Monthly Archives: June 2016

My Questions For Bryan

In my continuing conversation with Bryan Caplan on my book, he had questions for me (on my moral evaluations), and now I have questions for him.

My main claim of expertise for the book is that I have taken a particular future tech scenario and analyzed its social consequences, by applying simple standard theories from many academic disciplines. (As we don’t have data on the future, theory drawn from prior data is all we have to go on.) Regarding that claim, I don’t want to be judged (much) on how likely you think is my scenario or what value you place on it. Instead, I want to be judged on the scope and accuracy of my forecasts, relative to this consensus academic theory standard.

My book makes hundreds of specific forecasts. For each one you could ask: if you accepted my key scenario premises, how consistent is my forecast with what simple standard consensus (i.e., widely accepted) academic theories would imply about that topic? You might also ask whether you personally believe my forecast, all things considered, but that is a different standard.

Obviously given hundreds of forecasts it should be easy for most anyone to find ones they see as mistaken, by either of these standards. But readers who merely hear that a critic has a few disagreements won’t know how reliable that critics rates the book overall. Which is why I’d like expert critics to imagine scoring me for accuracy on all of my predictions, averaging those scores into a total accuracy, and then ranking me, relative to other academics, on accuracy and scope.

That is, I’d like critics to imagine that we took a large random sample of other academics, say tenured professors in social science, and assigned each of them the task of applying standard simple consensus theory from many fields to forecast many social consequences for the em scenario. These academics are to make as many forecasts as they can where standard theory suggests forecasts have a substantially better than random chance of being correct.

Some academics would do well at this, and others not so well. But there’d be some overall distribution among these academics, for both the total accuracy of the forecasts they chose to make, and also some total number (or amount) of forecasts they could make at some reasonable level of accuracy.

So, finally, we get to my specific questions to Bryan (or to any other expert reviewer). Now that you’ve made very clear your moral posture, please answer:

Relative to tenured professors of social science who were hypothetically given my task, and considering average accuracy relative to simple standard academic theories, what do you estimate to be my percentile rank in 1) overall accuracy, and 2) the number (or amount) of forecasts?

(Feel free to substitute a different comparison group if that makes the task easier or more insightful.) That is, what fraction of academics would done a better job better than I?

Added 16 June: Bryan “answers“:

My answer: If you want to forecast the Age of Em, simple standard academic theories are not enough to even get started.  The entire analysis hinges on which people get emulated, and there is absolutely no simple standard academic theory of that.  If, as I’ve argued, we would copy the most robot-like people and treat them as slaves, at least 90% of Robin’s details are wrong.  That’s low accuracy even by academic standards; I’d put it at the 20th percentile of overall accuracy.

Wow. I can’t remotely see most of the book’s details depending  much on how “robot-like” are the dominant em personalities, at least within the usual human range of variation. For example, I can’t see how it matters for these: ease of fast population growth pushing wages low and growth high, speed dependence of the length of useful work careers before retirement, traffic congestion effects setting city sizes, virtual reality interaction delays depending on mind speeds, frequent use of spurs that work for just a few hours and then end or retire, and easier training via train a few copies and use many.

GD Star Rating

Prestige is Political

Imagine an ancient forager band had a conflict. For example, imagine some were eating foods that induced stinky farts which bothered others who slept nearby. There are several generic ways to deal with such a conflict:

  1. Force – someone strong might destroy the stinky foods, or threaten to beat up those who eat them.
  2. Deal – those bothered by the smell might compensate others for not eating stinky foods.
  3. Exit – those bothered by the smell might leave and find or form another band.
  4. Prestige – prestigious folks could push the idea that eating stinky foods is low prestige, to shame people into not eating them.

I think foragers had a strong preference for this last type of solution. But note that prestige is not available as a solution to conflicts unless prestige is in part political. If prestige were a fixed thing, say some fixed weighting of smart, strong, tall, etc., then it couldn’t be changed to solve problems. But if prestige is somewhat flexible, a dominant political coalition can try to flex it to encourage desired outcomes.

Now consider an analogous global conflict today, such as global warming. It seems to me that people also intuitively prefer a prestige solution. Instead of forming a world government powerful enough to impose its will, or making a deal where rich nations pay poor ones whatever it takes to get them to sign, what elite nations actually seem to be doing is visibly cutting back on carbon, and trying to shame other nations into following their lead. They’d rather risk failing to solve the problem than having to resort to a non-prestige solution. Arguably prestige is in part how world elites actually pushed for changes such as more democracy, less slavery, and better protected environments.

I’m also reminded of how people seem to prefer to choose their lawyers, doctors, investment advisors, etc. via prestige, instead of via track records or incentive contracts. And how people want to change who succeeds in the world via pushing elite colleges and institutions to change their admissions process, instead of reducing barriers to competition to make success more meritocratic.

There are two kinds of status, sometimes called “prestige” vs. “dominance.” Both exist, but on the surface at least we want the former to matter more than the latter. And we often seem to categorize gaining via trade or personal effort as gaining via dominance. Which is in part why we often dislike market based solutions. But note that these two kinds of status could also be called “politics” vs. “non-political reality”. We prefer social outcomes to be determined by prestige that can be influenced by dominant political coalitions, and fear and suspect social outcomes determined by nature, personal effort, or social competition, even when such competition is peaceful.

GD Star Rating
Tagged as: , ,

Star Trek As Fantasy

Frustrated that science fiction rarely makes economic sense, I just wrote a whole book trying to show how much consistent social detail one can offer, given key defining assumptions on a future scenario. Imagine my surprise then to learn that another book, Trekonomics, published exactly one day before mine, promises to make detailed economic sense out of the popular Star Trek shows. It seems endorsed by top economists Paul Krugman and Brad Delong, and has lots of MSM praise. From the jacket:

Manu Saadia takes a deep dive into the show’s most radical and provocative aspect: its detailed and consistent economic wisdom. .. looks at the hard economics that underpin the series’ ideal society.

Now Saadia does admit the space stuff is “hogwash”:

There will not be faster-than-light interstellar travel or matter-anti-matter reactors. Star Trek will not come to pass as seen on TV. .. There is no economic rationale for interstellar exploration, maned or unmanned. .. Settling a minuscule outpost on a faraway  world, sounds like complete idiocy. .. Interstellar exploration … cannot happen until society is so wealthy that not a single person has to waste his or her time on base economic pursuits. .. For a long while, there is no future but on Earth, in the cities of Earth. (pp. 215-221)

He says Trek is instead a sermon promoting social democracy: Continue reading "Star Trek As Fantasy" »

GD Star Rating
Tagged as: , ,

Wall Street Journal on Age of Em

In the Wall Street Journal, Daniel Levitin likes it a lot!

A very different—indeed startling—vision of the future .. What is remarkable about Mr. Hanson’s book is not just the detail with which he imagines this future but the way he situates it within a perceptive analysis of our human past and present. .. His is a dyspeptic-topia. It looks grim. ..

Mr. Hanson’s book is comprehensive and not put-downable. The author has thought of everything. He’s anticipated every one of my objections, including the manifestly unscientific one of how creepy this all sounds. He admirably explains the assumptions he’s making and the limitations. ..

The only weak point I find in the argument is that it seems to me that if we were as close to emulating human brains as we would need to be for Mr. Hanson’s predictions to come true, you’d think that by now we’d already have emulated ant brains, or Venus fly traps or even tree bark. ..

For my own part, I hope that the ems come soon. .. Even if you aren’t interested in the future, “The Age of Em” provides a wonderful overview of the current social psychology of productivity. .. For readers of this newspaper, a particularly interesting section discusses how free-market forces will change economic behaviors, negotiations, price-setting and fee structures. Mr. Hanson is an amiable narrator and guide to all these topics and more. We could use a few more of him.

GD Star Rating
Tagged as:

New Yorker on Age of Em

Joshua Rothman, in The New Yorker, on Age of Em:

It may be, too, that we should look with some trepidation toward the transitional period—that strange era in which our real-world ways will be disrupted by the introduction of new and bizarre simulated life forms. In “The Age of Em,” a nonfiction work of social-science speculation published earlier this year, the economist and futurist Robin Hanson describes a time in which researchers haven’t yet cracked artificial intelligence but have learned to copy themselves into their computers, creating “ems,” or emulated people, who quickly come to outnumber the real ones. Unlike Bostrom, who supposes that our descendants will create simulated worlds for curiosity’s sake, Hanson sees the business case for simulating people: instead of struggling to find a team of programmers, a company will be able to hire a single, brilliant em and then replicate her a million times. An enterprising em might gladly replicate herself to work many jobs at once; after she completes a job, a copied em might choose to delete herself, or “end.” (An em contemplating ending won’t ask “Do I want to die?,” Hanson writes, since other copies will live on; instead, she’ll ask, “Do I want to remember this?”) An em might be copied right after a vacation, so that whenever she is pasted into the simulated workplace, she is cheerful, rested, and ready to work. She might also be run on computer hardware that is more powerful than a human brain, and so think (and live) at a speed millions or even trillions of times faster than an ordinary human being.

Hanson doesn’t think that ems must necessarily live unhappy lives. On the contrary, they may thrive, fall in love, and find fulfillment in their competitive, flexible, high-speed world. Non-simulated people, meanwhile, may retire on the proceeds from their investments in the accelerated and increasingly autonomous em economy—a pleasant vantage point from which to observe the twilight of non-emulated civilization. Many people have imagined that technology will free us from the burden of work; if Hanson is right, that freedom could come through the virtualization of the human race.

This was in an article about the simulation argument. Two years ago I compared em and sim conversations, noting that in both cases many discuss using them as fiction settings, the chances that they are true, clues for inferring if they are true, and what they imply for identity, consciousness, physics, etc. But few discuss social consequences, such as how to live in a simulation or what a em world is like socially.

Oddly to me, Rothman didn’t go that direction; he didn’t even mention my (or anyone’s) analysis of how to live in a simulation.

Oh, and running trillions of times faster than humans is quite a bit faster than I’ve guessed; I’ve said maybe millions of times faster.

GD Star Rating
Tagged as: ,

Reply to Jones on Ems

In response to Richard Jones’ book review, I said:

So according to Jones, we can’t trust anthropologists to describe foragers they’ve met, we can’t trust economics when tech changes society, and familiar design principles fail for understanding brains and tiny chemical systems. Apparently only his field, physics, can be trusted well outside current experience. In reply, I say I’d rather rely on experts in each field, relative to his generic skepticism. Brain scientists see familiar design principles as applying to brains, even when designed by evolution, economists see economics as applying to past and distant societies with different tech, and anthropologists think they can understand cultures they visit.

Jones complained on twitter that I “prefer to argue from authority rather than engage with their substance.” I replied “There can’t be much specific response to generic skepticism,” to which he replied, “Well, there’s more than 4000 words of quite technical argument on the mind uploading question in the post I reference.” He’s right that he wrote 4400 words. But let me explain why I see them more as generic skepticism than technical argument.

For context, note that there are whole fields of biological engineering, wherein standard engineering principles are used to understand the engineering of biological systems. These include the design of many specific systems with organisms, such as lungs, blood, muscles, bone, and skin, and also specific subsystems within cells, and also standard behaviors, such as gait rhythms and foraging patterns. Standard design principles are also used to understand why cells are split into different modules that perform distinct functions, instead of having each cell try to contribute to all functions, and why only a few degrees of freedom for each cell matters for that cell’s contribution to its system. Such design principles can also be used to understand why systems are abstract, in the sense of as having only one main type of muscle, for creating forces used for many purposes, one main type of blood system, to move most everything around, or only one main fast signal system, for sending signals of many types.

Our models of the function of many key organs have in fact often enabled us to create functional replacements for them. In addition, we already have good models of, and successful physical emulations of, key parts of the brain’s input and out, such, as input from eyes and ears, and output to arms and legs.

Okay, now here are Jones’ key words:

This separation between the physical and the digital in an integrated circuit isn’t an accident or something pre-ordained – it happens because we’ve designed it to be that way. For those of us who don’t accept the idea of intelligent design in biology, that’s not true for brains. There is no clean “digital abstraction layer” in a brain – why should there be, unless someone designed it that way?

But evolution does design, and its designs do respect standard design principles. Evolution has gained by using both abstraction and modularity. Organs exist. Humans may be better in some ways than evolution at searching large design spaces, but biology definitely designs.

In a brain, for example, the digital is continually remodelling the physical – we see changes in connectivity and changes in synaptic strength as a consequence of the information being processed, changes, that as we see, are the manifestation of substantial physical changes, at the molecular level, in the neurons and synapses.

We have programmable logic devices, such as FPGAs, which can do exactly this.

Underlying all these phenomena are processes of macromolecular shape change in response to a changing local environment. .. This emphasizes that the fundamental unit of biological information processing is not the neuron or the synapse, it’s the molecule.

But you could make that same sort of argument about all organs, such as bones, muscles, lungs, blood, etc., and say we also can’t understand or emulate them without measuring and modeling them them in molecular detail. Similarly for the brain input/output systems that we have already emulated.

Determining the location and connectivity of individual neurons .. is necessary, but far from sufficient condition for specifying the informational state of the brain. .. The molecular basis of biological computation means that it isn’t deterministic, it’s stochastic, it’s random.

Randomness is quite easy to emulate, and most who see ems as possible expect to need brain scans with substantial chemical, in addition to spatial, resolution.

And that’s it, that is Jones’ “technical” critique. Since biological systems are made by evolution human design principles don’t apply, and since they are made of molecules one can’t emulate them without measuring and modeling at the molecular level. Never mind that we have actually seen design principles apply, and emulated while ignoring molecules. That’s what I call “generic skepticism”.

In contrast, I say brains are signal processing systems, and applying standard design principles to such systems tells us:

To manage its intended input-output relation, a signal processor simply must be designed to minimize the coupling between its designed input, output, and internal channels, and all of its other “extra” physical degrees of freedom. ..  To emulate a biological signal processor, one need only identify its key internal signal dimensions and their internal mappings – how input signals are mapped to output signals for each part of the system. These key dimensions are typically a tiny fraction of its physical degrees of freedom. Reproducing such dimensions and mappings with sufficient accuracy will reproduce the function of the system. This is proven daily by the 200,000 people with artificial ears, and will be proven soon when artificial eyes are fielded.

GD Star Rating
Tagged as: , ,

Caplan on Age of Em

As many have noted, ours in an era of ideological polarization. On topics where there are strong emotions, we tend to gravitate to extremes, and are less interest in intermediate positions. Which is a problem for my book; while most see it as too weird, others mostly see it as not weird enough. A  tech futurism minority expects to soon see very rapid progress in artificial intelligence and machine learning, and so see brain emulations as too slow and inefficient compared to the super-intelligence they foresee. And the majority to whom that seems pretty crazy also seem brain emulations as similarly crazy; they don’t care much if ems seem a bit less crazy.

At least future tech enthusiasts who think my book not weird enough are willing to write reviews to say so. But those who think my book too weird mostly stay silent; I’ve heard privately of many who were going to cover the book before they fully realized what it is about. So I thank my college Bryan Caplan for being willing to say what others won’t, in his critical review. His review is long, with ten criticisms. This response will also be long, going point by point.

Six of his ten objections seem to be mainly about my language. (His review is indented, and often contains book quotes; my replies are not.) Continue reading "Caplan on Age of Em" »

GD Star Rating
Tagged as: ,

Age of Em Criticism

My book’s topic seems to me so obviously important that I figure a reader’s main question must be whether he can trust me to actually know something on it. As a result, potential readers should be especially interested to hear criticisms; where do reviewers think my book gets it wrong? And as the book draws on many disciplines, readers should be especially interested in expert criticism, i.e., reviewers who find fault in an area they know well. Let us consider the reviews so far.

Three reviews so far can be seen as “main stream media.” At the Financial Times, journalist Sarah O’Connor calls the book “alluring” and “fascinating”, but notes that not everyone will accept the premise that ems are possible or “that current economic and social theories will hold in this strange new world.” However, the closest she gets to direct criticism is:

Some of the forecasts seem old-fashioned, like the notion that male ems will prefer females with “signs of nurturing inclinations and fertility, such as youthful good looks” while females will prefer males with “signs of wealth and status”.

At the Guardian, journalist Zoe Williams uses the book to direct readers to her critical question: “In a world without work, how do we distribute resources?” At Reason, journalist Ronald Bailey calls the book “fascinating”, and summarizes it in detail, but doesn’t otherwise evaluate it, other than to note that “other futurists have projected other pathways” that the future might take.

There are 2.5 reviews at widely read blogs. Economist Tyler Cowen likes the book, but cares less about its official topic than its indirect uses, such as a “Straussian commentary on the world we actually live in” and “A reminder of how strange everything is.” Economist Bryan Caplan has posted half of a review, on “What’s Right in Robin Hanson’s The Age of Em”; his other shoe has yet to drop.

Psychiatrist Scott Alexander really likes and highly recommends the book, though he worries that it is not weird enough, and he thinks I overstate my case on prior futurist accuracy. Alexander assigns low moral value to the scenario I describe, even though he sees it as full of happy complex creatures. He fears it will get even worse, leading to ems who are only ever focused on their particular work task, with no mind-wandering, breaks from work, or socializing.

There are also five reviews at other blogs. (There are also three reviews at Goodreads, and one more at Amazon, which don’t mention author expertise or offer field-specific criticisms.)

Futurist and computational neuroscientist Anders Sandberg calls the book a “very rich synthesis of many ideas with a high density of fascinating arguments,” but warns “most readers will disagree with large parts of it” and “many elements presented as uncontroversial will be highly controversial.” He himself only complains that I put in “too little effort bolstering the plausibility” of the basic idea of an emulation, a topic to which he has devoted in much effort.

Education reformer Neerav Kingsland calls the book “worth reading” though he would have rather I had written more fiction. He questions our ability to foresee the results of changes this big, and he questions my prediction of low wages: “Perhaps it would become taboo to replicate yourself, akin to teenage pregnancy?”

Private investor Peter McCluskey calls the book “quite valuable” though he notes my key assumptions could end up being wrong. He wishes I would have estimated wages relative to suspense more precisely, though he felt I was borderline overconfident overall, and thought I devoted too much attention to topics like swearing, relative to topics like democracy.

Economist Peter St Onge says “The pacing is fast, chock-full of interesting ideas to play with .. Hanson has done a fantastic job.” But he sees me as “too pessimistic” because the cost to run an em is very low compared to the cost to maintain a human today, and he just can’t see marginal product of human-like labor falling that low, no matter how many workers there are.

Physicist Richard Jones, in contrast, to the above nine reviewers, criticizes just about everything but my physics. He has long criticized Eric Drexler’s efforts to apply principles of mechanical engineering to tiny chemical systems. On Age of Em, he says:

Mind uploading .. will not be possible any time soon .. The brain .. is not the product of design, it is the product of evolution, and for this reason we can’t expect there to be such a digital abstraction layer. .. It would need to incorporate a molecularly accurate model of brain development and plasticity. .. His argument is that our understanding of human nature and the operations of human societies .. is now sufficiently robust that .. meaningful predictions can be made about the character of the resulting post-human societies. I don’t find this enormously convincing. .. Hanson often is simply unable to make firm predictions; this is commendably even-handed, but somewhat undermines his broader argument. .. How do we know what forager values actually were? Very few forager societies survived in any form into historical times, .. and what we know about their values is mediated by the biases of the anthropologists and ethnographers that recorded them.

So according to Jones, we can’t trust anthropologists to describe foragers they’ve met, we can’t trust economics when tech changes society, and familiar design principles fail for understanding brains and tiny chemical systems. Apparently only his field, physics, can be trusted well outside current experience. In reply, I say I’d rather rely on experts in each field, relative to his generic skepticism. Brain scientists see familiar design principles as applying to brains, even when designed by evolution, economists see economics as applying to past and distant societies with different tech, and anthropologists think they can understand cultures they visit.

Regarding O’Connor concerns on old-fashioned mate preferences I cited a literature on that, and regarding Alexander’s zero-leisure fears the book cites a literature on max productivity breaks and vacations. Regarding Kingsland and St Onge hopes for high wages, I’ll note that though most of history before the industrial era, taboos against having kids didn’t prevent marginal productivity from typically being very low.

So far I’d say that reviews give readers reasons to suspect my emphasis is at times off, but not strong reasons to fear that Age of Em is so wrong as to be not worth reading. But more reviews are yet to come.

GD Star Rating
Tagged as: ,