools.

Caplan gestures towards work and earlier labor force participation as alternatives to school for many if not all kids. And I empathize: the years that I would point to as making me who I am were ones where I was working, not studying. But they were years spent working in schools, as a teacher or assistant. If schools did not exist, is there an alternative that we genuinely believe would arise to draw young people into the life of their community?

...

It is not an accident that the state that spends the least on education is Utah, where the LDS church can take up some of the slack for schools, while next door Wyoming spends almost the most of any state at $16,000 per student. Education is now the one surviving binding principle of the society as a whole, the one black box everyone will agree to, and so while you can press for less subsidization of education by government, and for privatization of costs, as Caplan does, there’s really nothing people can substitute for it. This is partially about signaling, sure, but it’s also because outside of schools and a few religious enclaves our society is but a darkling plain beset by winds.

This doesn’t mean that we should leave Caplan’s critique on the shelf. Much of education is focused on an insane, zero-sum race for finite rewards. Much of schooling does push kids, parents, schools, and school systems towards a solution ad absurdum, where anything less than 100 percent of kids headed to a doctorate and the big coding job in the sky is a sign of failure of everyone concerned.

But let’s approach this with an eye towards the limits of the possible and the reality of diminishing returns.

https://westhunt.wordpress.com/2018/01/27/poison-ivy-halls/
https://westhunt.wordpress.com/2018/01/27/poison-ivy-halls/#comment-101293
The real reason the left would support Moander: the usual reason. because he’s an enemy.

https://westhunt.wordpress.com/2018/02/01/bright-college-days-part-i/
I have a problem in thinking about education, since my preferences and personal educational experience are atypical, so I can’t just gut it out. On the other hand, knowing that puts me ahead of a lot of people that seem convinced that all real people, including all Arab cabdrivers, think and feel just as they do.

One important fact, relevant to this review. I don’t like Caplan. I think he doesn’t understand – can’t understand – human nature, and although that sometimes confers a different and interesting perspective, it’s not a royal road to truth. Nor would I want to share a foxhole with him: I don’t trust him. So if I say that I agree with some parts of this book, you should believe me.

...

Caplan doesn’t talk about possible ways of improving knowledge acquisition and retention. Maybe he thinks that’s impossible, and he may be right, at least within a conventional universe of possibilities. That’s a bit outside of his thesis, anyhow. Me it interests.

He dismisses objections from educational psychologists who claim that studying a subject improves you in subtle ways even after you forget all of it. I too find that hard to believe. On the other hand, it looks to me as if poorly-digested fragments of information picked up in college have some effect on public policy later in life: it is no coincidence that most prominent people in public life (at a given moment) share a lot of the same ideas. People are vaguely remembering the same crap from the same sources, or related sources. It’s correlated crap, which has a much stronger effect than random crap.

These widespread new ideas are usually wrong. They come from somewhere – in part, from higher education. Along this line, Caplan thinks that college has only a weak ideological effect on students. I don’t believe he is correct. In part, this is because most people use a shifting standard: what’s liberal or conservative gets redefined over time. At any given time a population is roughly half left and half right – but the content of those labels changes a lot. There’s a shift.

https://westhunt.wordpress.com/2018/02/01/bright-college-days-part-i/#comment-101492
I put it this way, a while ago: “When you think about it, falsehoods, stupid crap, make the best group identifiers, because anyone might agree with you when you’re obviously right. Signing up to clear nonsense is a better test of group loyalty. A true friend is with you when you’re wrong. Ideally, not just wrong, but barking mad, rolling around in your own vomit wrong.”
--
You just explained the Credo quia absurdum doctrine. I always wondered if it was nonsense. It is not.
--
Someone on twitter caught it first – got all the way to “sliding down the razor blade of life”. Which I explained is now called “transitioning”

What Catholics believe: https://theweek.com/articles/781925/what-catholics-believe
We believe all of these things, fantastical as they may sound, and we believe them for what we consider good reasons, well attested by history, consistent with the most exacting standards of logic. We will profess them in this place of wrath and tears until the extraordinary event referenced above, for which men and women have hoped and prayed for nearly 2,000 years, comes to pass.

https://westhunt.wordpress.com/2018/02/05/bright-college-days-part-ii/
According to Caplan, employers are looking for conformity, conscientiousness, and intelligence. They use completion of high school, or completion of college as a sign of conformity and conscientiousness. College certainly looks as if it’s mostly signaling, and it’s hugely expensive signaling, in terms of college costs and foregone earnings.

But inserting conformity into the merit function is tricky: things become important signals… because they’re important signals. Otherwise useful actions are contraindicated because they’re “not done”. For example, test scores convey useful information. They could help show that an applicant is smart even though he attended a mediocre school – the same role they play in college admissions. But employers seldom request test scores, and although applicants may provide them, few do. Caplan says ” The word on the street… [more]
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april 2017 by nhaliday
Secular Stagnation? The Effect of Aging on Economic Growth in the Age of Automation
Several recent theories emphasize the negative effects of an aging population on economic growth, either because of the lower labor force participation and productivity of older workers or because aging will create an excess of savings over desired investment, leading to secular stagnation. We show that there is no such negative relationship in the data. If anything, countries experiencing more rapid aging have grown more in recent decades. We suggest that this counterintuitive finding might reflect the more rapid adoption of automation technologies in countries undergoing more pronounced demographic changes, and provide evidence and theoretical underpinnings for this argument.
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january 2017 by nhaliday
In Computers We Trust? | Quanta Magazine
As math grows ever more complex, will computers reign?

Shalosh B. Ekhad is a computer. Or, rather, it is any of a rotating cast of computers used by the mathematician Doron Zeilberger, from the Dell in his New Jersey office to a supercomputer whose services he occasionally enlists in Austria. The name — Hebrew for “three B one” — refers to the AT&T 3B1, Ekhad’s earliest incarnation.

“The soul is the software,” said Zeilberger, who writes his own code using a popular math programming tool called Maple.
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january 2017 by nhaliday
The Membrane – spottedtoad
All of which is to say that the Internet, which shares many qualities in common with an assemblage of living things except for those clear boundaries and defenses, might well not trend toward increased usability or easier exchange of information over the longer term, even if that is what we have experienced heretofore. The history of evolution is every bit as much a history of parasitism and counterparasitism as it is any kind of story of upward movement toward greater complexity or order. There is no reason to think that we (and still less national or political entities) will necessarily experience technology as a means of enablement and Cool Stuff We Can Do rather than a perpetual set of defenses against scammers of our money and attention. There’s the respect that makes Fake News the news that matters forever more.

THE MADCOM FUTURE: http://www.atlanticcouncil.org/images/publications/The_MADCOM_Future_RW_0926.pdf
HOW ARTIFICIAL INTELLIGENCE WILL ENHANCE COMPUTATIONAL PROPAGANDA, REPROGRAM HUMAN CULTURE, AND THREATEN DEMOCRACY... AND WHAT CAN BE DONE ABOUT IT.

https://twitter.com/toad_spotted/status/984065056437653505
https://archive.is/fZLyb
ai robocalls/phonetrees/Indian Ocean call centers~biologicalization of corporations thru automation&global com tech

fly-by-night scams double mitotically,covered by outer membrane slime&peptidoglycan

trillion $ corps w/nonspecific skin/neutrophils/specific B/T cells against YOU

https://warontherocks.com/2019/08/the-coming-automation-of-propaganda/
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december 2016 by nhaliday
Overcoming Bias : Lognormal Jobs
could be the case that exponential tech improvement -> linear job replacement, as long as distribution of jobs across automatability is log-normal (I don't entirely follow the argument)

Paul Christiano has objection (to premise not argument) in the comments
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november 2016 by nhaliday

bundles : dismalityeconmetanoveltyprops

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