Fifteen Theses on “The Wealth of Humans” and “After Piketty”

Notes for the July 11, 2017 Research on Tap http://www.bradford-delong.com/2017/06/equitable-growth-research-on-tap-after-piketty-tue-jul-11-2017-at-500-pm.html event:

• Ryan Avent (2016): The Wealth of Humans: Work, Power, and Status in the Twenty-first Century http://amzn.to/2t9TtWe
• Heather Boushey, J. Bradford DeLong, and Marshall Steinbaum: After Piketty: The Agenda for Economics and Inequality http://amzn.to/2t9UI7y

Meditations on Ryan Avent:

Ryan Avent: What will happen to ‘The Wealth of Humans’? http://www.aei.org/publication/the-wealth-of-humans-a-qa-with-ryan-avent/: “This really dramatic technological change… the digital revolution… is adding hugely to the amount of effective labor that’s available to firms…. A lot of routine tasks in factories and in offices… [to] be automated…. High-skilled jobs… use these new technologies to do work that used to require a lot more people to do and in the process are displacing workers… enormous, abundant labor…. Employer[s] with… huge reservoir[s] of willing workers at very low wages… say…. “I don’t need to invest in this labor-saving technology…. replace my cashiers with automated checkout… replace the people moving boxes in the warehouse with robots”. And so you get this sort of self-limiting technological change…. The more powerful the digital revolution… the more people… looking for low-wage work… the less of an interest firms have in using machines to replace them…”

1. For the past thirty and the next thirty years—but probably not more—we are in all likelihood facing the increasing drift toward inequality driven by the rise of the Overclass as identified by Thomas Piketty. As long as the Overclass has enough control over the political system to manipulate it to reap enough rents to peg the rate of return on wealth—not physical capital, wealth—at 5%/year, we will see much if not all of the benefits from economic growth flowing to this Overclass, which will increasingly be an overclass of heirs and heiresses, rather than one that can claim that its wealth is due to some sort of meritocratic chops.

2. For the past ten years and the next ten years—if not more—our biggest and principal problem has been an economy in secular stagnation afflicted by slack demand, and that in a high -pressure economy like we had under Clinton in the late 1990s or Kennedy-Johnson in the 1960s, most of what we see as our economic problems would not melt completely away but be much reduced. Robots and artificial intelligence were overwhelmingly seen not as problems but as opportunities in the high-pressure economy of the later 1990s.

3. A generation ago we feared. But then we feared not the robot but the mainframe—and our fears of the mainframe then were like our fears of the robot now, save that while we now fear that robots will leave us with no work to do, we feared then that mainframes would leave us with no meaningful work to do and no work to do save being a mainframe-controlled dumb robot. As the Apple commercial said, we feared that 1984 would be like 1984: https://www.youtube.com/watch?v=2zfqw8nhUwA. Those fears were vastly overblown: we did not become robots subordinated to mainframes; instead, microcomputers and the internet became our personal intelligent tools.

4. The human brain is a massively parallel supercomputer that fits inside half a shoebox. It draws 50 watts of power. It is an amazing innovation, analysis, assessment and creation machine. 600 million years of proto-mammalian and mammalian evolution coupled with the genetic algorithm means that almost every single human can solve AI problems far beyond our current engineering reach—so much so that much of what our machines find impossible our brains find so trivially easy that we call such capabilities “unskilled”. When combined with our brains, human fingers are amazingly fine manipulation devices. And human back and leg muscles—especially when testosterone soaked—are quite good at moving heavy objects. Thus back in the environment of evolutionary adaptation, we used our brains, our big muscles, and our fingers to lead cognitively interesting—if stressful and short—lives.

5. Back in the environment of evolutionary adaptation, we used our brains, our big muscles, and our fingers to lead cognitively interesting—if stressful and short—lives. Short: life expectancy at brith of 25 or so. Stressful: watching relatively young people die around you all the time is a significant source of stress. And in order for the average woman to have two children who survive to reproduce, the average woman would have had to have three reach adulthood, about four reach the age of five, about six live births, and about nine pregnancies—that’s the average. Up until 250 years ago, the average woman spent about six years pregnant and eighteen years breastfeeding. Some more. Some less.

6. History has rolled forward since the hunter-gatherer age. And as history has rolled forward, we have figured out other things to do to add economic and sociological value than using our backs and legs to move things, our fingers to grasp things, and our brains to decide what to hunt and gather. Using backs to move heavy objects and our fingers to perform fine manipulations in cognitively-interesting ways has, relatively, declined.

7. As our use of our backs and fingers guided by our brains to create value has declined, we have turned to: (1) turning many of us into robots ourselves, performing simple routinized repetitive and vastly boring tasks to fill in the gaps in value chains between the robots that we know how to build; (2) jobs as microcontrollers for domesticated animals and machines—the horse does not know what plowing the furrow is—(3) finding jobs as relatively simple accounting and software bots, keeping track of stuff, what it is useful for, and how its use is to be decided; (4) becoming personal servitors; (5) becoming social engineers—trying to keep all those things and all those people—especially, perhaps, trying to keep those brains soaked in testosterone—somehow working in harmony, somehow pulling together, although admittedly with limited success; and (6) remaining innovators, analyzers, assessors, and creators as well.

8. Backs started to go out with the domestication of the horse. Fingers began to go out with the invention of the spinning jenny. But humans-as-microcontrollers, humans-as-accounting-‘bots—paper shufflers—and humans-as-the-robots we cannot yet build—took up all the job slack. Every horse needs a microcontroller. And a human brain was the only possible option. Even today, to a large amount every textile machine needs a human watching it at least part of the time. It doesn’t know when it’s gone wrong. It has no clue how to fix itself. It no more understands the idea of “fixing” any more than Alpha-Go understands that it is playing Go, and not just solving a problem of outputting a two-element vector in response to a 19 x 19 matrix of inputs with the additional structure that the output changes the matrix and that the possible matrices have a value-function structure.

9. Now, however, we can finally peer into a future in which the microcontrollers and the accounting bots are on their way out in a manner analogous to the backs and the fingers. But this is our future. This is not our present. For the past ten years and the next ten years—if not more—our biggest and principal problem has been an economy in secular stagnation afflicted by slack demand, and that in a high -pressure economy like we had under Clinton in the late 1990s or Kennedy-Johnson in the 1960s, most of what we see as our economic problems would not melt completely away but be much reduced.

10. What do we see when we peer into a future in which the microcontrollers and the accounting bots are on their way out in a manner analogous to the backs and the fingers? Fortunately, one thing this brings with it isthe forthcoming extinction of the the jobs that treat humans as simple robots: simple cogs in the machine that is Henry Ford’s River Rouge assembly line. Many occupations that vastly underutilize the massively parallel supercomputer that fits in half a shoebox are on the way out—and good: for those are not properly “human” jobs at all.

11. Not yet, but starting soon, and continuing for perhaps the next hundred years, we face the deep problem of the obsolescence of human brains as resources that can be employed—or, rather, underemployed—to create substantial economic value. Over the past six thousand years, ever since the domestication of the horse, we have seen the erosion, at first slowly and in the past two centuries rapidly, of the obsolescence of human muscles as resources that can be employed to create substantial economic value. But we have benefited because human brains underemployed—as microcontrollers for domesticated animals and machines, and as relatively simple accounting and software bots—have nevertheless been of great and increasing value. But now our microcontrollers are better microcontrollers than human brains, and our software accounting ‘bots are becoming better accounting ‘bots than human brains. Not next year, and not next decade, but further out by some unknown time, humans’ jobs will be as: personal servitors, social engineers, and innovators, analyzers, assessors and creators. Here we might well, someday, have a huge problem.

12. The market economy will amply fund AI research that replaces workers in capital intensive production processes by machines. Such industries have mammoth returns to scale. They thus tend to be characterized by large oligopolies. And so the firm that funds such labor-replacing research will capture with its own scale and in its own value chain a substantial part of the benefits of such R&D. That means that the combination of coming AI with a market economy might well be absolute poison for equity and equitable growth. It will race ahead with shedding workers in capital intensive production processes.

13. The market economy will not amply fund AI research that assists and amplifies workers in labor intensive production processes. Such tend to be small scale. The inventors and the innovators cannot capture even a small part of the benefit in their own production processes and value chains. And intellectual property is a very weak reed indeed to rely on to fix the problem—in fact, intellectual property is more likely to be the problem than the solution, cf. Nathan Myhrvold, and Intellectual Ventures.

14. The combination of coming AI with a market economy might well be absolute poison for equity and equitable growth. It will race ahead with shedding workers in capital intensive production processes. There will be—as Laura Tyson and Mike Spence pointed out in their contribution to Heather, Marshall, and my After Piketty book—a synergy between the dangers posed by the Rise of the Robots on the one hand and the inequality generating forces analyzed by Thomas Piketty in his Capital in the Twenty-First Century on the other.

15. Technological progress could rescue us from Pikettyian dystopia. Robots could be intelligent tools. AI could be gold for equity: amplifying the capabilities of workers in labor intensive production processes would, as John Maynard Keynes once said, bring us vastly closer to economic El Dorado. Recall how a generation ago we feared not the robot but the mainframe—and our fears of the mainframe then were like our fears of the robot now, save that while we now fear that robots will leave us with no work to do, we feared then that mainframes would leave us with no meaningful work to do and no work to do save being a mainframe-controlled dumb robot. As the Apple commercial said, we feared that 1984 would be like 1984. But we are unlikely to see a repeat of the microcomputer revolution. Firms will not invest on a large scale in AI that amplifies the capabilities of labor in labor intensive industries. It will not happen unless some NGO does. How about an engineering school? How about an engineering school at a public university?