–Unemployment, Disemployment and the new focus on OPTIMUM EMPLOYMENT

Mitchell’s laws:
●The more budgets are cut and taxes increased, the weaker an economy becomes.

●Austerity starves the economy to feed the government, and leads to civil disorder.
●Until the 99% understand the need for federal deficits, the upper 1% will rule.
●To survive long term, a monetarily non-sovereign government must have a positive balance of payments.
●Those, who do not understand the differences between Monetary Sovereignty and monetary non-sovereignty, do not understand economics.


Recently I posted, “How IBM can change the world.” and “Who, in the world of economics, is asking for that next super-computer? Both posts described why the field of economics desperately needs, and will radically be changed by, a computer having the skills of Watson, the IBM machine that won Jeopardy.

More recently, I posted “The new paradigm: Disemployment. Less work; more life,” New Paradigm II: What are your plans for the Age of Disemployment? and “How would you make disemployment work?”

These posts told why increasingly, thinking machines will replace human labor, and why the thrust of economics must change from “full employment” to optimum employment – the situation in which people will be required to work less and have the opportunity to live more, while machines do more work.

In “How would you make disemployment work?” I suggested these preliminary steps for our Monetarily Sovereign government:

1. Legally reduce the traditional 40 hour work week to 30 hours and less.
2. Prevent hunger for lack of dollars. The government could provide for everyone’s basic food supplies by paying grocery stores to offer free milk, meat, fish and vegetables.
3. Provide health care for everyone. The government could pay for 100% Medicare for every American of all ages.
4. Keep people from suffering homelessness. The government to pay for home mortgages at a minimum level (Rather than “minimum wage,” we could have “minimum home mortgage,” where people could add dollars for more expensive homes. Or “minimum rent,” something akin to the government paying for hotel stays).
5. Just as today we provide free education, grades 1-12, the government should provide free college and advanced degree education to every American.
6. Begin with government-paid-for local, public transportation, then expand this by paying airlines and railroads for free national public transportation.

Now comes NewScientist Magazine, with articles bearing on this subject:

NewScientist Magazine, August 22, 2012
Watson turns medic: Supercomputer to diagnose disease
by Jim Giles

More than a year after it won the quiz show Jeopardy!, IBM’s supercomputer is learning how to help doctors diagnose patients. Progress is most advanced in cancer care. “It’s a machine that can read everything and forget nothing,” says Larry Norton, a doctor at the Memorial Sloan-Kettering Cancer Center.

When playing Jeopardy!, Watson analysed each question. Then it looked for possible answers in its database, made up of sources such as encyclopaedias, scoring each according to the evidence associated with it and answering with the highest rated answer. The system takes a similar approach when dealing with medical questions, although in this case it draws on information from medical journals and clinical guidelines.

Watson is now absorbing records – tens of thousands at Sloan-Kettering alone – of treatments and outcomes associated with individual patients.

William Audeh, a doctor at Cedars-Sinai Medical Center in Los Angeles, says the last few months have involved “filling Watson’s brain” with medical data. The technology is particularly useful in oncology because doctors struggle to keep up with the explosion of genomic and molecular data generated about each cancer type.

Nurses are now training Watson by feeding it test requests and observing the answers.

Watson’s system is virtually identical with that used by human doctors – compare symptoms, treatments and outcomes – except Watson “can read everything and forget nothing” and has no emotional biases, and can work 24/365.

Here’s another snippet from the same article:

Preparing for your financial future

Is your pension invested in the best possible way? To answer this question involves weighing up multiple investment options, future income prospects and the experience of others in similar situations. It is the kind of problem that most people struggle with, but which IBM’s supercomputer Watson may be able to tackle.

IBM announced in May that it has partnered with Citi, a multinational bank, to explore the idea of training Watson as a financial adviser.

Again, this is exactly how you and your financial advisor decide your investments. Compare historical risk and opportunity with current and project economic fact. Except you can handle only a few variables, and have many human biases that cloud your judgement. Humans are notoriously poor judges of risk and reward (thus the existence of Lotto.)

A “Watsonesque” machine would learn everything and forget nothing — and not buy Lotto tickets. It also would do a better job projecting those economic facts.

And then NewScientist published this:

Digital doppelgängers: Building an army of you
15 August 2012 by Sally Adee

Alex Schwartzkopf can be in more than one place at once and, in principle, do thousands of things at the same time. He and his colleagues at the US National Science Foundation have trained up a smart, animated, digital doppelgänger – mimicking everything from his professional knowledge to the way he moves his eyebrows – that can interact with people via a screen when he is not around. He can even talk to himself.

It’s becoming possible to create digital copies of ourselves to represent us when we can’t be there in person. They can be programmed with your characteristics and preferences, are able to perform chores like updating social networks, and can even hold a conversation.

These autonomous identities are not duplicates of human beings in all their complexity, but simple and potentially useful personas. If they become more widespread, they could transform how people relate to each other and do business. They will save time, take onerous tasks out of our hands and perhaps even modify people’s behaviour.

For example, the website rep.licants.org, developed by artist Matthieu Cherubini, allows you to create a copy of your “social media self”, which can take over Facebook and Twitter accounts when required. You prime it with data such as your location, age and topics that interest you, and it analyses what you’ve already posted on your various social networks. Armed with this knowledge, it then posts on your behalf.

In principle, such services could one day perform a similar job to the ghostwriters who manage the social media profiles of busy celebrities and politicians today.

The Australian company MyCyberTwin allows users to create copies of themselves that can engage visitors in a text conversation, accompanied by a photo or cartoon representation. These copies perform tasks such as answering questions about your work, like an interactive CV. “A single CyberTwin could be talking with millions of people at the same time,” says John Zakos, who co-founded the firm. MyCyberTwin also uses tricks to add a touch of humanity. Users are asked to fill in a 30-question personality test, which means that the digital persona may act introverted or extroverted, for example.

In the past year or two, Apple has filed a series of patents related to using animated avatars in social networking and video conferencing. Microsoft, too, is interested. It has been exploring how its Kinect motion-tracking device could map a user’s face so it can be reproduced and animated digitally. The firm also plans to extend the avatars that millions of people use in its Xbox gaming system into Windows and the work environment.

So could avatars be automated too? It already happens in gaming: many people employ intelligent software to control their avatars when they’re not around. For example, some World of Warcraft players program their avatars to fight for status or to farm gold.

To similar ends, in 2007 the National Science Foundation began Project Lifelike, an experiment to build an intelligent, animated avatar of Schwartzkopf, who at the time was a program director. The hope was to make the avatar good enough to train new employees.

Jason Leigh, a computer scientist at the University of Illinois at Chicago, used video capture of Schwartzkopf’s face to create a dynamic, photorealistic animation. He also added a few characteristic quirks. For example, if Schwartkopf’s copy was speaking intensely, his eyebrows would furrow, and he would occasionally chew his nails. “People’s personal mannerisms are almost as distinguishing as their signature,” Leigh says.

These tricks combined to make the copy seem more, well, human, which helped when Leigh introduced people to Schwartzkopf’s doppelgänger. “They had a conversation with it as if it were a real person,” he recalls. “Afterwards, they thanked it for the conversation.”

The Project Lifelike researchers are now building a copy of the astronaut Jim Lovell, who flew on Apollo 13 and will answer questions at Chicago’s Adler Planetarium, and one of Alan Turing, who will field questions at the Orlando Science Center in Florida. Others are working on ways to create doppelgängers that will persist after people die.

And the beat goes on:

Meanwhile, Bickmore and his team are developing animated avatars of doctors and other healthcare providers. One of the nurse avatars they created is designed to discharge people from hospitals. In tests, he found 70 per cent of patients preferred talking to the copy rather than a real nurse, because they felt less self-conscious. Doctors, meanwhile, could use avatars to streamline their work. “A doctor might want to make a copy, for example, if they are the pre-eminent expert in a field,” Bickmore says.

As with doctors, academics could spread their workload too. “This would allow you to teach as many sections as your department desires,” Bailenson says. With several copies operating simultaneously, a teacher could jump between them at will, inhabiting any one without ever letting on to the students.

A British company called Philter Phactory makes autonomous bots called Weavrs (that) can operate Twitter accounts and other social media on a person’s behalf. The company’s selling point is that Weavrs can be used to trawl the web for interesting links about certain topics, then post status updates or share videos and articles about them.

Many actors and performers have digital personas, sometimes created against their will. It seems laws will need to be adapted to define who can control people’s digital selves (see “Double jeopardy”).

Jaron Lanier, an author and Microsoft researcher, worries about technologies that claim to amplify our efficiency. “If you’re a history professor and you can operate 10,000 of these (bots), why does the university have to hire any other history professors?” Lanier asks.

Visualize you always have lived in a grass hut. A hurricane is coming. You know with absolute certainty, the hurricane winds will destroy your hut. Do you ignore it, or do you build, and move to, a concrete building?

We know with absolute certainty, hurricane “Disemployment” is coming to the island of economics. We already have felt the rising wind. Will we continue doing what we always have done, using the same old ways to search for “full employment.”

Several excellent economists, whom I know, belong to “The Center for Full Employment and Price Stability.” I hope they change the thrust of their thinking from “full employment” to optimum employment, and help our island prepare for the hurricane.

What do you think?

Rodger Malcolm Mitchell
Monetary Sovereignty

Nine Steps to Prosperity:
1. Eliminate FICA (Click here)
2. Medicare — parts A, B & D — for everyone
3. Send every American citizen an annual check for $5,000 or give every state $5,000 per capita (Click here)
4. Long-term nursing care for everyone
5. Free education (including post-grad) for everyone
6. Salary for attending school (Click here)
7. Eliminate corporate taxes
8. Increase the standard income tax deduction annually
9. Increase federal spending on the myriad initiatives that benefit America

No nation can tax itself into prosperity, nor grow without money growth. Monetary Sovereignty: Cutting federal deficits to grow the economy is like applying leeches to cure anemia. Two key equations in economics:
Federal Deficits – Net Imports = Net Private Savings
Gross Domestic Product = Federal Spending + Private Investment and Consumption – Net Imports


22 thoughts on “–Unemployment, Disemployment and the new focus on OPTIMUM EMPLOYMENT

  1. Ever-shortening work weeks have been a long-standing trend, and there’s no reason to believe that trend will not continue.

    Using Watson for investment decisions is interesting, though. Assuming lots of advisers using the same program, and trying to make the same trade at the same time, it would be self-defeating, perhaps degenerating into a thrashing mode as each instance reacts to the new prices, and thus new expected returns, caused by the last trade of the other instances. I think of the argument used by fundamental analysts against technical analysis, “if it worked, everyone would use it and it would become a self-fulfilling prophecy”. Except that in the case of technical analysis, relatively few use it, and they often arrive at different conclusions using the same data, just as fundamental analysts do. If Watson were to eradicate those differences, what would happen to markets, when everyone’s computer says “buy” at the same time, and then suddenly they all say “sell” at the same time?


  2. John,

    The answer is, “everyone” would buy and sell at the correct price and the correct time. The alternative is the current situation, where “everyone” buys and sells at the wrong price and the wrong time. That’s why markets are so unstable.

    The reason technical analysis is so poor is because, well . . . technical analysis is so poor. Chartists use a few graphs to make their decisions. A “Watson” supercomputer would evaluate millions of variables, some of which would be: “What is everyone else doing?”

    As for work week length, the trend needs to be legalized via overtime laws.


    1. So, the Watson program might be selling something in my account at the same time it is buying the same thing in your account? That’s not what I imagined from the description of it.


  3. John, yes I can visualize that, depending on many factors, including your current investments, your life situation, etc. If you are loaded with “X,” it might sell “X,” but if you have no “X.” it might buy X. Or not.

    That’s the point. It would score every known variable — thousands of variables — and develop a plan specifically for you. Being human, you don’t have that ability. At best, you can handle a few variables, and rank them intuitively, then buy what your brother-in-law suggests.


    1. We already have advisers and mutual funds that do that, probably most of them already “run” by computers. I thought the idea of Watson applying immensely more compute power to it was going to give far better results than, say, the typical Vanguard life strategy fund, without the risk associated with the most successful investors (all your eggs in one basket).


      1. John, there are computers and there are COMPUTERS. What Vanguard does is to super computer analysis as a children’s pedal car is to a Porche.

        And Watson should be considered only a prototype — a proof of concept — for what the future holds.


        1. Rodger,

          It’s still not clear to me what investment objective or methodology you envision for Watson. There are all different approaches, and various tactics that apply to each. To keep it simple, is Watson going to be a stock-picker or a risk-manager? If the former, it would choose a stock (or bond or whatever) that it deems to have a better expected return than others. If it does that, it would do it for all the accounts it is managing, it would not sell such a stock in any account, except to balance it vis-a-vis the other accounts. For instance, it might decide that one should hold 3% of the portfolio in IBM, and it would do that for everyone, not buy it in one account and short it in another. If the latter, the approach would be a manged diversification strategy, such as the life management type funds, where the asset allocation is adjusted according to one’s age. You could overlay some stock-picking on that, deciding not to simply buy the S&P 400 Midcap index, but to avoid 50 of those 400 and overweight another 50 of them, but again that would be something it would do for everyone holding that index, not long in one account and short in another.

          The problem I see is that there are plenty of low-cost, highly diversified asset allocation strategies, and the only way to improve on them would be to lower the cost or introduce stock-picking. But, if Watson is a clearly superior stock-picker and becomes widespread, its simultaneous actions on behalf of millions of investors would move the market, eliminating its own profit potential. And if it trades against itself, taking both sides of a trade, it is playing a negative-sum game due to trading expenses.

          The stock “market” thing only works when different investors are taking different views of things, one buying and the other selling. Watson can succeed only if it never becomes more than a bit player in the markets.


  4. Where we would go wrong.
    “Watson,garbage in equals garbage out”
    When will economists,market gurus, everyone realize that, “Anyone that attempts to predict a future event (Price) is a fool; if by chance (Luck) they are correct, then they are just a lucky fool, albeit still just a fool.”
    How many need to lose all their wealth,health and life, before they will understand that PROBABILITY is only a prediction of a future result.
    As for market price the only valid answer Watson could give for price change would be ,”The price will either be higher, lower, or the same.
    Even if Warren Buffet were to supply the knowledge to Watson he would discover that holding stocks forever would be wrong, since forever is too long a period of time and the holdings would return to “dust”.
    Also read what Michael Lewis had to say at Princeton speech,”Thank Luck”.


    1. Every decision you make in life is based on “garbage-in, garbage-out.” Have you ever bought a security? What were the “non-garbage” variables you used for your decision?

      Watson’s method is to analyze the probabilities of thousands of variables. As a human, you may have the ability to analyze two or three variables — using “garbage-in, garbage-out.” And your analysis would be flawed by emotion, bias, lack of information, limited memory and what your best friend told you yesterday.

      That’s why Watson beat the world’s greatest Jeopardy players: More variables; better weighting.

      Rodger Malcolm Mitchell


      1. Perhaps why Watson beat humans is because the answer to the questions are in fact historical, something that has already happened.
        No prediction required, which means that even Watson would have to disclose, “Past perforance can not guarantee future success.”
        When John Paulson made $20 billion in one year, could he provide a guarantee of $1 dollar profit for the next 2 years? Ans: NO, lost billions.
        As for analying the probabilities of “thousands or million” of variables
        what good is that when even Watson can not guarantee from just 2,yes two, variables-on a coin toss, heads or tails ?
        Which by the way for a little humor , they seemed to have missed that there is really 3, yes three variables-The coin could land standing on its side !


    2. RMM: “Rodger Malcolm Mitchell says:
      August 23, 2012 at 3:34 pm
      When you invest (or don’t invest), you predict the future. How do you do it?”
      First thank you for a direct question, now the ans. is….
      With the full knowledge that it is absolutely a gamble. Just like betting on a horse race after considering all the variables, you make your “purchase”. But in horse racing at least you are sure that you will get paid since payment is liquid (in a pool of cash which is divided after “taxes” the house takes.
      This brings us back to economics.
      (A)… As stated by the OCC (Office of Comptrollor of the Currency, “US banks and financial institutions have positions of over $200 TRILLION.”
      (B)…Derivatives are like insurance policys,bets that something may or may not occur within a certain period of time.They are “credit ” bets in that they are merely recorded on a balance sheet (no actually currency needed). What is incomprehensible is that they are mostly backed “by thin air”, not ever 10%!
      (C) Within the time frame of the BET ,what does the institution/bank do if they are ahead a mere 10%-i.e.,$20 trillion? They can not get paid
      unless someone comes up with the money (read Uncle Sam).
      If one asks for payment them doesn’t get it, what do you think the others holding winning positions would do? Systemic failure?


  5. From Warren Mosler:
    “With only 1% of the population needed in agriculture, and less than 10% in manufacturing, the rest is a political choice and there is probably no need for anything more than a 20 hour week, particularly if we cut FIRE down to size.”


    1. Do you know where Warren gets these numbers from regarding the percentage of the population in manufacturing and agriculture? Great blog!


  6. “Nine steps to prosperity…” Hi Rodger. Another timely and fascinating post as usual. Any chance you might be able to slightly enlarge the “9 points” for future posts? First time users might be inclined to overlook them and their significance . Just a suggestion, nothing personal of course.


  7. there’s an entertaining movie out now that tangentially relates to your statements about technology and how it will soon replace human labor.

    when warren mosler talks about his JG proposals, he always asks the audience, “how many of you out there need a personal assistant?” well, in the near future, that personal assistant might be a robot:

    synopsis: http://www.angelikafilmcenter.com/angelika_film.asp?hID=1&ID=ou1lff3.1529026874522753fl.99

    trailer: http://www.youtube.com/watch?v=q4y8YAMPFhk


  8. John, visualize this.

    You own a mix of stocks and bonds, totaling a certain amount. You are X years old. Your job pays Y. The likelihood of your company’s growth is Z. You are married with three kids, ages A, B and C and are paying alimony on your first marriage. Your L% mortgage is $F and it ends [date].

    You have a college education form [college], and are working for an advanced degree in [degree]. You live at [street address], which affects your local taxes. You are (black, white, yellow). Inflation is D%.

    And on and on and on.

    Every one of those factors, plus thousands of others, affects your financial future. Do you know how much? Of course you don’t. Neither does your human financial adviser. So you wind up buying a stock you heard about from your cousin or suggested in Money Magazine.

    Watson will have analyzed all these factors for 350 million people, plus every company in the world. Based on the interplay of the factors, it will apply weights to each, and give you the best suggestions for you, one of which is to buy 100 shares of D Company, Inc.

    Your neighbor’s factors are different, so Watson gives him different suggestions, one of which is to sell 50 shares of D Company, Inc. Watson makes this decision millions of times per second.

    Watson also knows what advice it has given, and how your following that advice will affect the market, and whether you actually do follow the advice. It even has learned enough about your temperament to calculate the likelihood you’ll follow its advice.

    It takes all that into consideration as it provides advice — lots better than you and your human adviser can do.

    Don’t think with year 2000 computer capability. Visualize year 2030+ capability. The current Watson, which absorbed billions of facts, and via what is called “machine learning,” figure out how these facts were related, will look like a toy compared with machines a decade from now.


    1. I get it how different people should own different mixes of assets.

      But if Watson both buys and sells the same asset at the same time, only one of those trades will be profitable at any point in the future. The same can be said of the two sides of any trade, with or without a computer. It doesn’t matter that GM bonds were “right” for you because of your age group and 1000 other factors, you lost money on them when GM went bankrupt, and the guy who shorted them made money. Both can’t be right.


      1. Each person will need a different mix of securities, depending on many thousands of variables. To achieve a different mix, some people will have to sell shares while others will have to buy the same shares.

        Young employed people should consider higher return with less safety. But as they age and retire, they may be better with lower return, and more safety — so they sell the securities they bought when they were young (to other young people) and buy “old-age” securities.


        1. Right, that’s the part I get. We do that already, with minimal assistance from computers, other than storing large volumes of data, and at very low cost. So Watson is only going to tell you you need 8.7% large-cap technology stocks, not 9%. And it’s not going to tell you to buy MSFT and sell CSCO, because MSFT figures to have a higher return this coming year.


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