Digital Musings

The Digital Gilded Age: Entrepreneurship Without Knowing The Odds

Daniel Kahneman is a faculty member at Princeton University and a fellow at Hebrew University. He is the winner of the 2002 Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel (erroneously known as the Nobel Prize in Economics), despite being a research psychologist and not an economist. Along with Amos Tverski, he has developed the so called "prospect theory" . On important feature of prospect theory is loss aversion.

According to Wikipedia, loss aversion refers to the tendency for people to strongly prefer avoiding losses than acquiring gains. Some studies suggest that losses are as much as twice as psychologically powerful than gains.

In a YouTube video, Daniel Kahneman gives his thinking on loss aversion. What is quite interesting is the point he makes on the difference between knowing the odds and not knowing them. When you toss a coin, you know the odds. When you innovate, fairly good chances, you don't know the odds.

When people don't know the odds, loss aversion disappears. People, according to Kahneman, behave optimistically. They are no longer shying away. They even tend to be overoptimistic.

That is what makes entrepreneurs a different kind of people: If they really knew the odds, they would never start in the first place! It seems, though, that venture capitalists are precisely those who want to know the odds and, above all, price them (business plans, Powerpoint presentation, valuation...). This may explain why they are so loss averse.

What is even more troubling though is how, despite my friend Nassim Taleb's writings, people, especially managers, can be fooled by randomness. They often take for genuine skills what is purely the output of luck. Think of portfolio managers claiming to outperform the market (do you really believe them given how many of them started the same rat race in the first place?), of CEOs loaded with stock options who were fortunate enough (few years ago) to see them end up in the money (see what happens when the stock market plummet, stock options are under water, does this mean that this time CEOs lack relevant skills or lost them?) etc...

Not knowing the odds is another way of saying that anything can happen. So, the first quality of an entrepreneur, apart from being an optimist à la Kahneman, is recognizing that systematically disentangling skill from luck is not worth the effort. What matters is the ability to define a business that does take advantage of luck, that is serendipitous, that improves through tinkering.

If you happen to be successful in the course of doing so, I will not blame you if you let others praise your skills.

But please don't let them fool you and others for too long!

 

The Digital Gilded Age: How To Peel a Banana: When Attitude Beats Latitude

Did you know that monkeys peel bananas from the bottom up (well to make things even more confusing this is the other way round since bananas grow upside down)? Anyway! If you assume that monkeys are banana experts (not a bold assumption to make), how can it be that we, clever humans, have it all wrong for so many years?

This is not a joke or some kind of "I love to turn conventional wisdom upside down" trick. The reason why I am interested in the art of peeling a banana is not to add my own explanation but rather to illustrate a principle, namely that of inversion. This principle is much useful as it can spark very creative processes. It is simple and boils down to the question "what if I were doing it the other way round." Yale University Professors Ayres and Nalebuff use this principle in their book entitled Why Not? and in their eponymous website.

Why do we have ATM machines where we can get money even if we are not customers of the bank where the ATM is located while we cannot do the same when we want to deposit money in the same ATM?

Why is that telemarketers who call us on the phone to ask us questions don't use a number which would credit our bank account, thus paying us for our time that so far they consume for free.

Think of Dutch auctions: Instead of proposing higher and higher prices, the auctioneer does the reverse and the bidder who wins is the one who steps in first (as opposed to last in "traditional" auctions).

Applying this inverted way of looking at business and people is indeed a unique way of creating new ideas, new business opportunities.

When I was an investment banker, I did realize that it was easier (to a certain extent of course) to buy from my clients than to sell to them. Not that obvious when you think of that army of fellows on trading floors called salespeople. They are not called "buypeople"! Buying derivatives from my clients made it easier to sell them derivatives. This is one the reason why the business of structured finance has been so lucrative: Putting in one single financial product derivatives bought and sold made the transaction more appealing. I will always remember this sentence from the floor: We have to make the product «optically good looking»! And, optics does involve inversion indeed: which side of the lens are you looking through?

A blogger abides to the inversion principle being both at the same time his or her own publishing company and the author. Airbnb homeowners become hotel managers. Cab clients turn into Uber cab drivers. Apple recreate the stores that Amazon and Dell wanted us to leave. Even hotel chains are applying the inversion principle. In 2014 Scandic Hotels has launched its Scandic to Go concept whereby you no longer go to your hotel. Your hotel room fully equipped comes to you wherever you are (as a matter of fact the spot has to be checked and cleared by Scandic first).

Monkeys are smart. Unlike Michael Porter, they know that value is nowhere to be found in a chain where everything always flows in the same direction. It does indeed pay to invert the flow!

So, next time you eat a banana, try it the other way around. While eating it try to find a new idea that would make the monkeys proud of you !

 

The Digital Gilded Age: All or Nothing

I once heard on the radio that Swiss students went on strike because they wanted more scholarships and less student loans. Who indeed would pay interest charges when you can find legal ways to avoid them ? A scholarship is nothing but a fully subsidized loan. In the finance jargon, what Swiss students have been asking for is a zero cost funding topped by the right not to repay the principal of the loan (right which in this particular case is always exercised.) Most of us would certainly love to receive free of charge money to fund the assets we want to invest in.

Even though I have a lot of sympathy for student activism, what strikes me in this episode is that (far too) many people, including students, seem to think that we live in an "All or Nothing" society. Either you get what you want in full (zero cost funding for that matter) or you get nothing (namely a loan with an interest rate).

But, wait a minute, where has creativity gone? Human brain is admirable precisely because it has always been able to fill the void between all and nothing. Let's take the example of the student loan again. The interest rate does not have to be either zero or strictly positive. What if students could get a loan where the forthcoming installments would be indexed on some future earnings measurement ? When students' future earnings would go down, the loan installments would go down too : Right when they badly need it. Take the worst case scenario where students do not find any job. In that painful case, the loan reimbursements would be suspended as long as the students do not find a job. When students' future earnings would go north, installments would go north too : Right when they can afford it.

I know there are many contractual details to be fixed to make this type of structured loan fly. Sadly enough and because of the 2008 credit crisis the creative folks at My Rich Uncle do no offer such a scheme and variations around it anymore (http://en.wikipedia.org/wiki/MyRichUncle.) Their schemes were quite innovative and available online ! But the spirit is still there: Use your brain to fill the void between all or nothing !

Recently, I visited vintage bookstores in Brussels. I bought an old business textbook dated 1900. It is titled "Textbook of Commercial Sciences" and has been written by Professor Merten of the University of Ghent. Two things caught my eyes. The first one is related to the way the reader can authenticate whether he is reading a true copy or a fake one. Simple, each true copy had to carry the author's signature. The absence of the signature signaled that the copy was a fake. Of course, it begs the question of how one knows the authors' true signature in the first place and how one can be sure it has not been counterfeited. In any case, it is fun to see that the compulsory signature indicates that book piracy was already an issue in this pre-Internet age !

The second thing has to do with copyright and copyright enforcement. We all know the traditional formula. It usually says "All Rights Reserved". Well, here the text is rather different. It is a lot more personal and a lot more detailed. Indeed, the publisher writes unequivocally:

"All rights are reserved in accordance with the law. I am willing to sue anyone who would, in violation of my copyright, reproduce any theory or proof from this book, either from past editions or from the current one." , The Publisher.

One cannot be more specific! I truly find it more « credible » than the usual "All Rights Reserved". Here again though, what strikes me is that we are still stuck in an "all or nothing" situation. Either the book is copyrighted (all) or the book is public domain (nothing: No Rights Reserved).

This is sad! What about having something softer that would say "Some Rights Reserved"? These rights would be spelled accordingly. Some uses would then be allowed without violating the publisher's rights. For instance, photocopies of books should be allowed in jailhouses or hospitals.I know that Harvard Law Professor Lawrence Lessig and the folks at Creative Commons have been fighting big time for this. Creative Common licenses do allow to change the copyright terms from the default of "all rights reserved" to "some rights reserved." But, the simple fact that they still have to fight for it is again strong evidence of the pervasiveness of the "All or Nothing" society.

The "All or Nothing" society is a real plague. The last thing we should do is surrender to it, an insult to our individual and collective intelligence, truly. After all, copyright is a social creation that we can and must adapt along the way. Some argue that copyright should be totally abolished. I do not think this is a good solution. A full copyright world is indeed not right. However, a no copyright world is wrong too. And, what is true of copyright is also true of property rights. It is an obvious fact that ideas can flow worldwide at click-speed. This does not necessarily mean that all copyright and property right dams should be destroyed. These dams do carry opportunities that can make them legitimate. What if, for instance, some of the royalties they trigger were allocated to public funds supporting innovative projects? What if we reconsidered what I call the Faustian swap (free service in exchange of all your data)? The swap is truly odious: the more free data are crunched, the more we are crushed. The more data are given away, the wealthier, more powerful and more uncontrollable robber robot lords are. Free is not fun at all!

So, next time you feel in an "All" or "Nothing" situation, please observe it carefully, there might be room for a new business.

Your next business! (Or, your next piracy?)

 

The Digital Gilded Age: To Play Hooky Or Not To Play Hooky

"Our fine arts were developed, their types and usages were established, in times very different from the present, by men whose power of action upon things was insignificant in comparison with ours... In all the arts there is a physical component which can no longer be considered or treated as it used to be, which cannot remain unaffected by our modern knowledge and power... We must expect great innovations to transform the entire technique of the arts, thereby affecting artistic invention itself and perhaps even brining about an amazing change in our very notion of art."

Paul Valéry,

The Conquest of Ubiquity Pièces sur l'art, Paris, 1934, p. 103-104 (Bibliothèque de la Pléiade, Tome II, 1960, P 1284)

This quotation from a short essay by French writer Paul Valéry appears as the epigraph of Walter Benjamin's groundbreaking text: The Work of Art in the Age of Mechanical Reproduction. Authored in the 1930s by two men of letters, their writings constitute a visionary interrogation on the status of the work of art at a time when technology rendered it reproducible ad infinitum. Walter Benjamin's interest in the question did not arise haphazardly. His was passionate about photography. For him, photography is a form of art but unlike the other arts it allows for a multiplicity of prints remaining "identical" to the original. As technology permits large-scale reproduction of a work of art, Benjamin asked a key question: In what respect do we have to reconsider the relation between originals and copies since unlike for paintings we can no longer "authentically" distinguish the original form the copy? What becomes of art in a world of untethered reproduction?

As art amateurs we do have an intuitive answer. Indeed, we do experience a great difference between observing the Chartres cathedral stained-glass windows in the church itself and a print reproduction of the same stained-glasses. When we are inside the cathedral, we can feel the presence of thousands of pilgrims who prayed in front of the stained-glasses. The luminous contemplation of the famous Chartres blue is a direct link to them. The stained-glasses do not stand alone: they are wrapped into what Benjamin calls an aura. In that sense, Chartres stained-glass windows are truly authentic. And, this is precisely this aura that vanishes in the mechanical reproduction. This loss is not a full loss though. As Walter Benjamin put it:

"...by permitting the reproduction to meet the beholder or listener in his own particular situation, it reactivates the object reproduced."

Some eighty years later, the questions raised by Walter Benjamin and Paul Valéry are strikingly echoed in the domain of pedagogy, which is being thrown into upheaval by the emergence of Massive Open Online Courses (MOOCs), of which the best-known avatars are Coursera (www.coursera.org), Udacity (www.udacity.com), FutureLearn (www.futurelearn.com), EdX (www.edx.org) and OCEAN (http://www.ocean-flots.org/) Having previously escaped the digital tsunami that has wrought havoc on industry, academic institutions are now in the eye of the storm.

In a nutshell, MOOCs are courses to which millions of students throughout the world have free access via the web. Outfitted with a pronounced community dimension, the classes are neither walled off nor subject to geographical boundaries. Generally speaking, as is the case with Coursera, they are drawn up from colleges and universities such as Stanford, Yale or Princeton. The recent popularity of extra-mural pedagogy is nothing short of phenomenal; over the same lapse of time, student enrollment in Coursera has increased far more rapidly than member registration in Facebook or Twitter! As of now, Coursera counts more than four million students scattered around the world. Needless to say, e-learning and distance learning came into being prior to MOOCs, but neither of them has been able to attain comparable quantity (number of enrollees, countries and universities involved) or quality (worldwide learning communities, dissolution of the focal point of pedagogical authority). Michel Serres, the French veteran philosopher, Stanford professor and eternal optimist, is hardly worried by the shape of things to come:

"Far from disappearing, the class is plugging itself into the network and restructuring itself following an open and participatory model. It was previously formatted following the model of the page of a book: The teacher was in front of his class and held the position of the author, of the person who knows and transmits to those who are not in the know. Nowadays this model is falling to pieces. »

The shattering of the model is tantamount to the loss of the aura of the original, namely professor's lectures in an amphitheater. The master lecture is inherently theatrical. It brings together the actors in a classic unity of time, place and action. It is built around a focal point, the podium, the Power Point in the original sense of the word.

This short-lived unity, which is anchored in long-standing academic tradition, endows the lecture with an aura that is dissipated by MOOCs and the new technologies. A MOOC is initially a large-scale copy of the original, a copy rendered possible by the technological resources of the Web. And yet, it is far more than that; it is a reworked copy that Benjamin might have termed "reactivated". It is a copy which trumpets its infidelity with respect to the original.

This shattering could not help but vitally interest me for at least two reasons. The first is my passion for teaching. I taught economics and finance for more than fifteen years. This is an activity that I more than happily go back to when I am offered the opportunity. The second reason relates to Cyberlibris (www.cyberlibris.com), the firm which I co-founded fifteen years ago. Cyberlibris, whose digital libraries are used by millions of students worldwide, is a response to what we call the tyranny of the single, authoritative manual. Like it or not, the book has entered the age of digital reproduction. Similarly to MOOCs, which emancipate pedagogy from the enclosed space of the classroom, the digital book separates its content from its former "Gutenberg" container. The art of discovering and reading books is overhauled as a result. When a student reads a copy he is no longer depriving the other learners. Queuing up and rationing are becoming a thing of the past. As a digital community library dedicated to business schools, ScholarVox (www.scholarvox.com) epitomizes for instance this pedagogical emancipation. Day in and day out, several hundreds of thousands of students, professors and librarians converge towards a digital location where they can share their readings and manage, by design and community-based serendipity, to discover works they would surely never have otherwise known.

Needless to add, the library is anything but a new idea. On the other hand, the emancipated and emancipating library without walls is new indeed. Goodbye to the linear model of the appraised and validated, purportedly authoritative text; hello to a model of reading that is profoundly organic, literally natural. Mother Nature proceeds tentatively and uncertainly, by trial and error. That's how new species emerge, prosper or disappear. Mother Nature constantly make mistakes, and it is that what allows it to move forward in its untold wealth and multifarious diversity? In the digital library, students practice the same serendipitous "tatônnement" hopping from one book to next. They are a library away from their next book, a book away from their next library.

Given my digital library background and my passion for teaching , I could not help but ask myself questions on MOOCs and their repercussions on the arts of learning and teaching and, more plainly, on education and the institutions with which it has been associated.

Beyond Benjamin's interrogations, there are at least two reasons why this type of examination is indispensable at a time when MOOCs are becoming mainstream. The first of them is put forward in the highly pragmatic words of Sir Kevin Robinson:

« I mean, I always think this: Kids who start school this year in Australia in primary school will be retiring round about 2070. You know, nobody has a clue what the world will look like this time next year, let alone 2070. So, yes, parents are concerned and they're right to be concerned. I'm concerned. I've got two kids. But I'm concerned that they get an education which is tailored to these circumstances rather than the ones that obtained 150 years ago. »

http://www.abc.net.au/7.30/content/2009/s2600125.htm

Our educational model is derived from a long-standing tradition dating back to ancient Greece and the Gutenberg printing press. It was late in 19th century that presently existing compulsory education systems came into being. Since that time, their overall design has undergone hardly any genuine change. It remains permeated with a model derived from the master ironworkers of yesteryear. That's why it is high time to voice some concern. From this standpoint, MOOCs serve as active catalysts. The second reason for challenging the current model is that the diploma = employment equation that functioned so effectively for a number of decades has broken down. As underlined by Sir Kevin Robinson, the very notion of a degree is being trivialized:

« More and more people are now going to college and getting degrees. There are two reasons for this expansion. The first is population growth. In the last 30 years the world population doubled from 3 billion to 6 billion. The second reason is the growth of the knowledge economy and the growing demand for intellectual labor. The combined result is that in the next 30 years, more people will qualify, through formal education and training around the world, than since the beginning of history. This is an historic change in the demand for education, and it has huge implications for the nature of it. »

http://www.ecs.org/clearinghouse/60/51/6051.pdf

How Creativity, Education and the Arts Shape a Modern Economy, April 2005

My personal conviction is that MOOCs are providing a once-in-a-lifetime opportunity to comprehensively review and revise our thinking on education, pedagogy and the institutions through which they are administered.

With MOOCs, one moves from an economy of pedagogical perspiration (the campus, the walls, the classrooms, the faculty...) in which pedagogical returns are decreasing (once the classroom is filled with students, you have to have a new one to accommodate more students) to an economy of pedagogical inspiration where economies of scale are legion, where returns are increasing to scale and where serendipity is maximized. Who knows if among all these online African or Haitian students we won't find entrepreneurs, scientists whose discoveries will one day shake the world? MOOCs give long range wings to ideas. Ideas are freed from their traditional containers. They can travel faster and further away. Moreover, ideas are not like standard goods. The fact that you use Pythagora's theorem does not preclude me from using it at the same time as you. Academic institutions, which have been for so long the tabernacle of ideas, have now an opportunity to take advantage of these increasing returns to scale. But, this will require a great sense of adaptation from them. Mark Twain was so skeptical about this capacity for self-reform of academic establishments as to state:

"College is a place where a professor's lecture notes go straight to the students' lecture notes, without passing through the brains of either. "

Knowledge has become boundless, and MOOCs are avatars of today's overabundance. Knowledge is no longer a rare commodity; more precisely, it is no longer confined to campuses, which in Michel Serres's terms have become similar to the camps of the Roman army. Students can now play hooky and off the walls cherry-pick the courses they are most interested in.

Amidst the expansive portfolio of Coursera courses, the student may wish to take but a single course, for example the one given by Franklin Allen of the Columbia Business School. He is no longer required to tackle the whole Columbia curriculum after having been allowed to indulge his passion for finance. The freedom offered by the MOOCs is total: No curriculum is imposed. Each students can build his hooky playlist. For free! This worldwide hooky playlist game is not synonymous of lost revenues for schools and universities though. Scrutiny of the Coursera's geographical data shows that many registered students reside in emerging or underdeveloped countries. They undoubtedly are students who could not immediately have afforded the onerous tuition fees for Yale or Stanford. This means that these universities are not on the face of it losing any money at all.

This being said, two scenarios may be imagined. The first is based on the notion of filtering. By taking and passing the course units they have chosen, the students directly signal their value and interest to the universities involved and can easily be identified; when appropriate, they could be offered scholarships enabling them to accede to degree courses. The second scenario is inscribed in the same perspective. A student who one day was allowed to discover the source of his passion is unlikely to forget a decisive turning point in his life. It may even be presumed that when the time comes, he will decide to register in the university of which one of the on-line courses functioned as a revelatory foretaste. He will receive credit for the course.

The free-of-charge model is of course hardly new. This is the model on which radio is predicated. Radio is free; it can broadcast because third-party payers agree to substitute for the end user. It is easy to imagine that many third parties, particularly potential employers, will show interest in the data whose collection will be effectively facilitated by MOOCs. One can also suppose that companies will agree to finance and sponsor courses so as to derive benefit from information likely to serve the purposes of their selection and recruitment units.

This is indeed the strategy that is financially backed by numerous venture capital firms, particularly in Silicon Valley. Digital reproduction does not come cheap and this explain the Silicon Valley activism. The difficulty lies in the fact that once an initial investment is made (A quality MOOC is costly to put together), the marginal cost per supplementary unit is low. Advancing from two hundred to twenty thousand students poses no major problem. Everyone has access to the same MOOC. As a result, and in accordance with the teachings of microeconomics, it becomes difficult to charge a price for the supplementary units higher than the close to zero marginal cost and thereby generate sustainable income.

The monetary opportunity lies on the other side of the coin. It consists in the increasing returns offered by MOOCs. Co-founder of Coursera, Daphné Koller once mentioned that at Stanford, the "Machine Learning" course given by Andrew Ng, the other co-founder of Coursera, draws 400 students. On the Coursera website, however, more than 100,000 students take Ng's course. In order to achieve an identical result, on the Stanford facilities Andrew Ng would need to offer that course for one quarter of a millennium! Moreover, success breeds success. The more a course boasts a favorably inclined audience, the more candidates and the more students it attracts, and the more its franchise is reinforced. The fundamental question then consists in how to reconcile increasing returns to scale and the capacity to sustain a price higher than the marginal cost, that is to create a rent. In the minds of venture capitalists, the equation is simple enough. The option on that future rent has got to be captured through the injection of tons of money. One day, in one way or another, the option will be "monetized" as I carries lots of potential.

When one looks at this buoyant digital activity, it is hard not to be a trifle appalled when comparing a photographed classroom in 1900 and a photographed classroom in our time. Little or nothing has changed. Blackboards, tables, stools, podium are still in the same place. Only the uniforms have disappeared. However, as Benjamin was aware, the student no longer goes to class, to the original. The class, the copy of it, comes to the student. This inversion of the pedagogical path is fascinating and prompts me to take the risk of drawing an inventory of potential consequences.

All tinkerers?

The fact that MOOCs open the door to course granularity is crucial. The notion of curriculum established by the empowered academic authorities is still in almost all cases the dominant model. A student must fit in and meet its demands. If not, he runs the risk of failing to be awarded the coveted diploma. The curriculum contains a beginning, an end, and programmed progression. It is in some sense linear. MOOCs, on the other hand, are highly non linear: The student builds his own learning portfolio, grain by grain, according to his wishes and to his tastes. He does so outside the usual institutional boundaries. A finance-based comparison illustrates the repercussions of this very valuable non-linearity. It is inspired by the derivative markets. Any option trader knows that an option portfolio is of more value than an option on a portfolio. As regards the latter, any possible gain is binary: either the option is or is not in the money. As concerns the option portfolio, on the other hand, possible gains are decidedly more varied: each option may or may not contribute to the final gain. A greater number of lucrative possibilities consequently exist. It is preferable to dispose of a large number of "small" options on different assets rather than a "large" option on a single asset portfolio. This is somehow what trial and error is all about, a string of options which allows mistakes and rebound. You try something out, you are mistaken you try again. Since the trial is limited in scope and deleterious eventualities, the damage is minimal. MOOCs encourage this type of "tinkering" in which Mother Nature is indeed an expert. Otherwise we would not be here! They offer flexibility allowing the learner to "goof up" and enabling him to make one attempt after another, and to achieve self-discovery through experimentation. Far from stigmatizing error, they encourage him to learn from his mistakes and to wind up finding the right match for his needs. The learner thereby engages in "convex tinkering" recommended by Nassim Taleb and becomes "antifragile".

Bumbling, fumbling and stumbling are at once desirable and beneficial. And they are by no means detrimental to academic institutions, which derive benefit from this 1/N strategy by enlarging the pool of talents knocking on their doors. This is a crucial point: whether from the learner's or the establishment's standpoint, pedagogy has got to be convex. It has got to be not the locus of a single possibility, but rather the meeting point of everything and anything possible. This is the best way to address and respect the wide variety of the cognitive abilities presented in human beings.

Are diplomas yesterday's papers?

This spatial / temporal granularity and this non-linearity of education has radical repercussions on the very notion of a diploma. It is highly likely, if not a safe bet, that the notion of a diploma, taken as the ultimate validation of a finished industrial product, is bound to disappear. We will have to get used to attending fewer formal graduation ceremonies replete with their commencement addresses and caps and gowns. Is this really a loss? Paul Valéry was unsparing in his condemnation of the diploma:

"I do not hesitate to declare ; the diploma is the mortal enemy of culture. The greater the importance diplomas have been given in life (and their importance has steadily grown due to the economic circumstances), the lower the yield of teaching. The more prevalent the exams being given, the poorer the results. Poor in terms of their effects on public spirit and the spirit in general. Poor because they create hopes and illusions of acquired rights. Poor on account of the multiple stratagems and subterfuges they imply, the strategic preparations and, all in all, the use of all the expedients needed to cross the redoubtable threshold".

If one nonetheless wishes to conserve the term, the diploma will be the business of a lifetime. Each one of us will build the curriculum that suits him or her the best. The "diplomas" and itineraries will be as numerous as the learners. The diploma will no longer be a piece of parchment paper issued by a particular institution. There will rather be personalized sampling of the courses given by a large number of institutions. The constraints of time and geography will have gone with the wind. A diploma will no longer be the threshold detested by Paul Valéry. It will be a permanent individual and group building effort.

The virtues of syndication

How will this granularity affect existing institutions? There is a high likelihood of creation of granular models of "coopetition", which means models in which educational institutions agree to cooperate while competing with one another. This is already happening in Europe in the framework of the Erasmus exchanges and the ECTS scheme. MOOC technology will render it systematic and, crucially, planetary. One may imagine Harvard "labeling" a MOOC originating in Yale and integrating it to one of its degree-granting programs. Just like EdX and Udacity, Coursera will surely be called upon to become a MOOC syndication platform. Syndication will enable it to institutionally monetize the MOOCs available on its platform and by doing so, to generate income while remunerating the universities rightholders.

A wealthier ecosystem

Coursera and the other educational technology companies herald the arrival of pure players whose talent will consist in selecting among the dedicated portals the relevant MOOC "bricks". One may imagine a group of reputed professors building a platform containing their own MOOCs combined with those having been syndicated around, say, Coursera. The platform's validity will be premised on the professors' reputations and the originality of their proposals. This is where free-of-charge access takes on its full meaning. Indeed, it paves the way to setting the prices of syndication. The most popular free courses will, once syndicated, become the most expensive. It is also clear that academic institutions with a poor reputation will be called into question, as is made crystal clear by Professor Timothy Devinney:

"Having been at the top and bottom of the academic food chain (being both at U. Chicago and now in Australia at what is dominantly a teaching factory) I have seen the differences. The students at Chicago get knowledge at the coal face by people who understand what is both leading edge and sophisticated. Students here get commoditized information delivered by individuals who only know what they read because they are not leading edge scholars. Indeed, where the MOOC Tsunami will hit is on this commoditized end of the business."

Timothy Devinney, http://www.ft.com/cms/s/2/cde6163c-7f4a-11e2-97f6-00144feabdc0.html#axzz2QABQsuIB

Research: 1 point; Pedagogy: 1 point

The above remark by Timothy Devinney calls for a commentary. It may be considered as elitist insofar as the perfection of an academic institution would mainly reside in the quality of its professors' publications. We will not take sides in a debate as to what determines the scientific value of an article. This is neither the time, nor the place. On the other hand, Devinney's emphasis on the importance of scientific research spurs us to ask questions on the reasons for its omnipotence. One of them has to do with digital visibility, which reaches its peak in businesses or institutions such as Elsevier, SSRN and ArXiv. The articles and their authors are visible. They are digitally accessible. Up until recently, however, pedagogy and the pedagogues were not exactly in plain view. More precisely, they were visible within but not outside the walls of academia. Research carried the day for want of a visible opponent.

Emergence of the MOOCs represents a new deal. The pedagogues become highly visible. We can henceforth take it as a given that the promotion of professors will no longer exclusively depend on their research. It will also hinge on their pedagogical savvy and savoir-faire. In this respect, the filtering mentioned above will not involve the learners alone. It will also involve pedagogues, whose pedagogy will at long last be seen in the light of day. Learners will filter with the rigor and vigor that the Net encourages. Academic institutions will strive to hire the best pedagogues in order to endow their portfolios with the richest, most widely varied and relevant, not to mention the most audacious MOOCs.

Going off the (re)beaten tracks

At this time, MOOCs are still anchored to the curricula of academic institutions. In their seminal phase, it is par for the course that they rely on existing infrastructure. However, the audaciousness of the offer consists in their emancipation from existing forms. Teachers will have the opportunity to experiment with courses outside the tried-and-true taxonomies. More broadly speaking, a recovery of pedagogical liberty will be given impetus by an open invitation to take risks and engage in pedagogical tinkering. MOOCs will to an ever lesser extent be homothetic to a preexisting frame. They will rather devolve into a privileged field for large-scale experimentation and collection of data efficaciously contributing to the understanding of learner behavior. New subjects will emerge, and they will flout the usual disciplinarily specialized pigeon holes and compartments.

The art of conversation or the art of exposing oneself to risk

MOOCs restore prominence to the art of conversation that Michel de Montaigne held so dear as to prefer a brain well-formed to a brain well-filled. Today's classrooms remain hierarchical organizations in which pedagogy is aimed at filling heads up. However, it is obvious to any visitor in these precincts that heads are no longer content to be docilely "crammed". Quite on the contrary, they converse, they chat either physically or virtually. Only distractedly do they hearken to what's being professed on the podium. They are free because they know that the connected place providing access to the stock of knowledge is right before their eyes: the laptop, the tablet, the smart phone are screens that screen out the academic monologue. And new heads require new rules of engagement compatible with the tools they are helping to fashion. The "knower" (the professor) finds himself amidst the "knowing" (the students) as primus inter pares, first among equals. He has no choice but to run the risk of casual, informal conversation. He has no choice but to lay down his arms as an authority figure and to recognize that far from being the sole driver, he is himself a passenger. The knower and the knowing form an enigmatic couple that brings to mind the hedgehog and the fox, of whom the first recorded mention dates back to the 7th century before Christ. In a stand-alone verse of the poet Archilochis, as cited by Isaiah Berlin, we may read:

« The fox knows many little things. The hedgehog knows one big thing."

In more recent words, "The hedgehog always remains at the same place, stalking the prey within its reach. As for the fox, he is ever on the move, hunting for a wide variety of game." (Irène Tamba (2012)).

The professor, or the hedgehog, the porcupine, symbolizes centripetal force. The student, or the fox, symbolizes centrifugal force. If a classroom wishes to have a ghost of a chance of renewing its "aura", it must mutate into a space of sharing, of invention, of assumed orality. But that alone cannot suffice. The site where the rejuvenated class will provide new food for thought shall have to be re-conceived. Its architecture should not survive in a form inspired by "power point" pedagogy. Its libraries must not remain storage zones. Its territory has got to be transformed into an agora where silence is the exception, and not the rule. All told, campus architecture will need to be reviewed to as to emancipate itself from the "Roman camp" model castigated by Michel Serres.

The digital "trivializes" pedagogy, rendering it reproducible. By contrast, the physical pedagogical site cannot and must not be trivial. It has got to be difficultly reproducible, it has got to make the seeker of knowledge desire to enter. After all, it is a site made for meetings of minds, and that is the way it has got to be thought out. It has got to be unique, and equal to the challenges posed by the encounters, the "hic et nunc" exchanges between human beings who will never be wholly reproducible.

To whom does knowledge belong?

A MOOC is structured around one or several professors, who hold positions in academic institutions. How are we to define intellectual property when knowledge is disseminated via a MOOC? Let us imagine for illustrative purposes that a Yale professor, author of a successful MOOC, leaves his university for Harvard. Is he the proprietor of his MOOC, or has he ceded the copyright to the university of which he is now an employee? Once employed in his new university, can he bring into being a similar MOOC without being considered as an intellectual hacker? The intellectual property issue is far from negligible, and it shall need to be treated with vigilance and diligence by the universities intending to utilize MOOCs. One may imagine that a system similar to the one governing the economy of books will be put into place. While the professor will take on the role of the author, the university will assume the role of the publisher. The publisher will agree with the professor on contractual terms, operate the MOOC of which the professor is the author, and remunerate him according to the sales recorded by the MOOC.

How to evaluate, to certify, to accredit?

Traditionally, an educational system hinges in the notion of grade or mark, of an evaluation given by instances the legitimacy of whose authority cannot be called into question. With regard to MOOCs, on the other hand, observers have noted some trending towards peer evaluation, which is no longer wholly vertical, but also and significantly horizontal. On this subject, a method has been set up in Coursera (http://help.coursera.org/customer/portal/articles/1163294-how-do-peer-assessments-work-, https://www.coursera.org/about/pedagogy ).

This assessment is premised on the community-based dynamics constituting one of the guiding principles of the MOOCs. A student can draw support from a widespread network of other students registered for the same MOOC. Horizontal pedagogy both complements and supplements vertical pedagogy. Mutual pedagogical assistance brings together students who up until the moment before were total strangers. Digital solidarity is a common phenomenon on the Web; question & and answer forums are but one example. As concerns MOOCs, it is of paramount importance. In fact, digital solidarity is their alpha and omega, and it is no surprise to find it present in the assessment process.

What happens to confidentiality?

This is a recurrent preoccupation on the Web. Whether voluntarily or involuntarily, Internet users leave behind a number of tracks and traces that pique the interest of businesses. MOOCs can hardly be immune from ongoing debates on protection of private data. It is all too easy to imagine the hunger of companies for the academic records of MOOC users, which are essentially open for inspection! This is by no means an unreasonable concern. Data are a strong currency, and we shall not leave them in the hands of digital speculators. That much said, it must not lead to obliteration of the collective intelligence that aggregation of individual information allows to emerge. This is a fine line, but as always the devil lies in the details.

In praise of Babel  : What is to happen to public education authorities?

MOOCs are a homage to the Tower of Babel. Persons from hundreds of countries converge towards the MOOCs, which are derived from similarly multifarious professors and universities. Their diversity is an undeniable source of wealth. However, it just as undeniably raises questions concerning the supervisory authorities in public education and their mission consisting in the recognition of diplomas. Once degrees have become granular or gone so far as to disappear, what role shall national ministries of education and higher learning have to assume? What will be their missions in a geographical perspective dispensing with boundaries between nations?

At the end of 19th century, Ferdinand Buisson, a French General Controller of the Ministry of Education , tried to make "play hooky" part of the official instruction process through a method he called "the intuitive method":

"Sirs, the intuitive method is the one that tells the teacher: your task is heavier by the day. It is getting more complex. To get it done, you need to be helped. By whom? By good books, good tools, good programs? Yes, of course but even more by the student himself. He is your most reliable auxiliary, your most efficient co-worker. Make sure that instruction is not imposed on him. Make sure he takes full part in it and your problems will be solved. Instead of pulling him to make him advance, he will happily walk with you."

The core of the game has not changed that much! MOOCS are play hooky at its best. Play hooky has always been viewed as a bad habit. It is considered futile musing. But kids playing hooky are close to real life, playing with insects, looking at flowers and trees, gazing at the clouds, listening to bird songs. Their get a lot through their musings. They just need someone to give them some perspective to fully learn from their escapades. That's what MOOCs do at the end of the day. In his best seller "A Whole New Mind"; American author Daniel Pink writes:

"When facts become so widely available and instantly accessible, each one becomes less valuable. What begins to matter more is the ability to place facts in context and to deliver them with emotional impact."

So it goes with pedagogical contents. When they become so available, so abundant and accessible in so little time, they take on less importance. On the other hand, the ability to put them in context and provide them with emotional impact is perhaps what matters most.

Today's upheavals are particularly captivating insofar as they are likely to call upon our cognitive processes in many more ways than one. Subsequent to the works of Professor Roger W. Sperry, winner of the Nobel Prize for Medicine, we now know that the two hemispheres of our brain fulfill different yet complementary functions. The left hemisphere is the site of sequential thinking; the right hemisphere is the site of simultaneous, holistic thinking. Daniel Pink sums up the duality as he writes:

"The left hemisphere specializes in text; the right hemisphere specializes in context."

To summarize by once again citing the celebrated fox/hedgehog aphorism dating back to the 7th century before Jesus Christ, the left part of the brain assumes the role of the hedgehog, while the right part is reminiscent of the fox.

MOOCs favor learning through tinkering. They enable us to learn many things. What matters now is to endow this sequential tinkering with meaning and to arrive at a synthesis, what Daniel Pink calls right-brain thinking. Classroom pedagogy, which has so often been premised on left-brain thinking (an almost cult-like status), is challenged to capitalize on right-brain thinking. A pedagogue has to place himself at risk: he has to ignite his faculties of emotion, of esthetics, of context, of synthesis, of overview. Excepting the initial conception of MOOC, he is no longer the pope of left-brain thinking. In his pedagogical art, he has got to transform himself into an apostle of right-brain thinking. The architecture of the campuses in which right-brain thinking is called upon as likewise got to be comprehensively transformed.

Today's campus architecture, which is built around "Power Points", corresponds to a situation where hedgehogs try to train foxes. The future architecture of campuses shall have to develop in such a way that foxes and hedgehogs can switch roles in the same space.

In his Essays, Montaigne wrote that he preferred a well-made to a well-filled head. A full head is inclined towards left-brained rather than right-brained thinking. As of now, one shall not have one without the other. When push comes to shove, a well-made head is an hybrid one that details and connects; neither function systematically wins out over the other.

In an age of technical and digital reproducibility, pedagogy has to rise to the challenge of facilitating the flourishing of well-made heads that do play hooky! 

 

The Digital Gilded Age: The Elusive Quest for the Catch-All Corporate Metric

Management, these days, is full of corporate metrics that managers are urged to follow, to maximize or to minimize, in any case to outperform: EVA, CFROI, shareholder value, etc... to name a few.

The theory underlying these catch-all metrics boils down to the idea that following them is good for the corporation as a whole. As a result corporate decisions should always be benchmarked against them. In a nutshell, what is good for shareholders is also good for the firm as a whole. Managers who do well with respect to the metrics shall then be handsomely rewarded.

Surprisingly enough, the discussion around the true relevance of these benchmarks is rather tenuous. Yes, market imperfections are discussed and principal-agent models, game-theoretic-models have been crafted to discuss situations when incentives of different stakeholders are not properly aligned.

However, it is rather puzzling that a principle known under the name of "Goodhart's law" is hardly mentioned in business books. The law is named after Professor Charles A. E. Goodhart, Norman Sosnow Professor of Banking and Finance at the London School of Economics, who crafted it with central banking in mind. According to the 99th edition of Pears Cyclopaedia (1990--1, pp. G 27, G31), the law states that:

"As soon as the government attempts to regulate any particular set of financial assets, these become unreliable as indicators of economic trends."

"financial institutions can... easily devise new types of financial assets."

Professor Charles Goodhart was Chief Adviser to the Bank of England. He gave his own statement of the law in his Monetary Theory and Practice textbook, page 96:

"Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes."

In other words, when a measure becomes an objective, it is no longer a good measure. Too much emphasis on a measure as a target kills the measure that may have been relevant in the first place. Why? Because it is all to obvious that people who are subject to a given metric (say, outperform some profitability index) will do whatever it takes to beat it. They will game it as much as they can. For instance, in the case of an asset profitability ratio, they will minimize the denominator (assets) instead of maximizing the numerator (profit). This will last as long as the asset accounting trick is not discovered. And, this can last long: It was recently discovered that Toshiba manipulated its profitability seven years in a row! The more distant history is also quite rich in such stories, chief among them that of former USSR and its obsession for production targets (yielding the results that we all know about).

Now, even if metrics parameters are not manipulated, metric based management and compensation is not a good idea at all as it tends to reward (convex exposure to) luck rather than skill. Take the example of stock-options. A lot of managers became wealthy upon their exercise. Was it because they were remarkably skilled or just because it turned out that interest rates were going south lifting the stock price? How do you distinguish between what is due to chance and what is due to skill? Is not it unfortunate that metrics end up paying well people that were simply in the right place at the right moment?

Worse, in economies like our today digital economies which are highly non-linear (knowledge-based economies, complex systems, winner-take-all etc...), it is not even clear that any such measure does exist. More often than not, obliquity is at work. Metrics are very poor at capturing the richness and complexity in which we live and operate. They simply don't work.

So, why is that most business books authors and professors forget about Goodhart's law as if they were petrified telling students that, indeed, the oblique world outside is not made for metrics?

 

The Digital Gilded Age: Digital Obliquity

The objectives we reach are rarely those we had set at the start. British economist and columnist John Kay,(www.johnkay.com), calls this salutary deviation "obliquity".

The zeitgeist seems anything but oblique. Businesses and managers are asked to focus all their efforts on one goal only: to reward their shareholders, namely maximize their wealth. To fulfill this task managerial metrics are legion "Economic Value Added", "Cash Flow Return on Investment", "Risk Adjusted Return on Capital" etc ... Similarly, we measure the wealth of nations in terms of the gross domestic product (GDP) despite its numerous defects. GDP is the goal. To correct the GDP deficiencies, it has been suggested to use an Gross Happiness Product (GHP). GHP should be the next goal. Shall we really abide by these metrics? Or shall we be skeptical about their merits?: It is indeed easy to game them especially if one is handsomely rewarded for outperforming them. Are metrics good guides for action in the hyper-connected world in which we live assuming they are not gamed?

John Kay has a nice oblique story to show that we should beware. This is the story of the American Department of National Parks. One of the priority tasks of the Department is to protect forests and prevent them from being devastated by fires. There was a time when that mission took a very simple form: zero tolerance. Any fire should be extinguished. No fire outbreak was tolerated. In practice, this firm policy turned into rather embarrassing statistics. Instead of a reduction in fires, US officials observed an increase in fires. Their mission had failed. The objective was not reached. How come rigor was so poorly rewarded?

We must let the ground speak. The forests are dense environments in which bushes and trees coexist. These bushes are a potential threat. They can fuel major fires. It is therefore advisable, in addition to manual undergrowth clearing, to let small fires complete the job. Thus, instead of implementing a drastic zero fire tolerance policy, the Department would have been wiser to let rangers on the ground gauge the situation and decide whether or not to intervene. This holistic approach prevails today.

Such an adaptive approach is particularly relevant in systems where small variations may entail subsequent changes of great magnitude. The flagship example is the butterfly whose flapping wings in Africa trigger a violent tropical storm in the Caribbean a few weeks later. What this example essentially says is that complex systems are very sensitive to initial conditions. A slight change in a parameter (the wing flapping) is followed by a radically different system response. The system nonlinearities route the new response along brand new and, more often than not, unexpected paths. Complex systems like forests, fires, weather behave in a nonlinear fashion which implies they are unpredictable.

The digital economy exhibits a similar nonlinear behavior. Its complexity increases at the hectic Internet connectivity pace. This never ending branching process creates a vast archipelago whose many islands are no longer independent of each other. Its growth is such that what gets big is deemed to get bigger or to vanish. Moreover, our societies have moved from a mainly physical economy of perspiration (which Jack London documents in the Abyss Society) to an inspiration driven (digital) economy. Does it make a difference? Yes it does!

Firstly,it does because the world of ideas is different from the world of hard assets (notwithstanding the fact that hard assets are themselves the product of ideas). Ideas do not have the same properties as traditional assets. The fact that I use Pythagoras' theorem does not prevent you to use it at the same time. It is available for other people to use. But if I drive my car, another person cannot drive it at the same time as me. Ideas may eventually grant a legal monopoly power. A patent, a copyright allow its holder to define terms of use by third parties.

Secondly, it does because the economy of ideas is characterized by a very particular production cost structure. A standard perspiration good must be manufactured unit after unit to be sold. Each unit requires the mobilization of fixed and variable costs. It comes at a strictly positive marginal cost. An inspiration good is different. The original unit requires a significant initial investment outlay. The next units are copy/paste of this original unit. Hence their marginal cost is close to nil. Take the celebrated example of Microsoft's Windows software. Microsoft charges a hefty price for each copy of the software despite the fact that the cost of each extra copy is almost zero. Microsoft is able to extract a rent, a float from its clients. It enjoys monopoly power. Economists teach that the best way for an economy to be prosperous is to foster competition. Competition will eliminate rents as long as prices are not equal to the marginal cost. At this level profits are said to be normal, to be fair. But if we were to apply this competitive pricing rule to, say, Microsoft it would go bust. It would have to charge zero for its software as indeed its marginal cost is nil. It would be unable to recoup the initial outlay. In order to survive and be profitable, Microsoft needs market power. If things go well, it becomes the winner, the winner who takes all.

The question is then obvious. How does Microsoft reach this "managerial nirvana" without prematurely passing away? To answer this question, American economist Brian Arthur of the Santa Fe Institute compares the world of the British economist Alfred Marshall (1842-1924) to that of increasing returns to scale. The world of Marshall is an industrial world with capacity constraints (a plant cannot produce more than its capacity) and diminishing returns (once the capacity is reached returns tank). In this world, one day or the other, the profits converge to their "normal" level. In his Principles of Economics, Marshall demonstrates that this result obtains through optimization techniques, derivatives of cost functions etc...

The world of increasing returns to scale is totally different. This is a world where things move potentially very quickly: those that increase increase even faster, those that fall down shrink even faster. The typical example is network effects à la eBay. Sellers join eBay because they know that buyers are there. Buyers join too because they know they will find sellers there. The winner, eBay in this case, takes all. The more it does, the more it does! We can say the same about Twitter, Instagram or Facebook. The consequences of such a world are well known: imperfect competition (must be able to charge more than the marginal cost), uncertainty (a small change, a mistake can upset all), unpredictability (can't predict in fast changing nonlinear world), "winner take all" and record profits for the winner (2 + 2 = 8). This is how Microsoft got its Windows market power. This is how the most sought after Unicorns are born!

How should individuals, institutions, businesses and governments behave in a world so different from that of Marshall? Should they optimize, fine-tune metrics and try to outperform them? Or should they adopt a holistic behavior like US forest rangers?Well, it seems sensible in our world (which is a mixture of the Marshallian world and the Arthurian world) to develop a strong sense of adaptation. The world of increasing returns is really an oblique world that can play tricks on us. To garner "hits", metrics, whatever their "sex appeal", won't work. They are the sure recipes for failures. A slight mistake in the metrics and everything falls apart for good or bad. One cannot, for example, understand why Facebook paid so dearly to acquire Instagram or What's App using standard Marshall thinking. Facebook, despite its sheer size, is not immune to the digital flapping. Facebook was created at a time when the mobile smartphone revolution had not yet been "fomented". Instagram however is a genuine product of the smartphone phenomenon. This is its DNA. Instagram or What's App wing flapping may cause a storm at Facebook: A team of thirteen person and a small app were able to attract millions of users. At the time of its difficult IPO, Facebook could not take the risk of either Twitter or Google rounding up Instagram or What's APP. This is certainly a costly but ultimately very oblique bet. For, no one can say today what future "business model" will eventually justify or invalidate the amount paid. What is sure is that Facebook did not want to miss the smartphone crowd, the related advertising money and of course the the formidable data aspirator that both apps constitute.

Digital obliquity should also be pondered by governments and regulators. Governments in charge of drafting the institutional framework conducive to the prosperity of their nations must accept that the digital economy they contributed unleash requires a flexibility incompatible with their partisan ideologies. The cherished (linear) cause to effect link no longer works. Governments must adopt a Louis Pasteur stance: "chance favors the prepared mind." Serendipity must become the keyword of their programs even if serendipity seems to deprive them of any control on events.

Regulators should resist the urge to regulate everything, to codify everything, and above all to do it too soon. Regulation that wants to eradicate piracy (zero tolerance to fires) is an example. Moreover, it is the exact opposite of the "habeas corpus" dear to the Anglo-Saxon. The presumption of guilt becomes the rule. It is up to the innocent to demonstrate that he really is. It is not by enacting such drastic legislation (inspired mostly by incumbent corporate interests), by not listening to what pirates are saying that one prepares the nest of future business models.

The eagerness with which the French law on e-book prices has been passed is a vivid testimony of what not to do. In short this law says that only the publishing house can set the price of an e-book. This price has to apply to all distributors at the same time. The truth is that the sole purpose of the law is to protect the print book chain (from authors to readers through publishing houses, distributors and booksellers), to duplicate it in the digital world. A chain that becomes truly one, unable to unchain, unleash and redistribute productivity gains. This law is everything except oblique. It tries to freeze things instead of providing market players with the proper incentives to digitally adapt and innovate.

Famous British detective Sherlock Holmes would have clearly objected to it. In the Valley of Fear he reminds one of the protagonists the extraordinary value of being oblique:

"Breadth of view, my dear Mr. Mac, is one of the essentials of our profession. The interplay of ideas and the oblique uses of knowledge are often of extraordinary interest."

And he was not living in the digital gilded age where obliquity is the name of the game!

 

The Digital Gilded Age: Be convex, unswap!: Towards a new cottage capitalism

"History does not repeat itself, but it often rhymes" as Mark Twain is reputed to have said. 

There once was a so-called cottage capitalism. The emblematic tools of this cottage capitalism were the spinner's wheel, the weaver's loom, the nail-maker's forge..., and its home country 19th century Great Britain. From a 1861 census, England and Wales more than a million people were one way or the other cottage entrepreneurs, or cottage workers to be more precise. They were sewing clothes, shirts, hats, ties, gloves or forging nails from home. Most of them lived in the countryside. With the rise of the factory and its machines, cottage workers could not compete with factory workers, and they gradually disappeared. Physical capital was expensive, and only robber barons could afford to fund it.

Today, history rhymes. In reverse. Cottage capitalism is back, as, unlike its physical counterpart, digital capital is cheap and affordable. This is a true opportunity, and as long as we manage to keep robber robot lords at bay we may indeed see a move back from the factory to the cottage. 

 

The Digital Gilded Age: Average is mean

Averages are addictive. Whatever the quantity of interest (heights, weights, financial returns, interest rates, rainfall levels, temperatures, economic growth rates, budget deficits, sales, costs, income, wealth per capita, speed...) it is first summarized by its average. When it comes to predicting the value of a random variable from past observations (like the stock market return next year) averages come again into play. But, as we all (should) know: "The expected value is not to be expected". This is a casual way of saying that computing an average inevitably loses information about the structure of the data it aims at synthesizing. In other words, averaging yields a trade-off between data compression and information loss. Information compression makes it handy to deal with large samples of data. Compression however has a cost. Indeed, knowing the average height of students in a class is of no help to the tailor in charge of sewing the individual school uniforms! If he were to sew an average size uniform, some students would end up with trousers way too short while others would wear jackets too big for them.

The information loss is well monitored in the case of the famous bell curve, also known as the normal distribution. In this popular distribution data are symmetrically spread around their mean. Their dispersion around the mean is measured by a parameter called the variance which happens to also quantify the information loss if one were to squeeze the whole distribution to its mean. The bell curve is appealing because although data are dispersed around their mean they remain in a tight neighborhood to it. Student heights is a good example of this behavior: For a given age class, say 18 year old, there are no student measuring 3 meters or 90 centimeters. There are tall students as well as small ones. However they do not deviate that much from the average height. As a result, the mean and the variance are enough to capture the full distribution.

Is it always that simple? Of course not. It all depends on the context from which the data are drawn. If the data relate to weight, height and the like the bell curve is a good approximation, and the average conveys a valuable information that can be benchmarked against the variance. Now, what if we look at wealth per capita levels? Assume hundred people in a room. Their average wealth is, say, $180 000. Enters Bill Gates. The average is computed again, and now it is worth, say, $300 millions. This figure makes no sense at all. One single individual out of 101 affects the whole result. Hundred individual are well below the mean while one is well above it. The bell curve does not work, and the average wealth does not make any sense. Under this scenario the average is mean indeed. The same holds true for floods. The average flood is of no interest to the bridge builder. If he were relying on it, the bridge would not last long for sure. Rivers like wealth processes are too complex to be bell-behaved! Although the bell curve is called the normal curve it is not the normal state of affairs. Things that matter most to mankind are not normal. Think of how connected the economy has become: one small change somewhere may trigger a sequence of events that lead to a monstrous event. Think of the weather and its nonlinear intricacies. The string of factors, be they meteorological, social or economic, will magnify the initial change in ways that we are more often than not unable to monitor, not to say understand. Averages can no longer be trusted.

How come then we spend so much time and resources to estimate averages, dispersion measures, probability distributions while we simply fool ourselves? We become preys to our own inevitable errors, errors that can be lethal in hyper-connected times. This is sad: we should rather strive, as Nassim Taleb puts it, to "live happily in a world we do not understand." When we devote significant resources to model a given variable, say, x, and to estimate its average we forget that what matters is not x itself but how we are exposed to it, say, f(x). The function f describes our exposure to x, for instance the gains and/or losses associated with various values of x. Suppose x stands for floods. The function f may describe the damages to our home that floods could trigger. Whatever the depth of our knowledge of floods our house will not be spared if it sits next to the river. What matters is not the knowledge of x (namely floods) but f(x), namely whether our home is vulnerable or not to floods. Nassim Taleb calls the confusion between x and f(x) the conflation error. Whatever the accuracy with which we measure flood levels, one day our home will be flooded if we build it in an exposed area. That very day we will be hit by Nassim Taleb's famous black swan.

There is an easy way to live without the fear of the flood black swan: build our home away from rivers or seaside, namely change our exposure. Indeed,some battles do not deserve to be fought! But even if we are careful enough to avoid the conflation error, we are not done yet. Our effort should now be directed toward the understanding of the shape of function f(x). Is it linear? Is it convex? Is it concave? In other words how does it behave in response to changes in x. When x changes, does f(x) change more or less than x? This is a major question that we cannot escape especially in times of growing inequalities, winner-take-all dynamics and fast automation. To understand why let us look at the fate of the middle-class. The middle class that was once the symbol of prosperous economies is hollowed out. Shooting for the average position has become a very hazardous stance. Over the last few years, jobs have been more and more polarized. At the upper end the cognitive jobs that benefit from automation fare rather well both in terms of offerings and wages. Through automation they become more productive. They can do more while delegating the ancillary tasks to automation. At the lower end, employment in manual-task intensive jobs that machines cannot replicate (like say cleaning, services to the persons etc...) have risen. These jobs however command lower wages as a lot of people are chasing them including the hollowed out middle-class people. In the meantime jobs in the middle are eaten by software at a fast pace.

It really does not pay to be or to stay in the middle. Jobs prospects are better at both ends than at the middle. This hollowing out of the middle-class is stronger in an economy framed by increasing returns to scale and winner-take-all effects. The upper end captures most of the gains while the lower and middle ends have to share the leftover. Digital automation means that a growing share of income is currently going to capital owners. This effect is usually known as "capital-biased technological change" although I fear, if things do not change, we may have soon to call it robber robot lords biased technical change. To use Nassim Taleb's words, we may have entered into a barbell economy. Is this is good news or bad news?

The obvious and immediate bad news is that the formerly praised middle class is being "stolen" from us. Robots, software and machines take over the jobs that once made a significant portion of the society well-off. This middle Golden Age may not return, and for many it is indeed awful news. The good news rings like a salutary wake-up call. It helps understand why the average can be truly mean, why average may translate into fragile. Indeed, the hollowing out of the middle class provides clear evidence that it is fragile: it is vulnerable to external shocks such as technology driven labour market shocks. It loses from them more than it may gain. Automation lower production costs. Middle-class workers gain through lower consumption prices, but this gain is illusory when at the same time they lose their jobs. This observation brings us back to the exposure issue, to the conflation error in which x is often confused with exposure f(x). Assume that x stands for income. At the risk of oversimplifying being a middle-class member means that one earns the mean of x. Let us call it mean(x). The function f(x) describes the gains and losses associated with earning income x. Function f may include all sorts of things including well-being, satisfaction related benefits, accomplishment, status, prestige, etc... Let us take the example of an ultra simplified economy. In this economy the middle-class people are subject to random shocks that may depress their income x or increase it. Let us assume that a sudden technological shock occurs: A piece of software has been invented that automates middle-class routine jobs. The product that used to be manufactured by the middle-class worker can now be sold for free. What is the outcome? Holding the "average" job makes the middle-class worker vulnerable to automation duplication. As a result, he loses more (his job) than he gains (his purchasing power). As a thought experiment, imagine a fictitious individual who over a given period of time swings between times of low income and times of high income. Let us compare this fictitious individual with the middle-class earner (who constantly earns the mean income). As the middle-class worker has more downside than upside his "satisfaction" from earning the average is higher than the average "satisfaction" he would feel from swinging back and forth, namely if he were the fictitious worker. This spread is a valuable signal. It shows that middle-class workers overestimate the true state of their condition given their (concave) exposure to technological disorder. In other words randomness and harm are both underestimated. Once the exposure has been properly taken into account, it turns out that the seemingly stable and robust middle class is an illusion. Middle-class people are closer to the fictitious swinging individual than they think, and this is something they should be aware of. The average is indeed a liar. Northwestern University Professor of Economics and History Joël Mokyr summarizes the situation very nicely:

"Modern technology often leads to winner-take-all outcomes, and the inequality implications in terms of income – though not in terms of access to the good itself – are worrisome. What we gain as consumers, citizens, viewers and patients we may lose as workers. The demand for labour 'hollows out' and the demand for medium-skilled labour declines unless and until new jobs are created to absorb those replaced by automatons and robots."

The situation of cognitive well-paid workers is opposite. They gain from digital disorder, at least as long as the disorder outcome is software that complement their skills. They for sure gain more than they may eventually lose especially in presence of increasing returns to scale and winner-take-all effects. Their skills get augmented by the digital leverage of software. Here again the average is a liar. It underestimates the true situation of cognitive workers. Indeed, while middle-class workers are concave to external shocks cognitive workers are convex to these shocks2. As Joël Mokyr, Chris Vickers and Nicholas L. Ziebarth observe:

"routine tasks with little unpredictable variability are more likely to be mechanized, while jobs that require continuous adjustment to new information and new physical settings along with fine sensory motor-coordination are more difficult to automate."

Their observation is valuable on two accounts. First, it seems that jobs that themselves contain an intrinsic dose of disorder are those that are more difficult to hand over to machines. Moreover machines or software may help people holding these jobs become even better at them by relieving them from ancillary time consuming tasks. Second, lower-skill workers are now competing head-to-head with middle-skill workers who have no other job choices. Wages decrease as a result. These job market movements entail a growing bipolarization in which a larger percentage of the population chases lower paid jobs while a minority enjoys the riches. As a result, and as we noted earlier, the economy is now entering a barbell mode with strong dynamics at both its low end and high end and vanishing ones at its middle. The inevitable question is whether or not this "barbellization" is sustainable. In other words, the average is mean, but is there life beyond the average?

I think it is no coincidence that the barbellization takes place at the same time of what I call the Faustian "free against your data" swap occurs. Software, machines and artificial intelligence require tons of data. The easy way for robber robot lords to siphon them is to offer free services in exchange of them. Software then eats the middle because it has indeed been fed by the middle. A strong (data) currency has been traded by the middle against a rather weak (free) one. This is why Joel Mokyr, Chris Vickers and Nicholas L. Ziebarth observe that

"in a world of cheap goods, while inequality in terms of wealth or income may rise, inequality in the form of access to "primary" resources would greatly be diminished."

In other words, the lower end and the middle gets poorer in absolute terms, but they should not complain too much as they now enjoy free or low cost prices. What they lose on one hand, they regain it on the other hand. It remains however to be proven that the balance is (or will be) fair in relative terms. The massive use of data has another consequence which the optimists call the sharing economy while the pessimists call it the on demand (precarious) economy. One metaphor is often used these days to describe where this on-demand economy is heading, namely the Uberization of the economy. In short, old corporate fortresses with their legions of full time employees are torn apart to give place to data driven light structures with flexible on-demand workforces. As a result it is not only (middle) jobs that are disappearing. It is the very nature of work that is changing. This change takes place not only through self-employment but also and above all through a new breed of firms that match online in real time tasks and workers. Uber, Amazon's Mechanical Turk, BlaBlacar, AirBnB, etc... are the best known. Lawnlove (on-demand gardening), KitChit (on-demand cook), GoldenShine (on-demand domestic cleaning) are other less known examples of the same trend.

As always this buoyant activity carry good news and bad news. The bad news is that this on-demand workforce may indeed become a precarious workforce. It will have to face significant uncertainty as to when and where it will be called for a task and how much it will receive while at the same time having to cope with regular and fixed living expenses. Moreover modern work conditions are stress conducive as we all know. Stress levels may become worse. They may even outweigh the benefits of working from home, namely achieving a better balance between work and family life. There is also the obvious risk that employers may take advantage of their position especially with lower income workers that are easily substitutable. The on-demand flexibility associated with random revenues also begs the question of social coverage, of taxes, of access to housing... It is quite clear that we have entered into unchartered territories that the visible hand will have to thoroughly investigate to foster and preserve accountability and sustainability. The current fiscal, social and regulatory frame designed for other times is ill-suited for the new issues at stake. The new framework will have in to ensure that robber robot lords do not exhibit predatory behaviors. While this issue is being taken care of, the new framework shall provide the settings for a reshaped work landscape.

Indeed, if we manage to keep the robber robot lords at (political) bay, if we succeed in regaining legitimate power on our data, good news may be in store. Things went bad for the middle class workers because of the fragility of their concave technological exposure. It does not have to be so. Digital capital is cheap, and the cost of production is getting closer to the cost of reproduction. Convex exposure to digital capital is easy to get into, much easier than convex exposure to physical capital. In other words, it has become easy for people to own and manage their digital capital which in turn means that we may see cottage businesses blossoming. Obviously this does not imply that everybody is a born cottage entrepreneur. It means that people with ideas to, say, better service their local community can experiment them, tinker with them with a small downside and a truly rewarding upside. This is the best way to put oneself into a convex position where there is more to gain than to lose, where the feeling of having achieved something is at its peak. At last, it will happen provided the visible hand has worked hard to make it easy to ignite.

Despite the good news one shall not minimize the unavoidable adjustments that we will have to weather in the short and medium run because "average" is no longer good. A lot of people fell victim of the illusory comfort of reaching and belonging to the middle class. They did not realize the dangerous exposure (the other side of the coin) that being average implies. By the same token they also bought the miraculous digital bounty of what I call the Faustian and unfair "free against your data" swap. Sadly enough, wealth and income inequalities powered by increasing returns to scale and winner-take-all dynamics have simultaneously soared yielding a bipolar economy. For this economy to be sustainable, for the upper end not to divorce in unbearable ways from the lower end will require more than the charity of the upper end. It will require smart visible hands (an oxymoron for a lot of scholars) to make the two sides of the barbell accountable to each other. Otherwise, we will end up with a more and more concave lower end and a more and more convex upper end. The lower end will be enslaved to robber robot lords devouring the lion's share of productivity gains.

To put in (too short) a nutshell, the middle was stolen from us. While the middle was no panacea to say the least let us make sure, thanks to the cheapness of digital capital, that convexity is truly ours, that it will not be stolen from us. Digital winds shall fill all sails ready to venture afar. As I write nothing is less sure! 

 

The Digital Gilded Age: In Vino Veritas, In Data Veritas?

Wine tasting usually rhymes with friendship, memorable moments and harmony. It is hard not to remember the deep purple color, the unusual nose and blended flavor of a 1985 Côte Rotie Côte Brune. Wine is distinctly magic. It is a subtle hyphen between people.

Wine is also an investment. You buy wine to drink it a later. You hope that at the time you sip your wine it has become a great wine, an unforgettable one. You may by the way either drink it or sell it at an auction. If the price has gone up, you may even drink one case, sell the other and end up with more money than you initially invested. But nothing is sure. Only times will tell it seems. Winemakers are in the same uncertain situation. After the crop, (Bordeaux or Burgundy) wine has to age in oak casks for eighteen to twenty-four months. It is difficult to figure out from tasting wines in their early stage whether a great vintage is in the making or not. Hard to tell whether the business will be good or not.

Since 1978 one man has held the wine forecast podium. His name is Robert M. Parker, Jr. He is a wine guru, maybe the one and only of his kind. He spends tree months of every year tasting in vineyards. He then publishes grades for each wine he has tasted. His swishing and spitting approach has made him world famous. Every year wine amateur and wine professionals eagerly wait for Parker's verdict. Robert Parker publishes his grades in a newsletter entitled The Wine Advocate with more than 50,000 subscribers. In the late eighties Parker's dominance was challenged by one man who claimed that one cannot predict how well a certain vintage will age just by tasting it.

Princeton University economist and former editor of the American Economic Review Orley C. Ashenfelter , heavyweight of the economics profession, is the man who dared to defy Parker. He publishes a newsletter entitled Liquid Assets. For Ashenfelter, finding a good bottle of wine is as easy as an econometrics equation that basically says:

Wine quality = 12.145 + 0.00117*winter rainfall + 0.0614*average growing season temperature – 0.00386*harvest rainfall.

Mind-boggling, isn't it! According to Ashenfelter weather statistics are enough to predict the quality of any vintage. Needless to say that the exchanges between the two experts have been rather harsh: Nose against data, palate against computer.

Ashenfelter decried what he perceived to be a sense of elitism in the wine industry. He says:

“A more fundamental question arises about the motives of the early purchasers of the wines. Why have they ignored the evidence that the weather during a grape growing season is a fundamental and easily measured determinant of the quality of the mature wines? And will they continue to do so as the evidence for the predictability of the quality of new vintages accumulates.”

Robert Parker called the professor's methods "Neanderthal," "ludicrous and absurd". He once said that Ashenfelter was like “a movie critic who never goes to see the movie but tells you how good it is based on the actors and the director.” So, should you swish and spit or should you data crunch to know the future of your vintage?

The 1989 Bordeaux deeply divided the two men. Ashenfelter predicted it would be the wine of the century. Parker could not disagree more. A year after Ashenfelter predicted that the 1990 Bordeaux would be even better. Parker disagreed again. The verdict was given by wine auctions. The 89s sold for more than twice the price of Parker cherished 86s. The 90s sold for even higher prices! Crunched weather data outperformed Parker's nose and palate.

A third man has recently invited himself to the debate. Tristan Fletcher, an Artificial Intelligence researcher at University College London and co-founder of Invinio, brings support to Ashenfelter's faith in the data. He is too convinced that machines can understand the value of fine wines better than any human. He even thinks that machine learning techniques can do better than Ashenfelter's regression techniques. His preliminary results published in The Journal of Wine Economics seem to suggest that his techniques are indeed able to improve the accuracy of vintage predictions. I am sure that we will soon see other data scientists turned wine lovers promoting alternative algorithms to crunch wine data. These algorithms will be applied not only to wine but also to art, to collectibles, to any items that can be quantified one way or the other. This is not necessarily bad news. A French proverb says that when one loves one does not count. In that case one does love and one does count! One counts because it has value to know beyond Parker's nose and palate how vintages will fare in the future. In vino veritas and in data veritas!

Ashenfelter's seminal work shows how data and algorithms may leverage our nose and palate and improve our wine choices. It is very often used as an example of the merits of big data in daily life. Indeed, the very fact that wine veritas may be found in data provides evidence that data are precious, that algorithms are valuable. Businesses like Ashenfelter's or Fletcher's are born out of data. They do make money. These delightful examples should however alert us on the value we dissipate when we agree to give our personal data for free on the Internet. Yes we do get some services in return but I am not sure the value of this services matches that of our data. The data collection has reached a scale that most of us are unaware of. Personal data are no longer captured through our browsing of Internet only. Apps and sensors proliferate everywhere from our smartphones to our homes and cars. Digital vacuum cleaners silently siphon our data wherever we happen to be, whatever we happen to do, inside or outside. We have become data obedient. Swapping our data in exchange of the free use of search engines, e-mail services, calendars, applications of all sorts has become the rule to which we abide. No questions asked.

This “free against data” swap we are forced into is unfair. The data currency with which we pay is a strong currency but it trades as if it were a weak one. As Ethan Zuckerman reminds us,

“we’ve been taught that this is simply how the Internet works: If we open ourselves to ever-increasing surveillance—whether from corporations or governments—the tools and content we want will remain free of cost.”

It is unfair because nobody is willing to openly tell us how much our data are worth. The sheer size of advertising revenues is an indication of money at stake, but this is the tip of the iceberg. Nobody is willing to tell us the true price of data for fear that we may revise our opinion towards the free for data swap. University of Carolina Chapel Hill Professor Zeynep Tufekci recently made an interesting offer to Facebook founder, Mark Zuckerberg in a New York Times article entitled “Mark Zuckerberg, Let Me Pay for Facebook”. Facebook makes billions of dollars in advertising. In the second quarter of 2014, Facebook released the following quarterly numbers: 1.32 billion users, $ 2.91 billion revenue, $ 0.791 billion profit. This is a profit of about 20 cents per month per user. Tufekci suggests that she would be willing to pay 20 cents per month for the full privacy of her data1. She adds that these 20 cents could eventually subsidize Internet access in poorer countries. But guess what, this is not something that Facebook and the like want to hear. Why? Because our data are worth a lot more to them than their current ad (meagre) value per head. This is where opacity kicks in.

On top of being unfair, the swap is opaque as nobody is willing to openly tell us what uses beyond advertising will be made out of our data, by whom and for how long. Weather data can be used by a lot of different actors including wine investors and insurers. The same holds true for our personal data. They can be processed by banks, insurers, employers, schools, governments etc. and, of course, not only for advertising purposes. The monetization options of our personal data are numerous. We give all these options, known and unknown, for free. These options however are worth a lot of money. Each of us is indeed worth more than 20 cents per month and that's where it becomes scary. We are now short of our options.

Useful insights can be drawn from data. There is no doubt about that, but not at any cost. We shall not blindly consent to data despotism. Despotism might indeed be the right word. If big data delivers veritas, it is fair to ask whose veritas it is and for what purpose. In the US FTC (Federal Trade Commission) Chairwoman Edith Ramirez is wondering where big data is driving us. The FTC is in particular concerned with low-income communities and black people being discriminated against. Research by Latanya Sweeney from Harvard University shows that indeed “advertisements for arrest records were 25 percent more likely to show up on a search for a list of distinctively black names than white names.” The discriminatory bias identified in this study is only advertising related but it does raise serious issues. The problem may become worse when discrimination will affect healthcare access, insurance provision, job selection etc.

Internet used to be synonymous of greater transparency, shortening of distances and easy access to a wide choice of content. There is a significant risk that what we believed in was just the model apartment! The Internet is on data steroids. Massive virtual warehouses accommodate the steady stream of information worldwide. Data are no longer stored on our devices: they are saved in the so-called cloud. This cloud is sold to us as a personal digital attic where we can easily store and access our data. But we have to realize that this attic unlike our attic at home is not ours. Its content is no longer ours either. Ownership has been replaced more often than not by license agreements which we do not even read. We have become cargo cultists hoping that more and more bounty will freely fall from the cloud in exchange of our data. Eric Schmidt, Google's ex CEO, candidly summarizes the situation we are in : “We know where you are, We know where you’ve been. We can more or less know what you’re thinking about.”

Scary is not it? What is even more scary is that the manager of a private company is proud of this dominance and praises it in public. These days the words of Estienne de la Boétie, a 16th century French intellectual and a dear friend of French author Montaigne, resonate rather strangely:

“It is indeed the nature of the populace, whose density is always greater in the cities, to be suspicious toward one who has their welfare at heart, and gullible toward one who fools them. Do not imagine that there is any bird more easily caught by decoy, nor any fish sooner fixed on the hook by wormy bait, than all these poor fools neatly tricked into servitude by the slightest feather passed, so to speak, before their mouths.”

Estienne de La Boétie wrote this warning in 1576. His book is titled “The Discourse of Voluntary Servitude”!

Unfairness and opacity rule the Internet game: the
depth of gathered personal data and the sheer scale of their uses remain inaccessible to the ordinary person. We fool ourselves in believing that we are fishermen navigating the digital ocean but the odds are high that we have become the baits.

Free has become awfully expensive.

The “free for your data” Faustian swap is odious.

The Digital Gilded Age: Amilcar's Nightmare; On Jobs, Robots and Perspiration

In 1924 fascist leader Benito Mussolini won the Italian general elections for the first time. Just like many of their compatriots Italian couple Carlo and Giovanna Zannoni flew their country to escape the new horrendous regime. They settled in Moutiers, a mining town in French Lorraine. Thanks to its coal and iron ore mines Lorraine attracted workers from all over Europe. Carlo spent the rest of his life as an iron ore mineworker. In 1945 he was joined by his son Amilcar. Amilcar worked 14 years in the mine to finally discover the passion of his life, iron sculpture. He became a famous artist and made a living out of his talent. His work was deeply influenced by his experience in the depths of the Earth. One sculpture in particular fascinates me. It is titled "The Man Nibbled by the Machine." This is an astounding piece in which a man is devoured by a complex machinery. No flesh is left on his right leg. His left chest is wide open. So is the left part of his head. The heart, the left lung, the left brain have disappeared. They have been replaced by gears, spinning wheels, crossed axes etc... The man's body and brain are eaten by the machine. Amilcar's sculpture (which predates Terminator!) is a truly powerful metaphor: the vanishing flesh and organs suggest that man is losing his race against the machines. The nibbled body conveys a grim view of the future of man at work.

The fear of machines is of course not new. Man has always had a complex relationship to machines. He invents them to be more productive. At the same time though machines destroy jobs. The same question is asked again and gain: Are new jobs created faster and in greater numbers than suppressed ones? From Leonardo da Vinci to Harvard University Schumpeter, from the Luddites to MIT Brynjolfsson and McAfee the same anguish is expressed. What is the future of man in a world where machines do the job? This anguish is stronger than ever today. Arms and legs are no longer alone at stake: as anticipated in Zannoni's sculpture, the brain is now the target of a new breed of machines powered by artificial intelligence. Machines have never been so tangent to man. More and more people worry that this time is different. They fear that the disruption brought by digital automation will not be compensated by long run benefits as it used to be the case in the past. This is what MIT economists Brynjolfsson and McAfee call the great decoupling. Indeed, over the last thirty years,

"Economic abundance, as exemplified by GDP and productivity, has remained on an upward trajectory, but the income and job prospects for typical workers have faltered."

In 2013, after adjusting for inflation, US workers were earning roughly 15% less than in 1973. During the same time period productivity doubled, and real estate prices, healthcare costs and education tuitions rose sharply.

The angst is predicated on the fact that digital technology contributes to the replacement of more types of human labor than ever before. Radiologists are for instance at risk of losing their jobs to image analysis algorithms. Any job that rely heavily on data is under siege as machines get better and better at handling massive amounts of data. To understand how we ended up there let us look at the previous episodes since the 18th century.

The first and second industrial revolutions from the late 18th century to the early 20th century marked a turning point. Machines blossomed everywhere: from the spinning jenny, the steam engine, the milling machine, the cotton gin, the blast furnace to the internal combustion engine new manufacturing processes were put in place. New sources of energy became available such as oil and electricity. Hand production methods were replaced by machines that took over the dirty jobs. Mass production and assembly lines allowed growth to kick in and, despite the revolts of Luddites and the like, transformed agrarian societies into industrial ones. Even though the social conditions were more often than not terrible more jobs were created than lost, jobs that did not exist before. It is however fair to say that the newly minted jobs became awfully dull. Henry Ford could not be more explicit when he said:

"Why is it every time I ask for a pair of hands, they come with a brain attached?"

In the movie Modern Times Little Tramp, the character that made Charlie Chaplin famous, struggles to keep up with the infernal pace of the assembly line but finally suffers from a nervous breakdown. Thanks to machines perspiration did decrease but at the cost of pathetic and unhealthy dullness.

In the 20th century automated machines were deployed to take over dull jobs. The progress made by robotics, a branch of mechanical engineering, electrical engineering and computer science, contributed to the development of machines than can operate autonomously. In 1961, the first industrial robot, the Unimate, was installed in an American factory. Robots are now everywhere to be seen in assembly lines. They are faster and more accurate than human beings. For instance in automobile factories robots can execute fifty to hundred welding spots per second. Tesla's assembly line in Fremont, California is powered by close to 200 robots. Moreover robots do not perspire. They can work long hours without having to take a coffee break or a nap. Robotic automation helped increase productivity and wealth per capita. The wave lifted (almost) all boats and gave birth to the middle class.

The 21st century does not seem to hold the same promises. Its first years have been calamitous to say the least. Observers and commentators start wondering whether Nobel Prize Wassily Leontief was not right when he predicted that

"The role of humans as the most important factor of production is bound to diminish in the same way that the role of horses in agricultural production was first diminished and then eliminated by the introduction of tractors."

Now that dirty, dangerous and dull jobs have been swallowed by machines and robots, the technologists' ambition is to conquer the brain. The goal is to disseminate androids that can not only walk but also think and make decisions. It is an old dream of course. Jacques Vaucanson, a French inventor born in Grenoble in 1709, cherished the hope of an artificial man. He built famous androids that could play the flute and the tambourine. They played the instruments so well that Vaucanson's inventions were welcomed either with fear or skepticism. Vaucanson could not pursue his ventures. He was asked by the authorities to work on the turnaround of the French ailing silk industry.

Vaucanson's dream is well and alive though. Google Director of Engineering Ray Kurzweil is crystal clear about his goal, and he is sure that it will be reached:

"I have been consistent in predicting that AIs will match human intelligence in all of the ways in which humans are now superior by 2029. They will then be able to apply their enormous speed and scale and total recall to all of human knowledge. I believe that recent advances should give us a lot of confidence that we will meet or beat that goal."

Because of the exponential factors at work (computing power, storage, speed, Kurzweil's law of accelerating returns etc...) there is no doubt according to Kurzweil that we will be able to reverse engineer the brain and hack its algorithmic component, in other words its mind part1. We will not only replicate the brain/mind but outperform it. We will replicate it thanks to the advances in artificial intelligence. The algorithmic part of the brain will be made downloadable. No flesh allowed! We will outperform the brain/mind because computers and algorithms do not forget. They can store far more data than an individual brain can. They do not make mistakes. They are unbiased and above all they will be able to share information via the cloud, a sort of powerful collective algorithmic mind. Kurzweil is convinced that we will then reach a singularity point, a point in time when there will be no difference between man and machine. Our intelligence will have become nonbiological as if Amilcar Zannoni's worst nightmare of a man nibbled by machines had come true. If one follows Kurzweil's trans-humanistic argument it is not jobs that will disappear but man as we know it. According to Kurzweil's friend and MIT Professor Marvin Minsky there is not much to worry about since after all the brain is "a meat machine" and the body "a bloody mess of organic matter." The bad news is that we will not have any jobs anymore but the good news is that we will not care as we will be something or someone else!

In a sense we have come full circle. Henry Ford wanted a body only, no brain attached. Ray Kurzweil wants the opposite : mind only, no body (and brain) attached! While both perspectives look scary, their simplistic views of man complexity is rather good news. Indeed, we do intuitively feel that a body without a brain and a mind does not make much sense. A brain and a mind without a body does not make much sense either. This split view of mind, brain and body is what University of Southern California Professor of Neurobiology Antonio R. Damasio calls Descartes' Error. Descartes, a 17th century French philosopher, wrote the famous statement "Cogito ergo sum." It says it all: to be one (only) needs to think. Descartes posited the dualism between the mind and the body. In other words the body is not of great value, and although not made of matter the mind is what matters. Kurzweil would wholeheartedly approve. Damasio agrees to disagree. Body, brain and mind cannot be considered separately. For instance, when a threatening dog barks at us, our pulse quickens, our blood pressure rises, and adrenaline is released. The complex reactions the body triggers in response to the barking dog are called emotions in neurobiology. Then comes the expression of feelings as our brain notices the changes in our body conditions. Following the emotions in front of the barking dog we experience the feeling of fear, a mental outcome. Feelings (at the brain level) are formed by emotions (at the body level). Damasio summarizes it eloquently: "Mental activity, from its simplest aspects to its most sublime, requires both brain and body proper." These body/brain/mind processes have been shaped and perfected by millions of years of evolution. Mother Nature is indeed a great tinkerer. She takes the time, makes mistakes and does not set up any target date to reach goals that, by the way, she does not have in the first place, a behavior that is the exact opposite of Kurzweil's. Kurzweil has a goal, a target date (he loves making predictions) and one huge bet on artificial intelligence. Mother Nature places multiple bets without having any specific goal (she plays the unknown instead of the known). This is what makes her so good at what she does. Kurzweil and the like piggyback on the known (at least what they think they know), and reduce it to a computer power problem. The rest, the unknown is just something that has not been computed yet but will sooner or later be. Brute force instead of soft serendipity! They forget that all what is computed and computable does not necessarily matter, and, above all, that all what matters does not always have to be computed. They overlook the pervasiveness of randomness, and how nature (including man) has dealt with it. This is a rich fabric of mistakes, trial, errors and of course successes in the great Augustinian tradition: "Si enim fallor sum". All humans, taken together as they are, flesh, brain and bones, are worth a lot more than any central cloud made of our supposedly perspiration-proof downloaded minds. To put in very simple terms, I perspire therefore I am! To put it in Hungarian philosopher Michael Polanyi's words:

"We can know more than we can tell... The skill of a driver cannot be replaced by a thorough schooling in the theory of the motorcar; the knowledge I have of my own body differs altogether from the knowledge of its physiology; and the rules of rhyming and prosody do not tell me what a poem told me."

Good luck Mr Robot!

Indeed, robots do not perspire, nor do they consume by the way. This is their weakness. This is a great piece of news. Not so long ago perspiration is what used to make our jobs fragile: inspired in California, perspired in China! Perspiration combined with inspiration is what may save our jobs in the so-called race against the robots. But if we take it as a race, we will lose and Kurzweil may have it right. The terms of the race as they are currently spelled are indeed not in our favor. The race is not inevitable however. As French writer Georges Bernanos once wrote

"the danger does not lie in the machines, if it did we would be pushed into this silly dream of having to destroy them... The danger does not lie in the multiplication of machines either. It is in the growing number of men who, since they were born, are only used to what machines can deliver."

This is indeed a danger especially if we leave the machines and the robots in the wrong hands who happen to capture the bulk of productivity gains, and all the optionality (big) data give access to. Moreover we shall not forget that a whole generation has only known and used the Internet by swapping its strong currency, its data, against the weakest one can find, free! This would not really matter if digital capitalism were not a winner-take-all game. It is more than ever shaped by the rent seeking behaviors of robber robot lords. For instance, it is no accident that Google heavily invests in robotics. Robots need to be trained to be efficient at what they are supposed to do. The training takes place through data. It takes for example zillions of images to improve a robot's vision. These data do not come out of the blue. They come from us via the Faustian "free against data" swap. We are even kind enough to tag the data and upload them to the cloud. Life has never been easier for the robber robot lords!

It does not have to be so though. Digital capital is abundant. It has low marginal costs. Digital capital being more and more used in production it stands to reason that capital owners should see their returns decrease, unless of course they seek to capture rent positions and we let them do so. The race is not a race against the robots. It is a race against the robber robot lords, against the new Carnegie, Vanderbilt and the like. In his book Antifragile, Nassim Taleb praises Prometheus and mocks Epimetheus. According to Taleb, Prometheus who stole the fire from the gods is antifragile, long disorder. Prometheus enjoys upside while having no downside. The more disorder there is, the better his position becomes. Epimetheus who accepted Pandora's jar is short disorder. Only bad things can happen, and did happen after he opened the jar. I fear that we are more Epimetheus than Prometheus. Indeed, the jar we have been offered is in all senses of the word (especially in the Internet sense) a cookie jar. We have accepted it without knowing what uses would be made out of our data. The robber robot lords have stolen the fire of our data, namely the many valuable options these data carry that can and will be monetized. We have opened the jar, and, as things stand, we have no way of knowing what the robber robot lords (will) do with our data. Again, this issue is no longer a minor one: it concerns billions of people on Earth whose data are siphoned by the robber robot lords.

It is time to throw the cookie jar away and regain the control of our strong (data) currency. I do not think that robots are our best enemies for we do not for instance regret having machines do the job in mines instead of children. By the same token I do not think we should regret having robots do the hazardous, dirty, dull and time intensive jobs, be they blue collar or white collar. Automation frees up time. It liberates our mind/brain/body (which is far more than an algorithm) so that we can "perinspire" on important issues. If the decoupling between economic growth and job creation is confirmed, we cannot satisfy ourselves of Brynjolfsson and McAfee's simplistic dirty secret of economics:

"technology progress does grow the economy and create wealth, but there is no economic law that says everyone will benefit."

The key issue is not that there is a decoupling. The key issue is to whom this decoupling benefits. Sadly enough, Brynjolfsson and McAfee are right, economics has become a truly dismal science of growth full of dirty secrets. It has not always been the case though. Economics used to be called political economy. The great minds behind it were concerned with the distribution of wealth, and not so much about its maximization. That is what mattered to them, how humans can live and strive in a balanced society. They knew for a fact that, even if it helps, a growing cake is not a remedy to inequalities, especially when the cake is cooked in a winner-take-all kitchen. They kept a close eye on the distribution of wealth for they knew that an unequal and unbalanced society is unsustainable. Today's society is at risk of growing inequalities. It may become more unequal in a digital gilded age that is predicated on increasing returns to scale and winner-take-all effects. It is unbalanced and may become more unbalanced in a digital gilded age during which we entered, on an unprecedented scale, into Faustian "free against data" swaps with robber robot lords. Data are the gems of the digital gilded age, and there is no economics dirty secret saying these gems should go for free and benefit the predatory few while being stolen from the gullible many. We are not e-monkeys: we do not accept e-peanuts!

Again the race is not against the machines and the robots. The race is against those who own them to avoid that they end up owning us.

The race is about the (re)distribution of wealth in what we hope will be a sustainable digital gilded age.