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Outside of the charmed magic circle of western and central Europe, North America, and the other Anglo-Saxon settler colonies, few indeed are the economies that have managed successful economic development in the sense of convegence: materially closing any significant fraction of their productivity and living standards gap vis-a-vis the world's economic leaders. The Northeast Asian Pacific Rim, now including China; further south, Malaysia, Thailand, Indonesia, and Vietnam; India and Sri Lanka; elsewhere, Turkey, Chile, Botswana, Mauritius, and Cabo Verde. That is all. And with perhaps one or two exceptions, those few have followed the particular economic development path of using low-wage manufacturing exports to nurture their domestic communities of engineering practice—a path that is now closing.
It has long been easy to see the glass half-full with respect to global economic growth: technologies and organizational forms can be imitated and adopted, do diffuse, and even the poorer parts of the globe are much richer than they were two or one or even half a century ago. It has been much harder to see the glass half-full with respect to convergence: the catching-up and closing of the gap vis-a-vis the world's industrial leaders. Why have so few countries been able to walk the path? And what are our prospects for the future? With the prospective closing of the standard parth for convergence, seeing the glass half-full is becoming harder: perhaps there will be no glass at all.
Note to Self: On the one hand, we are worried because we know we are not terribly rational animals, and we know that big data can find correlations. We thus fear people will then use those correlations to hack our brains for their profit or advantage—and for our loss. we fear they will learn how to hack our brains to get us to think, say, do, or buy things that are not in accord with our best selves or our long-term goals—things that we will later on profoundly regret.
On the other hand, this morning, while I was waiting for my first appointment, I was served up nine bra ads—and not because I have desires to cross-dress that I have not yet admitted to myself. It was because Big Ad Data is not smart enough to figure out: "although this internet identity is associated with this credit card number, the person surfing the web right now is not the person who buys the bras"...
I confess I do not get this from Paul Krugman.
Yes, the trade deficit crowds-out traditionally-male blue-collar import-substituting manufacturing jobs, but imports crowd-in traditionally-male blue-collar wholesale trade jobs, and finance traditionally-male blue-collar construction (and capital-goods manufacturing) jobs. If you look at all traditionally-male blue-collar—wholesale, construction, manufacturing, and mining)–what you get is not a story of the trade deficit, but rather a story of (a) macro shocks to aggregate demand, and (b) the long-run technology-and-preferences trend—some of which is automation.
NAFTA is nowhere.
The 2002-2007 bilateral-trade "China shock" is simply not a terribly big deal for the country as a whole: employment in traditionally-male blue-collar occupations was flat. A big deal for places that found their manufactures competing with new imports from China, yes. But not for blue-collar traditionally-male employment in the country as a whole.
For the country as a whole, it is aggregate demand—2001-3 recession, weak recovery, 2007-9 catastrophe, and then superweak recovery—with a supporting role for technology-and-preferences:
Paul Krugman: "Yang asserts that automation destroyed lots of manufacturing in the midwest, [but] you don't have to be a protectionist to realize that the acceleration of job loss after 2000 was mainly about the surging trade deficit:
No Longer Fresh at Project Syndicate: Robo-Apocalypse? Not in Your Lifetime: "Will the imminent “rise of the robots” threaten all future human employment? The most thoughtful discussion of that question can be found in MIT economist David H. Autor’s 2015 paper, “Why Are There Still so Many Jobs?”, which considers the problem in the context of Polanyi’s Paradox. Given that “we can know more than we can tell,” the twentieth-century philosopher Michael Polanyi observed, we shouldn’t assume that technology can replicate the function of human knowledge itself. Just because a computer can know everything there is to know about a car doesn’t mean it can drive it. This distinction between tacit knowledge and information bears directly on the question of what humans will be doing to produce economic value in the future... Read MOAR at Project Syndicate
Live at Project Syndicate: Robo-Apocalypse? Not in Your Lifetime: "Will the imminent “rise of the robots” threaten all future human employment? The most thoughtful discussion of that question can be found in MIT economist David H. Autor’s 2015 paper, “Why Are There Still so Many Jobs?”, which considers the problem in the context of Polanyi’s Paradox. Given that “we can know more than we can tell,” the twentieth-century philosopher Michael Polanyi observed, we shouldn’t assume that technology can replicate the function of human knowledge itself. Just because a computer can know everything there is to know about a car doesn’t mean it can drive it. This distinction between tacit knowledge and information bears directly on the question of what humans will be doing to produce economic value in the future... Read MOAR at Project Syndicate
Note to Self: Comment on Richard Baldwin: The Globotics Upheaval: Globalization, Robotics, and the Future of Work: Start from the observation the the human brain is a massively-parallel supercomputer that fits inside a breadbox and draws 50 watts of power.
For 6,000 years, since the domestication of the horse, human backs, human thighs, and human fingers have becoming less powerful as sources of economic value, as animals and machines have increasingly competed with and substituted for them. Up until recently, however, every domesticated animal every machine had required a microprocessor. And the highly-productive decentralized societal division of labor of enormous extent created huge and increasing amounts of need for white-collar information processing: the accounting, control, transmission of information, and purveyance of misinformation jobs that are most of what people like us here do. Thus while human backs and thighs and fingers became less powerful as sources of economic value as time passed, human brains become more valuable. But now we have robots which contain their own microprocessors, and software 'bots that handle huge amounts of the white-collar information processing. So the job-creating aspects of technological creative destruction are now open to question
From this standpoint, we can worry along either of two dimensions:
I Want to Take a Virtual Course on the Public Sphere in the Age of Costless Electronic Reproduction. What Should I Read?
Five things to start off the reading list:
This is hugely double-plus unhood. You would think Facebook would be more careful these days: Jeremy B. Merrill: Facebook Moves to Block Ad Transparency Tools—Including Ours: "Our tool had let the public see exactly how users were being targeted by advertisers. The social media giant urged us to shut it down...
Welcome to the 21st-century, in which my coffee machine says that it is “booting”...
Note to Self: No, Apple! No Potty Mouth, Please!: A number of the biases in voice recognition systems come from the initial training dataset. Senior google employees have claimed to me–how serious they were I do not know–that Gmail autocomplete's extraordinary! love! for! exclamation! points! comes from its use of google engineers as its initial training dataset.
Today I am disturbed that Apple voice recognition keeps hearing “slut“ when I say “slack“. What training dataset produces that? From my perspective, Apple voice recognition needs to acquire much less of a potty mouth—or at least to have a potty-mouth-off switch—for it to be useful to me. Someday it is going to do something, and I am not going to catch it...
Quoctrung Bui: Map: The Most Common Job In Every State: "We used data from the Census Bureau, which has two catch-all categories: "managers not elsewhere classified" and "salespersons not elsewhere classified." Because those categories are broad and vague to the point of meaninglessness, we excluded them from our map:
Blum Hall B100: Plaza Level: 2 PM: Bill Janeway: The Digital Revolution and the State: The Great Reversal
Bill Janeway: Doing Capitalism in the Innovation Economy 2.0 https://books.google.com/books?isbn=1108471277: "The innovation economy begins with discovery and culminates in speculation. Over some 250 years, economic growth has been driven by successive processes of trial and error: upstream exercises in research and invention and downstream experiments in exploiting the new economic space opened by innovation...
...Drawing on his professional experiences, William H. Janeway provides an accessible pathway for readers to appreciate the dynamics of the innovation economy. He combines personal reflections from a career spanning forty years in venture capital, with the development of an original theory of the role of asset bubbles in financing technological innovation and of the role of the state in playing an enabling role in the innovation process. Today, with the state frozen as an economic actor and access to the public equity markets only open to a minority, the innovation economy is stalled; learning the lessons from this book will contribute to its renewal...