As a further chapter in my occasional highlight of serendipitous discoveries, teams of scientists from the UK and the U.S. discovered and evolved in Japan an enzyme that can degrade plastic by assisting a bacterium with digesting PET plastics. Ongoing further research promises to put a relatively cheap end to worldwide plastic pollution by recycling it sustainably. As it stands today, PET plastics can survive hundreds of years in the environment and have turned into an increasingly serious and mushrooming burden to major countries and large oceanic regions. Researchers from the University of Portsmouth, UK and the Renewable Energy Laboratory at the U.S. Department of Energy have now discovered, and published in PNAS, a potential solution to this blight by studying and tuning the structure of a natural enzyme that developed on its own in a Japanese waste recycling center. Initial research found that the PETase enzyme assists a bacterium, Ideonella sakaiensis 201-F6, with breaking down or digesting PET plastics. The enzyme structure was then optimized by bioengineering by adding some amino acids. This optimization process resulted in random changes to PETase’s activities and ultimately indeed an altered enzyme that turned out to be significantly more effective than its natural form. The same team now continues to explore the enzyme further to see if PET plastics can be degraded on an industrial scale, and if so, with what side effects. It is entirely possible, indeed likely, that the next few years will yield industrially viable processes to disassemble PET and possibly other plastics back into their original organic building blocks to set in motion a sustainable chain of recycling. Independent scientists not directly involved in this research consider this biodegradability approach clearly promising despite the obvious concerns that the development of the enzyme as possible solution against pollution is still at too early a stage to render a meaningful assessment possible. And that may well be true, but it is also secondary: enzymes are non-toxic, biodegradable and capable of being produced in large quantities by microorganisms, and there is great potential for using enzyme technology to solve society's growing waste and landfill problem by degrading at least some of today’s most commonly used plastics. Even as it may still be necessary to await further developments intended to improve the enzyme, this discovery brings sustainable recycling of plastics within striking distance.
A new study suggests that increased trade with China had more dramatic impact in the U.S. than previously thought. While economists across the board continue to consider unilateral tariffs the wrong approach, U.S. public discourse about the trade conflict between the U.S. and China has turned to more subtle aspects of the pros and cons of globalization. The central question remains: How can people be compensated who lost job and perspective because of free trade? Economists who normally write only for an expert audience turn into permanent guests in the media. Most of them reject an isolationist strategy. Their argument goes like this: if we look at development over time, it was not free trade but automation that has caused the sharp drop of number of U.S. industrial workers. Besides, and despite dramatic warnings from select industries, the problem is far less serious than the political debate suggests: U.S. unemployment at 4.1 percent is much lower than widely accepted – in fact, it is extremely low.
And even if there are job retention problems, tariffs will not relieve them. But there are shades of gray in the debate: Kerwin Charles, Erik Hurst and Mariel Schwartz, all from the University of Chicago, have been part of a recently published research paper making an interesting objection to the debate. Although the authors do not favor isolationists policies, their arguments suggest that a serious consideration of the pros and cons of a liberal trade policy is more complex than it appears at first sight. Competitive pressure from China is indeed a factor – potentially the key factor – in the loss of U.S. manufacturing jobs. But this happens through a mechanism not as simple as mere wage differentials. In their paper Transformation of Manufacturing and the Decline in US Employment, Charles, Hurst and Schwartz show just how dramatic the decline of U.S. industry had been. Since 2010, 5.5 million net jobs were lost. One third of all manufacturing jobs disappeared. Like other research, Charles and his colleagues show that job losses were heavier in industries where Chinese competition had particularly increased. However, the China factor explains only about a third of job losses. A bigger part was played by the increased level of automation. Machines play a far more important role in processes today than they did 20 years ago, and owing to technology, U.S. industry produces far more with less than it did 20 years ago.
At first glance, this argument seems to prove right those who say that the development was not caused by trade but by automation. But Charles, Hurst and Schwartz take their analysis one step further: they show that the degree of automation rose more sharply in those industries that had come under competitive pressure from China.
Therefore, free trade appears to accelerate automation, because it increases competitive pressure. Automation and free trade are perceived by many economists as two different developments that only happen at the same time. But these results of Charles, Hurst and Schwartz suggest a strong connection: wherever lower-cost producers show up, U.S. employers are forced (or, rather, strongly incentivized) to replace humans with machines. Thus, negative consequences of trade would be stronger than expected. Peter Navarro, Director of Trade and Industrial Policy, argues similarly: if technology alone would explain elimination of jobs, there could not be many more manufacturing workers on a per-capita basis in Germany and Japan than there are in the U.S. – but there are.
Other economists have held that protectionism accelerates automation. This is not an either-or conundrum: let’s just agree that technology accelerates automation – because it’s there, because it improves quality and reduces cost and thus creates competitive advantage, and because machines don’t strike and don’t talk back. Contrary to human workers, they also become cheaper to buy with time. A world without work, for many or most?
Economic theory held for a long time that countries always benefit from free trade because the exchange of goods and services allows them to specialize. If everyone produces what he does well, everyone wins. So long as prosperity increases overall, people who lose their job as a result of globalized free trade can get employment elsewhere. Industrial workers simply become IT specialists. This has been the standard model for some decades, but recent research shows that this is precisely what did not happen: many former steel workers in the Midwest, for example, do not get other jobs in emerging industries for which they could be retrained in theory, but they instead remain unemployed.
The Chicago study now shows the dramatic effects this has had. For example, substance abuse rose most sharply in recent years where industrial job losses were heaviest. They prove this by numbers showing prescriptions of painkillers by doctors and by the development of drug deaths. Substance abuse is today the leading cause of death among Americans less than 50 years old. The U.S. experiences the worst drug crisis in history. Addicts typically do not look for employment – and so they drop out of statistics.
When economists talk about pros and cons of trade, they typically do not include the cost of a drug pandemic in their tally. But regardless of accounting estimates, tariffs will not bring lost jobs back. They may improve U.S. steel output manufactured by robots, yes, but this only benefits the shareholders of steel mills – it does not restore jobs for human workers.
Negative cost of trade is difficult to measure. But that also applies to its benefits. Nobody can say exactly what kind of economic utility results from universal access to ownership of cheap iPhones and Galaxies from China - in many ways, gadgets are just gimmicks. Besides, the real and thus far underestimated danger lay in the fallout from progressive escalation of trade conflicts: China and others respond to U.S. steel tariffs with countermeasures, which the White House considers excessive, and in response to that, economic advisors recommend additional punitive measures.
Now, if one shifts focus from China to Schumpeter’s creative destruction by entrepreneurial technology, one can take the Chicago study to its logical consequence for policy purposes: universal basic income (UBI), an idea supported by some household names in technology like Elon Musk, Ray Kurzweil, Sam Altman, but also Mark Zuckerberg and Richard Branson, although the idea dates back to Milton Friedman (negative income tax), Bertrand Russell, Thomas Paine, Sir Thomas Moore and Pericles. I plan to write about its pros and cons one of these days, as the idea gains attention again after two or three millennia of being kicked around by some prominent thinkers.
More and more German companies rely on artificial intelligence when it comes to personnel selection. Insurer Talanx has stated that it conducts executive search with software that creates within minutes extensive personality analyses of applicants based on language tests. According to Talanx, the software produces a 90 percent approximation of the results obtained by psychologists after days of work at assessment centers. Talanx relegates assessment to an algorithm for good reason: a large part of its management will retire by 2025. Other companies using the same software, Precire, include Frankfurt Airport’s operator Fraport and Ranstadt HR agency. The algorithm test of Precire was created by an Aachen startup of the same name. The developer currently works on integrating a medical speech analysis program for early detection of depression. To date, Precire is able to reveal first signs of depression at a very early stage.
Artificial intelligence development is considered a multi-billion-dollar market in Europe, and the situation in the U.S. is very similar. AI technologies could soon make impact on other sectors, but platforms such as Precire are both highly promising and alarming at the same time, as cheap and increasingly accurate technology is bound to spread quickly.
Alas, practical concerns reach far beyond EU’s GDPR: who will ensure that this easily recorded deep psychological language analysis will be used only with valid consent and for certain purposes but not for others, and not by potential anonymous actors? More immediately, who will incur the risk of hiring an individual with symptoms, or even likelihood of future onset of depression? What else besides depression will be revealed by additional modules and additions to such a platform? What are the consequences for Fourth and Fifth Amendment rights? Do individuals retain a reasonable expectation of any privacy if physical characteristics such as voice and images are increasingly available from plenty of uncontrollable recordings, such as millions of CCTV cameras, public and private webcams, and voice-operated AI systems? Will banks start to rely for credit decisions also on customer profiles based on voice commands given to automated navigation systems? How about individuals considering relationships with new acquaintances? Has anyone ever seen a genie retreat into its bottle?
Multiple elections in Western countries since 2016 were about “the forgotten men and women,” the losers of globalization and victims of automation. It is safe to say that their numbers are bound to grow while neo-Luddite resistance may destabilize purportedly open societies from inside more than migration has to date. As the potential for abuse by further dilution of traditional concepts such as “informed consent” and “reasonable expectation of privacy” proliferates, will resistance to technology, even at great sacrifices of convenience and price, remain even theoretically possible?
In practical terms, time is linear. And it passes. Because it has alternative uses, different ways of spending, it is capable of analysis under the concept of opportunity costs. It can also be related to human life and psychology as a yardstick, by determining its value in terms of one’s willingness to wait. Especially under risk and ambiguity.
While time passes, it is in itself without alternative. If we “save” it, this sounds as if we could deposit it on a “time account” – but it is never the same time we “save” and “spend.” There is no guarantee that what we save today will still be there tomorrow. Or at all. Much of our sense of time relies on the assumption that we will still be there – tomorrow or in a year or five.
The sociology of time is another dimension. In all likelihood, Neanderthals did not separate work and leisure, thus had no schedule for collecting berries or hunting mammoths, and therefore time was not managed, but its use was based on current needs as part of a persistent struggle for survival. Competing uses of time, and its partition and separation for different uses is a much more recent phenomenon. Already circa 29 BCE, though hardly for the first time, Virgil’s observation appears: sed fugit interea, fugit inreparabile tempus. There had been countless similar admonitions against sloth and procrastination, in the aphorisms of Hippocrates, come to fame latinized as ars longa, vita brevis, Horace’s carpe diem and Plato’s Phaedo’s (64a4) adoption by Tertullian (Apologeticus XXXIII) as the Christian memento mori, its relative conceptual novelty was likely due to literacy more than it was to newly broken ground. But, yes, suddenly, time management became an individual as well as a social necessity, at the latest during the transition from the medieval to the modern era that brought about development of watch technology to measure passage of time, thus made its role and observation independent of natural time. It was the foundation of the industrial revolution, of its separation of labor and specialization. Now, coordinated contributions by distinct and separate individuals became synchronized and regulated with regard to time – the “deadline” in all its pervasive forms was born, though it had to have been in existence far earlier. At the same time, religious reforms brought on by Calvinism translated the material rewards of increased efficiency into signs of divine favor and created theological underpinnings for the values of modern capitalism. Because of this nexus (and its multitude of implications), higher material standard of living seems to correlate, at least empirically, with increased scarcity of time. Since time was managed, mankind transitioned from subsistence economics into a standard of wealth economics.
There is no evidence, however, of an inevitable nexus between evanescence of leisure and affluence. Though it may seem that time pressure is the price we pay for growth and prosperity. But this is a fallacy: while the time resources of poor people may be valued less, poverty engenders more pressing shortages of time than affluence, not least because the forms they bring about are more inescapable.
Time shortage under affluence has different causes: l’embarras du choix. The stress of too many options, too much choice, too much diversity. The risk of a “wrong” – or, almost as dissatisfying – a “suboptimal” choice in terms of ratings, rankings or other externally imposed preferences is much greater than in earlier, simpler times with fewer choices. At the same time, social media create pressure by showing us all the exciting things other people are doing right now and that we appear to be missing out on. The need to make reviewable comparisons, decisions and choices constantly creates dissatisfaction of another kind than need.
Time is a resource and its valuation just as important as that of any other – perhaps more so. Time is not money, but it can have monetary value, beyond mathematical trivia. To have time has become a status symbol. “Important people have time.” They are in a position to delegate secondary choices and lower priorities which in turn frees up their available time resources. As a result, the most successful person is not the one that spends the longest hours at the office but the one with a work-life balance that wraps up his or her agenda in time for golf, social, charitable or artistic engagements. Or even for sleep and rest. It may be a 21st century standard of success to show sufficiency of time, this scarcest of resources of the hoi polloi. Yet, at the same time, to some and indeed many, the times when being richer meant working less are so yesterday.
Let’s not delude ourselves – wide swaths of mathematics have been regulated at least in their applied incarnations. At least since cryptography, a branch of number theory, has come to be considered an “armament” requiring an export license.
But as “weapons of math destruction” have become commonplace and algorithms that rule our working lives and consumer existence are used for anything and everything from predictive advertising to policing to a virtually unlimited number of other uses that include the internet of things as much as smart agreements and the internet of contracts, it became increasingly obvious that delegation of the outcome of machine analysis, evaluation, learning and assessment would require regulation. Cathy O’Neil, the “mathbabe” with a comet-tail long track record in finance, has been arguing for considerable time that algorithmic notations project the past onto the future (so the best we can hope for is to perpetuate the past) and are thus rife with bias: they serve as a means of social control through pernicious feedback loops, such as value-added models penalizing seemingly excellent educators, perpetuating racial, class-based and other discrimination in “predictive policing,” political polling, prison sentencing, car insurance premiums, or employment tests.
When Lufthansa, following the bankruptcy of Air Berlin, substantially and unjustifiably hiked its airfares (to no one’s surprise, because a serious low-cost competitor had just vanished) and was chided by the German Federal Cartel Office, it created the “algorithmic defense”: no human was to blame, it was all “the algorithm’s fault.” To which federal regulators remarked that algorithms were not written by God in heaven. We can be sure to see algorithmic defenses spring up all over the place, almost at the speed of light.
In this context, O’Neil postulates a “Hippocratic oath” of modeling and data science: first, do no harm. That would require that mathematical models be purged of characteristics that allow them to serve as proxies for race and class and start responding to ethical responsibilities – which are tricky because there are different stakeholders. Thus, meaningful regulation in a meta way requires auditing algorithms – which, in reality, would mean to create and continually improve algorithms that audit algorithms. That is because mathematics is inherently “trusted” but, because of its undisclosed assumptions and model correlations in most algorithms, is anything but trustworthy: its formulae are secret, and, although they almost operate like laws in some instances, their disclosure is currently mandated by no law, not even by the Freedom of Information Act, and has proved difficult to enforce by civil litigants. Furthermore, the constitutionality of potential outcomes dictated by algorithmic output is reviewed by no one. For example, we have fair hiring laws – just that those are not applied to Big Data algorithms, and there are no signs of an emerging nationwide conversation about it, just as there is not about so much of data science.
In the face of increasingly overwhelming evidence that the very analogy-based and precedent-oriented genesis of AI does, in fact, “learn” from models that carry prejudicial patterns on race, class and gender (surely among others), indicating “group membership” or value allegiances of algorithms and robots steered by them may become the next frontier of disclosure – perhaps through brand names, though it will likely require greater and deeper efforts. But mere disclosure of potential or predictable biases reinforced by autonomous learning may not be enough in the absence of proactive and affirmative eradication tools. Which raises another bizarre specter: the infiltration of AI by algorithms to secure political correctness. So long as algorithms are written by humans, draw value data input from humans and perform for a human target audience, it will be difficult to see how phenomena that have existed in human valuation, rating and triage processes could fail to leave mirroring marks on mathematical models ultimately traced back to them.
Chinese-American nanoscience made a Great Leap Forward through the collaborative effort of the National Center for Nanoscience and Technology (NCNST) in Beijing and Arizona State University’s Biodesign Institute's Center for Molecular Design and Biomimetics: in a first in vivo murine study, autonomous nanorobots proved to be intelligent delivery vehicles capable of causing complete cancer regression within a few days. DNA nanorobots employed one of the new drug delivery methods (which have always been a fundamental strength of nanotechnology) with thrombin-loaded DNA programmed to respond to a molecular trigger to fold into itself like an origami sheet and subsequently, like a tiny machine, deploy thrombin at the targeted point. By injecting tumor-associated blood vessels with thrombin that cut off tumor blood supply within 24 hours, nanorobots caused tumor cell shrinkage and necrosis. Most notably, clotting did not occur in healthy tissues other than those programmed for targeting. Significantly, in a control study of side effects in porcines, healthy tissues also remained unaffected. Once fully tested and developed for human use, the technology will obviate the need for most chemotherapy models as well as use of targeted drugs, because elimination of blood supply limited to tumor cells yields far more precise results.
Now for the real hurdle: overcoming opposition to approval for human use by vested interests in the multi-billion chemotherapy and radiation therapy industry. Luckily, and quite significantly, this technology did not originate in Lobbyland, and following very recent reforms of the Chinese drug and device approval process, chances are that Chinese approvals of nanorobot therapy will be way faster, securing East Asia’s foothold in the future of cancer therapy. That would, of course, happen not a moment too soon, given the explosion of cancer rates in China, largely due to severe carcinogenic environmental pollution in heavily industrialized parts of the country that already experiences a wide array of consequences of limited effectiveness of environmental regulation, held back in favor of rapid and profitable industrialization. But the interesting observation is that forum shopping to defeat inefficient bureaucracies is gaining ground in science and technology and with startup environments, just as it did in litigation, taxation, treaty shopping and multiple other areas: market players vote with their feet on the quality, efficiency and stimulation effects of regulation, and pass value judgment on its overall utility.
Philippe Legrain is one of the most attractive independent thinkers at LSE – one might label him a contrarian with at least some good cause – in the populist universe that gave us Brexit. What I find most amusing is that his almost trivial economics lends to leave opponents with next to no plausible logic to contradict him. His recent scholarship precipitated richly on the obvious: why immigration boosts the GDP. It is only in an era of mass stultification through grotesquely emotionalized nationalist arguments pitching to a base blissfully unaware of the lessons of history and without comprehensible basis in economic fact, that this would support a “controversial” intellectual agenda over the years as it has in Legrain’s case while he argued for a “European Spring.”
Now, it is hardly a revolutionary idea that doing the right thing from a humanitarian perspective turns out yielding dividends and is actually good business. What is a welcome change, however, is to voice such substantiated Merkelism at a time of Realpolitik when the pendulum of irrational fears and anger swings in the opposite direction in so many places.
Now, it is hardly a revolutionary idea that doing the right thing from a humanitarian perspective turns out yielding dividends and is actually good business. What is a welcome change, however, is to voice such substantiated Merkelism at a time of Realpolitik when the pendulum of irrational fears and anger swings in the opposite direction in so many places.
In Refugees Work: A Humanitarian Investment That Yields Economic Dividends, a paper that appears to be the first comprehensive international study of its kind, Legrain shows how refugees contribute to advanced economies, and found that they double the host society’s investment in them over a period of just five years. Would that the same could be said about each dollar invested in aging natives. Refugees contribute economically as workers of all skill levels, entrepreneurs, innovators, taxpayers, consumers and investors. The “diversity dividend” is, in fact, remarkable: more than three in four patents filed in 2011 at the top-ten patent-generating U.S. universities were attributed to at least one foreign-born inventor, while in Britain, migrants were found to be almost twice as likely to start a business as are locals. The most entrepreneurial migrants in Australia are refugees. One-third of recent refugees in Sweden are college graduates while two-thirds of those have skills that match current graduate job vacancies.
While it would certainly appear that Legrain falls victim to his own propaganda and pitches his findings as actual solutions, without applying the same strict scrutiny to the cost side of his cost-benefit analysis, there is no question that many if not all of the most successful synthetic societies in modern history leveraged economic contributions made by refugees: the United States, Australia, New Zealand, Canada, Israel, but also Germany and several South American nations come to mind. In turn, refusal to quickly integrate and invest in refugees has proved disastrous in the case of Arab Nations with regard to Palestinians, and across Africa with its numerous displacements in the wake of seismic political shifts. Although even prolific generators of refugees can end up beneficiaries: remittances from abroad to Liberia, for example, amount to 18.5% of its GDP. Some of Legrain’s findings are fallacious on their face, or, rather, reflect trivialities: so, for example, the “discovery” that recognition of foreign qualifications ought to be streamlined, since it costs only £25,000 to train a refugee doctor to practice in the U.K., while it costs over £250,000 to “mint” a new British physician. If only social engineering were that simple, and could afford to ignore blowback from professions and market segments facing competition from immigrants. Refugees are not, and cannot be, the sole priority and consideration in balancing social interests.
Among the interesting findings of Legrain’s study is that the U.S. is more successful than the EU at getting refugees to work: their greater initial investment results in a higher rate of employment than for people born in the U.S., with earnings rising sharply over time while reliance on social assistance declines rapidly. If, as is plausible, the first priority should be to get refugees to work early, then granting asylum seekers right to work while their claims are being reviewed, as is done in Canada or Sweden, but not in the U.S., is an act of simple pragmatism, not of principle. Legraine is right that policy ought to combine the active assistance of the Swedish model with the job and entrepreneurial opportunities in U.S. practice. Refugees ought to be resettled where there are jobs, not in areas where cheap housing is available but jobs aren’t, and the same is true of rigid labor markets privileging insiders at the expense of outsiders, not to mention stifling entrepreneurship. While government assistance for refugees ought to be generous, prompt and wide-ranging initially, open-ended welfare provisions not only create a moral hazard but also have, on balance, a negative impact. Serious analytic examination of economic benefits of diversity, initiated inter alia by Legrain, has far from ended and has barely begun to demonstrate its predictable wealth of results.
Thoughts about contrarian tipping points for conventional wisdom
Citior, altior, fortior - faster, higher, stronger. The venerable Olympic motto has left the sports arena and turned us all into valiant gladiators. It is a race we are inevitably bound to lose – against machines and cyborgs as much as against human mutants who undisputedly excel at quantitative criteria but have contributed precious little to the qualitative quantum leaps that made up the ultimate sum total of evolution.
At the same time, we are witnessing the unprecedented olympification of all areas of life. The day cannot be far when every aspect of our existence, everyone and everything with which we come in contact will be ‘rated.’ From credit ratings to U.S. News & World Report to Zagat’s, it is the equivalent of cameras in the courtroom: people start acting for the camera, and for the ranking, to the detriment of any other priority or independent substantive consideration. I am not saying it is all bad – witness body cameras for police, and think of transparency in public companies – but, once a tipping point is reached, it does create powerful opportunities for contrarian approaches: think leveraged buyouts and private equity, think investment in distressed assets, think off-balance-sheet items, think emphasizing criteria the jury didn’t. It is the very essence of market forces as opposed to Marxist planned economies to award rewards for what has not been planned for, what went unpredicted, and, hence, unrated.
I challenge you to name a dozen Wunderkinder, child or youthful prodigies who later won significant recognition or even just awards for lifetime achievement. There was Mozart, yes. Now, keep going!
It would just be willful blindness to overlook the evidence: our time is witnessing a spectacular rise in extremely successful college dropouts. In fact, the vast majority of billionaires falls into that category – whatever value one might wish to accord a high net worth, they must be doing something right. Think of Bill Gates, Steve Jobs, Larry Ellison, Frank Lloyd Wright, Buckminster Fuller, James Cameron, Mark Zuckerberg, Tom Hanks, Harrison Ford, Lady Gaga, Tiger Woods, Roman Abramovich, Ben Affleck, André Agassi, Christina Aguilera, Paul Allen, Woody Allen, Brooke Astor (AND her husband!). Why should I get carpal tunnel syndrome typing honorable mentions for the legions of those sore “underachievers” when you can read the “hall of shame” of college dropouts all by yourself?
The rest of us make up for the ever-growing pool of wannabe Olympians – measured by purely quantitative criteria, because these are so wonderfully indisputable. Yes, they are indisputable because they are also almost completely meaningless, and it is, after all, impossible to argue persuasively with nonsense. Our standardized tests relate to testing relevant aptitude much as the ability to jump 5 yards would be predictive for admission to a police academy: something just tells you that neither Sherlock Holmes nor Inspector Jacques Clouseau were capable of doing it – or needed to. But it is such a fair, objective, and, above all, non-discriminatory criterion! Who cares if Sherlock Holmes doesn’t make the cut-off: we know in our guts that, just like Jessica Fletcher, he will ultimately not need a police badge to solve the darndest cases. It gets a little trickier in licensed professions, though. What distorts these tests is that, because of the substantial numbers of test-takers, a good part will excel both at relevant and at (the painstakingly measured) irrelevant criteria. Of course, it is the former the test administrators and their clients will shamelessly claim credit for.
Standardized tests, the panacea of “selective institutions of higher learning,” have shunted deep and slow thinkers to the side to give way to those that excel at quick access to memorized data and to measurable standardized solutions. Were Galilei or Newton’s apple measurable? That’s not to say a lawyer or a doctor ought not be able to think quickly on her feet, but only very rarely does it matter. The other times, it matters mostly for quantitative productivity: that is to say, it indicates one’s ability to resolve déjà vu problems quickly and with minimal reflection. Speed is an entirely useless criterion in the quest for resolving novel, cutting-edge challenges. But then, junior-level professionals are not even expected to tinker with those, and by the time they reach a level where actual thinking may be not only permitted but required as part of their job description, they can be trusted to have learned all tricks of simulating creativity.
There is another consequence to standardized tests, and it has thoroughly corrupted higher education: no matter how cleverly they are designed, all standardized tests inevitably become “learnable.” While this gives rise to profitable cottage industries concerned with test-prepping, it once again skews test results in favor of those able to afford it. If only learning for the test would overlap with learning for life – but it doesn’t. There is, quite simply, no utility whatsoever in one’s ability to retain, for a few weeks at most, inordinate volumes of arcane SAT or GRE vocabulary otherwise ably provided by Merriam Webster. That, or speed-reading, is how we select who should be granted a license to grow their mind? Really?
And this is also exactly why financially quantifiable success based on qualitative innovation has since some time become the domain of the college dropout. The very same principle can be applied, mutatis mutandis, to professionals who, by implication of our licensing laws, cannot have dropped out of college but have faced a very similar dilemma at the level of graduate and professional schools.
Jobs that enable one to repay one’s educational loans within tolerable time and with tolerable lifestyle compromises are restricted to graduates of roughly a dozen professional schools nationwide in each area. That’s where employers of a certain caliber recruit – with a few notable but statistically not terribly significant exceptions. The rest cannot find jobs that will keep them out of quasi-poverty after debt service. How do we know how to identify these gatekeeper schools? Quite easily: they all come ranked, mostly by U.S. News & World Report (and a few others who base their raison d’être on not being U.S. News and offering some alternative but rarely more meaningful ranking criteria). Oh, ranking! What a genius business model, based on a delusionary distortion of the Olympic motto. The self-fulfilling prophecy of yet another substantively unsupportable racket.
It is also the reason why an unprecedented cult of youth has taken hold, ignoring the fact that excellence is not confined to the 18-28 age bracket. But combination of acceptable debt service and retirement savings is.
Once again, all these conclusions point us to a search for the road less traveled: because the beaten path holds very little promise, except an early death by hamster wheel.
If you add to that the fact that many employers of licensed junior professionals have concluded that professional schools have taught their entry-level arrivals few things of value, this, in essence, reduces their academic diplomas to an expensive (and meaningless) kind of intelligence test that comes with decades-long indebtedness. What follows this exercise is another decade of sorely needed professional training, this time under practical mentors who set real-world priorities, i.e., not “philosophy of…”, “doctrine of…”, “concept of….” but actual solutions that hold up to the tempest of practical challenges.
Well, one thoroughly fascinating alternative concept is the Thiel Fellowship. Whatever one may choose to think of the political and other meanderings of its founder, it is what only a contrarian can come up with. Not concerned with speed-reading, paper chases or other quantitatively measurable academic caprioles standardized tests are so fond of, it provides fellows with $100,000 in grant money for dropping out of college and pursuing real-life implementation of an idea judged worthy of the effort and sacrifice. Peter Thiel, one of the most creative entrepreneurs of recent years, a chess master, co-founder of PayPal and early funder of Facebook, will strike many as a living contradiction to his own ideas, since he is, after all, a graduate of Stanford (B.A. in Philosophy and a J.D. from the Stanford Law School). But I see no contradiction here at all – rather a need for vigorous generalization. Under Thiel’s approach, no ranking of the outcomes is necessary. The thing speaks for itself, in the language of Justice Potter Stewart: we know success when we see it. No need to make presumptuous ‘decisions’ whether robotics, biotech or the next BigData app are more important for the future of a generation about to be spawned. Let’s not forget, after all, what ranking has really become about: the nod of the ranker – and no other merit, whatever effort is made to cloak subjective outcomes in a costume of objectivity.
While a junior assistant or paper-pusher or suitcase-bearer might well be judged by his or her “efficiency” at menial practical tasks that lend themselves to quantitative scoring, that should not be applied if their employer had the development of significant potential of people on its agenda.
It took Einstein seven years to incubate Special Relativity and then ten years for General Relativity. It is fair to assume that no scientific funding organization would have supported this process patiently with grants (and, in fact, no one did – long-haired Albert worked at the patent office in Bern to support himself, passed over for ‘promotion’ twice “until he fully mastered machine technology”).
Yes. I know. Not every seven years spent brooding over a bizarre idea will result in anything even vaguely resembling greatness. Ask any PhD in Mathematics. In fact, the percentage of this happening will be lousier than the survival rates of start-up companies. It is equally true that there are few alternatives to such brooding other than a DARPA-like approach.
Part of the regulatory madness that makes taking companies private so attractive is the insanity of measuring strategic management performance by quarterly reports and prospectuses. A systemic prescription for failure and abuse? You bet. But one devilishly perplexing temptation is inherent in quantitative scoring that has even moderate acceptance: controversies and justified criticism aside, right or wrong, numbers will be relied upon for selection and allocation processes, only because they are so easy to use, and, more importantly, ‘because they are there.’
To force an individualized, qualitative, subjective look at the individual or decision in question would require considerably greater expense of time and depth of analysis and comparison. Besides, it would invariably give rise to challenges on grounds of fairness, comparability, discrimination and similar objections – simply because such obvious if irrelevant points of attack are inherent in any non-quantitative review. But do markets care what’s ‘fair’ or ‘objective’? Back to Sherlock Holmes, Jacques Clouseau, or Jessica Fletcher: res ipsa loquitur and nothing else.
Just like religions can be shown to have been molded to suit the interests of clerics and not of their respective flocks, the stark realities in higher education beg a similar question: are substance and processes designed at all to serve the interests not only of students but of prospective employers – whose overarching interest must obviously be a maximum of innovative, creative and productive staffers?
Take law school as a classical example: past a single year of common core, of elementary foundational classes, it matters not if there is any utility to class selection in the following years. On the contrary, giving maximum weight to speculative, theoretical and abstract classes is encouraged by faculty who argue that this is students’ ‘last opportunity to acquaint themselves with questions of a philosophical nature, not dictated by utility.’ A quick aside – does real life reward anything at all that does not rise to standards of utility? When did it? But it is, of course, so much easier to teach an abstract class of notions, concepts, and obscure yet controversial doctrines, than to present something that bears the almost objectionable aura of black-letter law. Employers have long given up on expecting graduates to have learned useful things in law school beyond the mere ability to think, and are entirely prepared to start what they consider meaningful education from zero once post-sheepskin reality settles in.
Today, most higher education is a compelling example of systemic failure, especially when one takes total cost to society of its irrational, inaccurate and inefficient selection mechanisms into account. At a national credit risk in excess of $1 trillion, student debt has become the next perfectly foreseeable financial albatross, just like S&L guarantees, the Dot Com bubble and subprime mortgages had been – long before evidence thereof was considered ‘reliable’ enough by special interests that favored the status quo. Each, an unforeseeable, unpredictable crisis? Permit me not to comment. What happened was, in fact, inevitable – only its exact occurrence remained somewhat uncertain.
A functional – although perhaps not formal – equivalent of the Thiel Fellowship will be of utmost importance for the future of professional education. Almost alone among civilized nations, the U.S. affords the incomprehensible luxury of requiring professional education to begin at the graduate rather than at the undergraduate level. It cannot be the purpose of tertiary education to make up for the sometimes indisputable weaknesses of secondary education by mandating an extremely costly four extra years rather than weeding out its victims by aggressively substantive admissions testing. How completing an arcane and often entirely unrelated undergraduate major makes for better lawyers may be an argument for another time and place. However, any meaningful incentive that causes effects similar to those encouraged by the Thiel Fellowship has to find very fertile ground. It would revolutionize professional education as we know it, by stripping it of trappings that matter nowhere outside of academia and that are a direct violation of carpe diem from the macroeconomic perspective of allocating national resources where they yield their most significant returns.