Economic Singularity Review

The Economic Singularity: Artificial intelligence and the death of capitalism .. This new book from best-selling AI writer Calum Chace argues that within a few decades, most humans will not be able to work for money.

A strong claim! This book mentions me by name 15 times, especially on my review of Martin Ford’s Rise of the Robots, wherein I complain that Ford’s main evidence for saying “this time is different” is all the impressive demos he’s seen lately. Even though this was the main reason given in each previous automation boom for saying “this time is different.” This seems to be Chace’s main evidence as well:

Faster computers, the availability of large data sets, and the persistence of pioneering researchers have finally rendered [deep learning] effective this decade, leading to “all the impressive computing demos” referred to by Robin Hanson in chapter 3.3, along with some early applications. But the major applications are still waiting in the wings, poised to take the stage. ..

It’s time to answer the question: is it really different this time? Will machine intelligence automate most human jobs within the next few decades, and leave a large minority of people – perhaps a majority – unable to gain paid employment? It seems to me that you have to accept that this proposition is at least possible if you admit the following three premises: 1. It is possible to automate the cognitive and manual tasks that we carry out to do our jobs. 2. Machine intelligence is approaching or overtaking our ability to ingest, process and pass on data presented in visual form and in natural language. 3. Machine intelligence is improving at an exponential rate. This rate may or may not slow a little in the coming years, but it will continue to be very fast. No doubt it is still possible to reject one or more of these premises, but for me, the evidence assembled in this chapter makes that hard.

Well of course it is possible for this time to be different. But, um, why can’t these three statements have been true for centuries? It will eventually be possible to automate tasks, and we have been slowly but exponentially “approaching” that future point for centuries. And so we may still have centuries to go. As I recently explained, exponential tech growth is consistent with a relatively constant rate at which jobs are displaced by automation.

Chace makes a specific claim that seems to me quite wrong.

Geoff Hinton – the man whose team won the landmark 2012 ImageNet competition – went further. In May 2015 he said that he expects machines to demonstrate common sense within a decade. .. Facebook has declared its ambition to make Hinton’s prediction come true. To this end, it established a basic research unit in 2013 called Facebook Artificial Intelligence Research (FAIR) with 50 employees, separate from the 100 people in its Applied Machine Learning team. So within a decade, machines are likely to be better than humans at recognising faces and other images, better at understanding and responding to human speech, and may even be possessed of common sense. And they will be getting faster and cheaper all the time. It is hard to believe that this will not have a profound impact on the job market.

I’ll give 50-1 odds against full human level common sense AI with a decade! Chace, I offer my $5,000 against your $100. Also happy to bet on “profound” job market impact, as I mentioned in my review of Ford. Chace, to his credit, sees value in such bets:

The economist Robin Hanson thinks that machines will eventually render most humans unemployed, but that it will not happen for many decades, probably centuries. Despite this scepticism, he proposes an interesting way to watch out for the eventuality: prediction markets. People make their best estimates when they have some skin in the forecasting game. Offering people the opportunity to bet real money on when they see their own jobs or other peoples’ jobs being automated may be an effective way to improve our forecasting.

Finally, Chace repeats Ford’s error in claiming economic collapse if median wages fall:

But as more and more people become unemployed, the consequent fall in demand will overtake the price reductions enabled by greater efficiency. Economic contraction is pretty much inevitable, and it will get so serious that something will have to be done. .. A modern developed society is not sustainable if a majority of its citizens are on the bread line.

Really, an economy can do fine if average demand is high and growing, even if median demand falls. It might be ethically lamentable, and the political system may have problems, but markets can do just fine.

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  • PandorasBrain

    Lots to disagree with in this review, Robin, but let’s not chase each other down those rabbit holes. Instead, I’ll take your odds. After all, it’s Geoff Hinton’s judgement you’re betting 50-1 against, not mine. Where do I sign? 🙂 Oh, and I know I owe you a review. I will get to it, I promise.

    • http://overcomingbias.com RobinHanson

      After July 23, 2026, we’ll judge if “full human level common sense AI” had been achieved by that date. Seems like that will be clear enough that you and I can bet on an honor system.

      • PandorasBrain

        I’m happy to trust you, Robin, but maybe we should appoint an impartial judge as to whether common sense has been achieved. Someone we both know and trust. David Wood?

      • http://overcomingbias.com RobinHanson

        I’m happy to accept David Wood as judge.

  • Joe

    “Will machine intelligence automate most human jobs within the next few decades, and leave a large minority of people – perhaps a majority – unable to gain paid employment? It seems to me that you have to accept that this proposition is at least possible if you admit the following three premises: 1. It is possible to automate the cognitive and manual tasks that we carry out to do our jobs. 2. Machine intelligence is approaching or overtaking our ability to ingest, process and pass on data presented in visual form and in natural language. 3. Machine intelligence is improving at an exponential rate.”

    A fourth premise, necessary for the stated conclusion yet not mentioned, is that what enables humans to be economically valuable is merely ‘our ability to ingest, process and pass on data presented in visual form and in natural language’. In other words, the ability to learn is all that matters. What Hanson calls ‘content’ – the product of learning, i.e. the ability to actually do a useful task – is not very important, as that’s really the easy part. Once you have an abstract intelligent agent you can relatively quickly train it to do whatever task you want done.

  • Robert Koslover

    Keynes anticipated that industrial/technological progress would ultimately eliminate our need to work. “Economic Possibilities for our Grandchildren (1930)”
    http://www.econ.yale.edu/smith/econ116a/keynes1.pdf

    • http://tinyurl.com/ogzkd6x Ricardo Cruz

      Keynes published a lot of great stuff. That was not a very interesting read. He just makes the observation, as many before and after him, that if productivity keeps increasing people in the future will be immensely rich. He doesn’t even try to identify from where productivity increases will come from. And he says that “within the next hundred years”, the economic problem may be solved. That will be 2030. Okay, let’s wait and see… hehe

  • Lord

    A large minority have always been out of the workforce but were usually wives. The problem is more that the skilled will be employed and married while the unskilled will tend to be unemployed and unmarried. While a fall in median wages needn’t cause market difficulties, they are more likely to when high earners see no reason to spend much being more than satisfied, see no reason to support low earners and the unemployed, and see no reason to invest, the skilled being fully employed and the unskilled without the income. It would be very difficult to keep average demand growing as a result. Growth in non profits and in skilled labor saving would be the main avenues for investment.

  • Shea

    It seems to me that “full human level common sense AI” could be a much higher standard than what Chace/Hinton were originally referring to. And it may well turn out that we don’t even need to get to “human level” common sense for AI to make a serious difference. Couldn’t a rudimentary level of common sense be enough to allow AIs to make profound dents in our economy?

    • http://overcomingbias.com RobinHanson

      I agree that full common sense is different criteria from “serious difference.”

  • http://tinyurl.com/ogzkd6x Ricardo Cruz

    A modern developed society is not sustainable if a majority of its citizens are on the bread line.

    What I don’t understand with this argument, which is not your quote but you don’t seem to disagree, is that I don’t understand how a majority of people could ever be unemployed unless very temporarily.

    If the majority is strangled out of the economy tomorrow, they would rapidly develop a economy of their own. Right?

    Faster computers, the availability of large data sets, and the persistence of pioneering researchers have finally rendered [deep learning] effective this decade

    This is a tangent, but when I first read this in my mobile phone I didn’t notice the persistence of pioneering researchers. I don’t see this point emphasized often enough. The main obstacle in deep learning for much time was the vanishing gradient problem. The series of techniques to overcome it made neural networks much faster to learn. Faster computers helped of course, and large datasets have motivated large companies to invest on deep learning. But it was mostly direct human ingenuity at the end of the day AFAIK.

    • http://invariant.org/ Peter Gerdes

      The majority of unemployed individuals will only develop an economy if the value they can offer through their labor is worth the unpleasantness of that labor.

      As long as (as seems likely) political expediency or moral concern causes society to offer some minimal monetary assistance to the unemployed it could well be that anything most people could make wouldn’t be worth the toil it took to make it. After all they would already have a very comfortable life with any items they desire and robots to perform menial tasks.

      Prostitution raises it’s head as an obvious form of employment but there has to be something of sufficient value to trade sex for…and there could always be good sex robots.

      • http://tinyurl.com/ogzkd6x Ricardo Cruz

        Obviously, if you give everybody a big unemployment pay-check then sure, they won’t work. At least not in the open market.

      • http://juridicalcoherence.blogspot.com/ Stephen Diamond

        What exactly is special about a majority? [What’s the highest percentage that could be unemployed?]

      • http://tinyurl.com/ogzkd6x Ricardo Cruz

        During the great depression, monetary authorities themselves caused deflation. There was poor understanding of economic phenomena such as sticky wages, so politicians passed laws which exacerbated the problem further. There were poor communication channels so people did not find ways to barter directly. None of this is true today.

        Are we to believe that, as robots produce tons of stuff, monetary authorities will just allow deflation and watch massive unemployment passively? Let’s say that’s true, on the day and age of fast communication, are we to believe that the majority of farmers, truck drivers, computer programmers, etc would not find a way to barter produce or just start trading under a crypto-currency? They would just cross their arms and die?

      • Peter David Jones

        Homo economicus won’t worrk if unemployment is well paid. Homo sapiens is a more complicated animal. Some people volunteer. Ie work for nothing for instance.

      • http://tinyurl.com/ogzkd6x Ricardo Cruz

        Homo economicus is a strawman that no economist believes in.

        This strawman started because economists believe in building simple models and then grow them. Obviously, the simplest of models do not have all the sophistication of homo sapiens.

        Anyhow, sure, I agree that depending on the unemployment paycheck and the work that they do, people may choose to continue working. We know that when people retire their health sometimes gets worse because they no longer feel useful. Unemployment is one of the most stressful and unhappy conditions that people report.

        But it was the person I was responding to me that was saying: artificial intelligence -> unemployment paycheck -> unemployment. I agreed with him, maybe a little hastily.

      • Peter David Jones

        I would like to live in a world where homo economicus is extinct. But I keep seeing evidence to the contrary.

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  • Alfred Differ

    Regarding the last quote and economic contraction, there is also a problem with the distinction between greater efficiency and improvements brought about from creative destruction. Growing bread lines might (but doesn’t have to) swamp price reductions from efficiency due to diminishing returns, but it is unclear that they must swamp price reductions brought about by innovation. It’s a black swan thing. Hard to predict.

  • Riothamus

    I am less interested in questions of capability, and more in questions of supply and generality.

    1. This wave of automation is software rather than hardware; this means simultaneously that there is effectively no limit to the supply and that employment doesn’t scale with adoption.

    2. The service sector tends to be more general in the skills it requires than agriculture or manufacturing. When software can completely replace a paralegal, the same or similar software is also able to do all the jobs a paralegal could do. This is distinct from robots who do a specific sequence of tasks in a specific setting, and allowed a laborer to move to a different environment and learn a different sequence of tasks for which there was no robot.

    So I expect automation to proceed exactly as fast as demand for it does, and also for it to automate whole skill sets instead of individual jobs. This implies a faster process than previous waves of automation. I have low confidence that our methods of discovering new ways to create value and of producing workers to implement them are experiencing a similar adjustment.

  • Mark Bahner

    “3. Machine intelligence is improving at an exponential rate.”

    That’s not a meaningful statement. The S&P 500 has been growing exponentially for more than 100 years. But it’s been less than 10% per year.

    In order to have a meaningful assessment, it’s necessary to say what the doubling time is, and how far behind machine intelligence is.