WHAT SCIENTIFIC CONCEPT WOULD IMPROVE EVERYBODY'S COGNITIVE TOOLKIT?
Professor of Translational Genomics, The Scripps Research Institute; Cardiologist, Scripps Clinic
Hunting for Root Cause: The Human "Black Box"
Root cause analysis is an attractive concept for certain matters in industry, engineering and quality control. A classic application is to determine why a plane crashed by finding the proverbial "black box" — the tamper-proof event data recorder. Even though this box is usually bright orange, the term symbolizes the sense of dark matter, a container with critical information to help illuminate what happened. Getting the black box audio recording is just one component of a root cause analysis for why a plane goes down.
Man is gradually being morphed into an event data recorder by virtue of each person's digital identity and presence on the web. Not only do we post our own data, sometimes unwittingly, but also others post information about us, and all of this is permanently archived. In that way it is close to tamper-proof. With increasing use of biosensors, high-resolution imaging (just think of our current cameras and video recording, no less digital medical imaging), and DNA sequencing, the human data event recorder will be progressively enriched with data and information.
In our busy, networked lives with constant communication, streaming and distraction, the general trend has moved away from acquiring deep knowledge for why something happened. This is best exemplified in health and medicine. Physicians rarely seek root cause. If a patient has a common condition such as high blood pressure, diabetes, or asthma, he or she is put on some prescription drugs without any attempt at ascertaining why the individual crashed — certainly a new, chronic medical condition can be likened to such an event. There are usually specific reasons for these disorders but they are not hunted down. Taken to an extreme, when an individual dies and the cause is not known it is now exceedingly rare that an autopsy is ever performed. Doctors have generally caved in their quest to define root cause, and they are fairly representative of most of us. Ironically, this is happening at a time when there is unprecedented capability for finding the explanation. But we're just too busy.
So to tweak our cognitive performance in the digital world where there is certainly no shortage of data, it's time to use it and understand, as fully as possible, why unexpected or unfavorable things happen. Or even why something great transpired. It's a prototypic scientific concept that has all too often been left untapped. Each person is emerging as an extraordinary event recorder and part of the Internet of all things. Let's go deep. Nothing unexplained these days should go without a hunt.
Senior Consultant (and former Editor-in-Chief and Publishing Director of New Scientist); Author, After the Ice: Life, Death, and Geopolitics in the New Arctic
Our species might well be renamed Homo Dilatus, the procrastinating ape. Somewhere in our evolution we acquired the brain circuitry to deal with sudden crises and respond with urgent action. Steady declines and slowly developing threats are quite different. "Why act now when the future is far off," is the maxim for a species designed to deal with near-term problems and not long term uncertainties. It's a handy view of humankind which everyone who uses science to change policy should keep in their mental took kit, and one that that is greatly reinforced by the endless procrastination in tacking climate change. Cancun follows Copenhagen follows Kyoto but the more we dither and no extraordinary disaster follows, the more dithering seems just fine.
Such behaviour is not unique to climate change. It took the sinking of the Titanic to put sufficient life boats on passenger ships, the huge spill from the Amoco Cadiz to set international marine pollution rules and the Exxon Valdez disaster to drive the switch to double-hulled tankers. The same pattern is seen in the oil industry, with the Gulf spill the latest chapter in the disaster first-regulations later mindset of Homo dilatus.
There are a million similar stories from human history. So many great powers and once dominant corporations slipped away as their fortunes declined without the crisis they needed to force change. Slow and steady change simply leads to habituation not action: you could walk in the British countryside now and hear only a fraction of the birdsong that would have delighted a Victorian poet but we simply cannot feel insidious loss. Only a present crisis wakes us.
So puzzling is our behaviour that the "psychology of climate change" has become a significant area of research, with efforts to find those vital messages that will turn our thinking towards the longer term and away from the concrete now. Sadly, the skull of Homo dilatus seems too thick for the tricks that are currently on offer. In the case of climate change, we might better focus on adaptation until a big crisis comes along to rivet our minds. The complete loss of the summer Arctic ice might be the first. A huge dome of shining ice, about half the size of the United States covers the top of the world in summer now. In a couple of decades it will likely be gone. Will millions of square kilometers of white ice turning to dark water feel like a crisis? If that doesn't do it then following soon after will likely be painful and persistent droughts across the United States, much of Africa, Southeast Asia and Australia.
Then the good side of Homo dilatus may finally surface. A crisis will hopefully bring out the Bruce Willis in all of us and with luck we'll find an unexpected way to right the world before the end of the reel. Then we'll no doubt put our feet up again.
Expert, Financial Derivatives and Risk; Author, Traders, Guns & Money: Knowns and Unknowns in the Dazzling World of Derivatives
Confluence of factors is highly influential in setting off changes in complex systems. A common example is in risk — the "Swiss cheese theory". Losses only occur if all controls fail — the holes in the Swiss cheese align.
Confluence, coincidence of events in a single setting, is well understood. Parallel developments, often in different settings or disciplines, can be influential in shaping events. A coincidence of similar logic and processes in seemingly unrelated activities provide indications of likely future developments and risks. The ability to better recognize "parallelism" would improve cognitive processes.
Economic forecasting is dismal, prompting John Kenneth Galbraith to remark that economists were only put on earth to make astrologers look good. Few economists anticipated the current financial problems, at least before they happened.
However, the art market proved remarkably accurate in anticipating developments, especially the market in the work of Damien Hirst — the best known of a group of artists dubbed yBAs (young British Artists).
Hirst's most iconic work — The Physical Impossibility of Death in the Mind of Someone Living — is a 14-foot (4.3 meter) tiger shark immersed in formaldehyde in a vitrine weighing over two tons. Charles Saatchi (the advertising guru) bought it for £50,000. In December 2004, Saatchi sold the work to Steve Cohen, founder and principal of the uber hedge fund — SAC Capital Advisers, which manages $20 billion. Cohen paid $12 million for The Physical Impossibility of Death in the Mind of Someone Living, although there are allegation that it was only $8 million.
In June 2007, Damien Hirst tried to sell a life size platinum cast of a human skull, encrusted with £15 million worth of 8,601 pave-set industrial diamonds, weighing 1,100 carats including a 52.4 carat pink diamond in the center of the forehead valued at £4 million. For the Love of God was a memento mori, in Latin remember you must die. The work was offered for sale at £50 million as part of Hirst's Beyond Belief show. In September 2007, For the Love of God was sold to Hirst and some investors for full price, for later resale.
The sale of The Physical Impossibility of Death in the Mind of Someone Living marked the final phase of the irresistible rise of markets. The failure of For the Love of God to sell marked its zenith as clearly as any economic marker.
Parallelism exposes common thought processes and similar valuation approaches to unrelated objects.
Hirst was the artist of choice for conspicuously consuming hedge fund managers, who were getting very rich managing money. Inflated prices suggested the presence of "irrational excess". The nature of sought after Hirst pieces and even their titles provided an insight into the hubristic self-image of financiers. With its jaws gaping, poised to swallow its prey, The Physical Impossibility of Death in the Mind of Someone Living mirrored the killer instincts of hedge funds, feared predators in financial markets. Cohen "… liked the whole fear factor."
The work of Japanese artist Takeshi Murakami provides confirmation. Inspired by Hokusai's famous 19th century woodblock print The Great Wave of Kanagawa, Murakami's 727 paintings showed Mr. DOB, a post nuclear Mickey Mouse character, as a god riding on a cloud or a shark surfing on a wave. The first 727 is owned by New York's Museum of Modern Art, the second by Steve Cohen.
Parallelism is also evident in the causes underlying several crises facing humanity. It is generally acknowledged that high levels of debt were a major factor in the ongoing global financial crisis. What is missed is that the logic of debt is similar to one underlying other problematic issues.
There is a striking similarity between the problems of the financial system, irreversible climate change and shortages of vital resources like oil, food and water. Economic growth and wealth was based on borrowed money. Debt allowed society to borrow from the future. It accelerated consumption, as debt is used to purchase something today against the uncertain promise of paying back the borrowing in the future. Society polluted the planet, creating changes in the environment which are difficult to reserve. Under-priced, natural finite resources were wantonly utilized, without proper concern about conservation.
In each area, society borrowed from and pushed problems into the future. Current growth and short-term profits were pursued at the expense of risks which were not evident immediately and that would emerge later.
To dismiss this as short-term thinking and greed is disingenuous. A crucial cognitive factor underlying the approach was a similar process of problem solving — borrowing from or pushing problems further into the future. This was consistently applied across different problems, without consideration of either it relevance, applicability or desirability. Where such parallelism exists, it feeds on itself, potentially leading to total systemic collapse.
Recognition and understanding of parallelism is one way to improve cognitive thinking. It may provide a better mechanism for predicting specific trends. It may also enable people to increase the dialectic richness, drawing on different disciplines. It requires overcoming highly segmented and narrow educational disciplines, rigid institutional structures and restricted approaches to analysis or problem solving.
Evolutionary Psychologist, University of New Mexico; Author, The Mating Mind; Spent
Personality traits are continuous with mental illnesses
We like to draw clear lines between normal and abnormal behavior. It's reassuring, for those who think they're normal. But it's not accurate. Psychology, psychiatry, and behavior genetics are converging to show that there's no clear line between "normal variation" in human personality traits and "abnormal" mental illnesses. Our instinctive way of thinking about insanity — our intuitive psychiatry — is dead wrong.
To understand insanity, we have to understand personality. There's a scientific consensus that personality traits can be well-described by five main dimensions of variation. These "Big Five" personality traits are called openness, conscientiousness, extraversion, agreeableness, and emotional stability. The Big Five are all normally distributed in a bell curve, statistically independent of each other, genetically heritable, stable across the life-course, unconsciously judged when choosing mates or friends, and found in other species such as chimpanzees. They predict a wide range of behavior in school, work, marriage, parenting, crime, economics, and politics.
Mental disorders are often associated with maladaptive extremes of the Big Five traits. Over-conscientiousness predicts obsessive-compulsive disorder, whereas low conscientiousness predicts drug addiction and other "impulse control disorders". Low emotional stability predicts depression, anxiety, bipolar, borderline, and histrionic disorders. Low extraversion predicts avoidant and schizoid personality disorders. Low agreeableness predicts psychopathy and paranoid personality disorder. High openness is on a continuum with schizotypy and schizophrenia. Twin studies show that these links between personality traits and mental illnesses exist not just at the behavioral level, but at the genetic level. And parents who are somewhat extreme on a personality trait are much more likely to have a child with the associated mental illness.
One implication is that the "insane" are often just a bit more extreme in their personalities than whatever promotes success or contentment in modern societies — or more extreme than we're comfortable with. A less palatable implication is that we're all insane to some degree. All living humans have many mental disorders, mostly minor but some major, and these include not just classic psychiatric disorders like depression and schizophrenia, but diverse forms of stupidity, irrationality, immorality, impulsiveness, and alienation. As the new field of positive psychology acknowledges, we are all very far from optimal mental health, and we are all more or less crazy in many ways. Yet traditional psychiatry, like human intuition, resists calling anything a disorder if its prevalence is higher than about 10%.
The personality/insanity continuum is important in mental health policy and care. There are angry and unresolved debates over how to revise the 5th edition of psychiatry's core reference work, the Diagnostic and Statistic Manual of Mental Disorders (DSM-5), to be published in 2013. One problem is that American psychiatrists dominate the DSM-5 debates, and the American health insurance system demands discrete diagnoses of mental illnesses before patients are covered for psychiatric medications and therapies. Also, the U.S. Food and Drug Administration approves psychiatric medications only for discrete mental illnesses. These insurance and drug-approval issues push for definitions of mental illnesses to be artificially extreme, mutually exclusive, and based on simplistic checklists of symptoms. Insurers also want to save money, so they push for common personality variants — shyness, laziness, irritability, conservatism — not to be classed as illnesses worthy of care. But the science doesn't fit the insurance system's imperatives. It remains to be seen whether DSM-5 is written for the convenience of American insurers and FDA officials, or for international scientific accuracy.
Psychologists have shown that in many domains, our instinctive intuitions are fallible (though often adaptive). Our intuitive physics — ordinary concepts of time, space, gravity, and impetus — can't be reconciled with relativity, quantum mechanics, or cosmology. Our intuitive biology — ideas of species essences and teleological functions — can't be reconciled with evolution, population genetics, or adaptationism. Our intuitive morality — self-deceptive, nepotistic, clannish, anthropocentric, and punitive — can't be reconciled with any consistent set of moral values, whether Aristotelean, Kantian, or utilitarian. Apparently, our intuitive psychiatry has similar limits. The sooner we learn those limits, the better we'll be able to help people with serious mental illnesses, and the more humble we'll be about our own mental health.
Professor in philosophy and cognitive science at the Central European University, Budapest
In 1967, Richard Dawkins introduced the idea of a meme: a unit of cultural transmission capable of replicating itself and of undergoing Darwinian selection. "Meme" has become a remarkably successful addition to everybody's cognitive toolkit. I want to suggest that the concept of a meme should be, if not replaced, at least supplemented with that of a cultural attractor.
The very success of the word "meme" is, or so it seems, an illustration of the idea of a meme: the word has now been used billions of time. But is the idea of a meme being replicated whenever the word is being used? Well, no. Not only do "memeticists" have many quite different definition of a meme, but also and more importantly most users of the term have no clear idea of what a meme might be. Each time, the term is being used with a vague meaning relevant in the circumstances. All these meanings overlap but they are not replications of one another. The idea of a meme, as opposed to the word "meme", may not be such a good example of a meme after all!
The case of the meme idea illustrates a general puzzle. Cultures do contain items — ideas, norms, tales, recipes, dances, rituals, tools, practices, and so on — that are produced again and again. These items remain self-similar over social space and time: in spite of variations, an Irish stew is an Irish stew, Little Red Riding Hood is Little Red Riding Hood and a samba is a samba. The obvious way to explain this stability at the macro level of the culture is, or so it seems, to assume fidelity at the micro level of interindividual transmission. Little Red Riding Hood must have been replicated faithfully enough most of the time for the tale to have remained self-similar over centuries of oral transmission or else the story would have drifted in all kinds of ways and the tale itself would have vanished like water in the sand. Macro stability implies micro fidelity. Right? Well, no. When we study micro processes of transmission — leaving aside those that use techniques of strict replication such as printing or internet forwarding — what we observe is a mix of preservation of the model and of construction of a version that suits the capacities and interests of the transmitter. From one version to the next, the changes may be small, but when they occur at the population scale, their cumulative effect should compromise the stability of cultural items. But — and here lies the puzzle — they don't. What, if not fidelity, explains stability?
Well, bits of culture — memes if you want to dilute the notion and call them that — remain self-similar not because they are replicated again and again but because variations that occur at almost every turn in their repeated transmission, rather than resulting in "random walks" drifting away in all directions from an initial model, tend to gravitate around cultural attractors. Ending Little Red Riding Hood when the wolf eats the child would make for a simpler story to remember, but a Happy Ending is too powerful a cultural attractor. If a person had only heard the story ending with the wolf's meal, my guess is that either she would not have retold it at all — and that is selection — , or she would have modified by reconstructing a happy ending — and this is attraction. Little Red Riding Hood has remained culturally stable not because it has been faithfully replicated all along, but because the variations present in all its versions have tended to cancel one another out.
Why should there be cultural attractors at all? Because there are in our minds, our bodies, and our environment biasing factors that affect the way we interpret and re-produce ideas and behaviors. (I write "re-produce" with a hyphen because, more often than not, we produce a new token of the same type without reproducing in the usual sense of copying some previous tokens.) When these biasing factors are shared in a population, cultural attractors emerge.
Here are a few rudimentary examples.
Rounded numbers are cultural attractors: they are easier to remember and provide better symbols for magnitudes. So, we celebrate twentieth wedding anniversaries, hundredth issue of journals, millionth copy sold of a record, and so on. This, in turn, creates a special cultural attractor for prices, just below rounded numbers — $9.99 or $9,990 are likely price tags — , so as to avoid the evocation of a higher magnitude.
In the diffusion of techniques and artifacts, efficiency is a powerful cultural attractor. Paleolithic hunters learning from their elders how to manufacture and use bows and arrows were aiming not so much at copying the elders than at becoming themselves as good as possible at shooting arrows. Much more than faithful replication, this attraction of efficiency when there aren't that many ways of being efficient, explains the cultural stability (and also the historical transformations) of various technical traditions.
In principle there should be no limit to the diversity of supernatural beings humans can imagine. However, as Pascal Boyer has argued, only a limited repertoire of such beings is exploited in human religions. Its members — ghosts, gods, ancestor spirits, dragons, and so on — have all in common two features. On the one hand, they each violate some major intuitive expectations about living beings: expectation of mortality, of belonging to one and only one species, of being limited in one's access to information, and so on. On the other hand, they satisfy all other intuitive expectations and are therefore, in spite of their supernaturalness, rather predictable. Why should this be so? Because being "minimally counterintuitive" (Boyer's phrase) makes for "relevant mysteries" (my phrase) and is a cultural attractor. Imaginary beings that are either less or more counterintuitive than that are forgotten or are transformed in the direction of this attractor.
And what is the attractor around which the "meme" meme gravitate? The meme idea — or rather a constellation of trivialized versions of it — has become an extraordinarily successful bit of contemporary culture not because it has been faithfully replicated again and again, but because our conversation often does revolve — and here is the cultural attractor — around remarkably successful bits of culture that, in the time of mass media and the internet, pop up more and more frequently and are indeed quite relevant to our understanding of the world we live in. They attract our attention even when — or, possibly, especially when — we don't understand that well what they are and how they come about. The meaning of "meme" has drifted from Dawkins precise scientific idea to a means to refer to these striking and puzzling objects.
This was my answer. Let me end by sharing a question (which time will answer): is the idea of a cultural attractor itself close enough to a cultural attractor for a version of it to become in turn a "meme"?
Technology Entrepreneur & Venture Capitalist, Khosla Ventures; Formerly General Partner at Kleiner Perkins. Caufield & Byers; Founder, Sun Microsystems
The Black Swan Technology
Think back to the world 10 years ago. Google had just gotten started; Facebook and Twitter didn't exist. There were no smart phones, no one remotely conceived of the possibility of the 100,000 iPhone apps that exist today. The few large impact technologies (versus slightly incremental advances in technologies) that occurred in the past 10 years were black swan technologies. In his book, Nassim Taleb defines a Black Swan as an event of low probability, extreme impact, and with only retrospective predictability. Black swans can be positive or negative in their impact and are found in every sector. Still, the most pressing reason I believe "black swan technology" is a conceptual tool that should be added to everyone's cognitive toolkit today is simply because the challenges of climate change and energy production we face today are too big to be tackled by known solutions and safe bets.
I recall fifteen years ago when we were starting Juniper networks, there was absolutely no interest in replacing traditional telecommunications infrastructure (ATM was the mantra) with Internet protocols. After all, there were hundreds of billions of dollars invested in the legacy infrastructure, and it looked as immovable as today's energy infrastructure. Conventional wisdom would say to make incremental improvement to maximize the potential of the existing infrastructure. The fundamental flaw in the conventional wisdom is the failure to acknowledge the possibility of a black swan. Improbable is not unimportant. I believe the likely future is not a traditional econometric forecast but rather one of today's improbable becoming tomorrow's conventional wisdom! Who would be crazy enough t forecast in 2000 that by 2010 almost twice as many people in India would have access to cell phones than latrines? Wireless phones were once only for the very rich. With a black swan technology shot you need not be constrained with the limits of the current infrastructure, projections or market. You simply change the assumptions.
Many argue that since we already have some alternative energy technology today, we should quickly deploy it. They fail to see the potential of the Black Swan technology possibilities; they discount them because they mistake improbable for unimportant and cannot imagine the art of the possible which technology enables. I believe doing this alone runs the risk of spending vast amounts of money on outdated conventional wisdom. Even more importantly, it won't solve the problems we face. Any time focused on short-term, incremental solutions will only distract from working on the homeruns that could change the assumptions around energy and society's resources. While there is no shortage of existing technology providing incremental improvements today — whether today's thin film solar cells, wind turbines, or lithium ion batteries — even summed, they are simply irrelevant to the scale of our problems. They may even make interesting and sometimes large businesses, but will not impact the prevailing energy and resource issues at scale. For that we must look for and invest in quantum jumps in technology with low probability of success; we must create in Black Swan technologies. We must enable the multiplication of resources that only technology can do.
So what are these next generation technologies, these black swan technologies of energy? These are risky investments that stand a high chance of failure, but enable larger technological leaps that promise earthshaking impact if successful: making solar power cheaper than coal or viable without subsidies, economically making lighting and air conditioning 80 percent more efficient. Consider 100 percent more efficient vehicle engines, ultra-cheap energy storage, and countless other technological leaps that we can't yet imagine. It's unlikely that any single shot works, of course. But even 10 Google-like disruptions out of 10,000 shots will completely upend conventional wisdom, econometric forecasts, and, most importantly, our energy future.
To do so we must reinvent the infrastructure of society by harnessing and motivating bright minds with a whole new set of future assumptions, asking "what could possibly be?" rather than "what is." We need to create a dynamic environment of creative contention and collective brilliance that will yield innovative ideas from across disciplines to allow innovation to triumph. We must encourage a social ecosystem that encourages taking risks on innovation. Popularization of the concept of the "Black Swan Technology," is essential to incorporate the right mindset into the minds of entrepreneurs, policymakers, investors and the public: that anything (maybe even everything) is possible. If we harness and motivate these bright new minds with the right market signals and encouragement, a whole new set of future assumptions, unimaginable today, will be tomorrow's conventional wisdom.
Digital Editor, The Economist; Author, The Edible History of the Humanity
You can show something is definitely dangerous, but not definitely safe
A wider understanding of the fact that you can't prove a negative would, in my view, do a great deal to upgrade the public debate around science and technology.
As a journalist I have lost count of the number of times that people have demanded that a particular technology be "proven to do no harm". This is, of course, impossible, in just the same way that proving that there are no black swans is impossible. You can look for a black swan (harm) in various ways, but if you fail to find one that does not mean that none exists: absence of evidence is not evidence of absence.
All you can do is look again for harm, in a different way. If you still fail to find it after looking in all the ways you can possibly think of, the question is still open: "lack of evidence of harm" means both "safe as far as we can tell" and "we still can't be sure if it's safe or not".
Scientists are often accused of logic-chopping when they point this out. But it would be immensely helpful to public discourse if there was a wider understanding that you can show something is definitely dangerous, but you cannot show it is definitely safe.
Institut Nicod, CNRS, Paris
Kakonomics, or the strange preference for Low-quality outcomes
I think that an important concept to understand why does life suck so often is Kakonomics, or the weird preference for Low-quality payoffs.
Standard game-theoretical approaches posit that, whatever people are trading (ideas, services, or goods), each one wants to receive High-quality work from others. Let's stylize the situation so that goods can be exchanged only at two quality-levels: High and Low. Kakonomics describes cases where people not only have standard preferences to receive a High-quality good and deliver a Low-quality one (the standard sucker's payoff) but they actually prefer to deliver a Low-quality good and receive a Low-quality one, that is, they connive on a Low-Low exchange.
How can it ever be possible? And how can it be rational? Even when we are lazy, and prefer to deliver a Low-quality outcome (like prefer to write a piece for a mediocre journal provided that they do not ask one to do too much work), we still would have preferred to work less and receive more, that is deliver Low-quality and receive High-quality. Kakonomics is different: Here, we not only prefer to deliver a Low-quality good, but also, prefer to receive a Low-quality good in exchange!
Kakonomics is the strange — yet widespread — preference for mediocre exchanges insofar as nobody complains about. Kakonomic worlds are worlds in which people not only live with each other's laxness, but expect it: I trust you not to keep your promises in full because I want to be free not to keep mine and not to feel bad about it. What makes it an interesting and weird case is that, in all kakonomic exchanges, the two parties seem to have a double deal: an official pact in which both declare their intention to exchange at a High-quality level, and a tacit accord whereby discounts are not only allowed but expected. It becomes a form of tacit mutual connivance. Thus, nobody is free-riding: Kakonomics is regulated by a tacit social norm of discount on quality, a mutual acceptance for a mediocre outcome that satisfies both parties, as long as they go on saying publicly that the exchange is in fact at a High-quality level.
Take an example: A well-established best-seller author has to deliver his long overdue manuscript to his publisher. He has a large audience, and knows very well that people will buy his book just because of his name and anyway, the average reader doesn't read more than the first chapter. His publisher knows it as well…Thus, the author decides to deliver to the publisher the new manuscript with a stunning incipit and a mediocre plot (the Low-quality outcome): she is happy with it, congratulates him as she had received a masterpiece (the High-quality rhetoric) and they are both satisfied. The author's preference is not only to deliver a Low-quality work, but also that the publisher gives back the same, for example by avoiding to provide a too serious editing and going on publishing. They trust each other's untrustworthiness, and connive on a mutual advantageous Low outcome. Whenever there is a tacit deal to converge to Low-quality with mutual advantages, we are dealing with a case of Kakonomics.
Paradoxically, if one of the two parties delivers a High-quality outcome instead of the expected Low-quality one, the other party resents it as a breach of trust, even if he may not acknowledge it openly. In the example, the author may resent the publisher if she decides to deliver a High-quality editing. Her being trustworthy in this relation means to deliver Low-quality too. Contrary to the standard Prisoner Dilemma game, the willingness to repeat an interaction with someone is ensured if he or she delivers Low-quality too rather than High-quality.
Kakonomics is not always bad. Sometimes it allows a certain tacitly negotiated discount that makes life more relaxing for everybody. As one friend who was renovating a country house in Tuscany told me once: "Italian builders never deliver when they promise, but the good thing is they do not expect you to pay them when you promise either."
But the major problem of Kakonomics — that in ancient Greek means the economics of the worst — and the reason why it is a form of collective insanity so difficult to eradicate, is that each Low-quality exchange is a local equilibrium in which both parties are satisfied, but each of these exchanges erodes the overall system in the long run. So, the threat to good collective outcomes doesn't come only from free riders and predators, as mainstream social sciences teach us, but also from well-organized norms of Kakonomics that regulate exchanges for the worse. The cement of society is not just cooperation for the good: in order to understand why life sucks, we should look also at norms of cooperation for a local optimum and a common worse.
Software Pioneer, Interface Designer, Author, I Think, There 4 am?
Einstein's Blade in Ockham's Razor
In 1971, when I was a teenager, my father died in a big airplane crash.
Somehow I began to turn 'serious', trying to understand the world around me and my place in it, looking for meaning and sense, beginning to realize: everything was very different than I had previously assumed in the innocence of childhood.
It was the beginning of my own "building a cognitive toolset" and I remember the pure joy of discovery, reading voraciously and — quite out of sync with friends and school — I devoured encyclopedias, philosophy, biographies and... science fiction.
One such story stayed with me and one paragraph within it especially:
"We need to make use of Thargola's Sword! The principle of Parsimony.
First put forth by the medieval philosopher Thargola14, who said,
'We must drive a sword through any hypothesis that is not strictly necessary"
That really made me think — and rethink again...
Finding out who this man might have been took quite a while, but it was also another beginning: a love affair with libraries, large tomes, dusty bindings... surfing knowledge, as it were.
And I did discover: there had been a monk named Guillelmi, from a hamlet surrounded by oaks, apocryphally called 'William of Ockham'. He crossed my path again years later when lecturing in Munich near Occam Street, realizing he had spent the last 20 years of his life there, under King Ludwig IV in the mid 1300s.
Isaac Asimov had pilfered, or let's say homaged, good old Guillelmi for what is now known in many variants as "Ockham's razor", such as
"Plurality should not be posited without necessity."
"Entities are not to be multiplied beyond necessity"
or more general and colloquial and a bit less transliterated from Latin:
A simpler explanation invoking fewer hypothetical constructs is preferrable.
And there it was, the dancing interplay between Simplex and Complex, which has fascinated me in so many forms ever since. For me, it is very near the center of "understanding the world", as our question posited.
Could it really be true, that the innocent sounding 'keep it simple' is really such an optimal strategy for dealing with questions large and small, scientific as well as personal? Surely, trying to eliminate superflous assumptions can be a useful tenet, and can be found from Sagan to Hawking as part of their approach to thinking in science. But something never quite felt right to me — intuitively it was clear that sometimes things are just not simple — and that merely "the simplest" of all explanations cannot be taken as truth or proof.
Any detective story would pride itself in not using the most obvious explanation who did it or how it happened.
Designing a car to 'have the optimal feel going into a curve at high speed' will require hugely complex systems to finally arrive at "simply good".
Water running downhill will take a meandering path instead of the straight line.
Both are examples for a domain shift: the non-simple solution is still "the easiest" seen from another viewpoint: for the water the least energy used going down the shallowest slope is more important than taking the straightest line from A to B.
And that is one of the issues with Ockham:
The definition of what "simple" is — can already be anything but simple.
And what "simpler" is — well, it just doesn't get any simpler there.
There is that big difference between simple and simplistic.
And seen more abstractly, the principle of simple things leading to complexity dances in parallel and involved me deeply throughout my life.
In the early seventies I also began tinkering with the first large scale modular synthesizers, finding quickly how hard it is to recreate seemingly 'simple sounds'.
There was unexpected complexity in a single note struck on a piano that eluded even dozens of oscillators and filters, by magnitudes.
Lately one of many projects has been to revisit the aesthetic space of scientific visualizations, and another, which is the epitomy of mathematics made tangible: Fractals — which I had done almost 20 years ago with virtuoso coder Ben Weiss, now enjoying them via realtime flythroughs on a handheld little smartphone.
Here was the most extreme example: a tiny formula, barely one line on paper, used recursively iterated it yields worlds of complex images of amazing beauty.
(Ben had the distinct pleasure of showing Benoit Mandelbrot an alpha version at the last TED just months before his death)
My hesitation towards overuse of parsimony was expressed perfectly in the quote by Albert Einstein, arguably the counterpart "blade" to Ockham's razor:
"Things should be made as simple as possible — but not simpler"
And there we have the perfect application of its truth, used recursively on itself: Neither Einstein nor Ockham actually used the exact words as quoted!
After I sifted through dozens of books, his collected works and letters in German, the Einstein archives: nowhere there, nor in Britannica, Wikipedia or Wikiquote was anyone able to substantiate exact sources, and the same applies to Ockham. If anything can be found, it is earlier precedences...;)
Surely one can amass retweeted, reblogged and regurgitated instances for both very quickly — they have become memes, of course. One could also take the standpoint that in each case they certainly 'might' have said it 'just like that', since each used several expressions quite similar in form and spirit.
But just to attribute the exact words because they are kind of close would be, well..another case of: it is not that simple!
And there is a huge difference between additional and redundant information.
(Or else one could lose the second redundant "ein" in "Einstein" ?)
Linguistic jesting aside: Nonetheless, the Razor and the Blade constitute a very useful combination of approaching analytical thinking.
Shaving away non-essential conjectures is a good thing, a worthy inclusion in "everybody's toolkit" — and so is the corollary: not to overdo it!
And my own bottom line: There is nothing more complex than simplicity.
Professor, Harvard University, Director, Personal Genome Project
The names Lysenko and Lamarck are nearly synonymous with bad science — worse than merely mediocre science because of the huge political and economical consequences.
From 1927 to 1964 Lysenkov managed to keep the "theory of the inheritance of acquired characteristics" dogmatically directing Soviet agriculture and science. Andrei Sakharov and other Soviet physicists finally provoked the fall of this cabal in the 1960s, blaming it for the "shameful backwardness of Soviet biology and of genetics in particular … defamation, firing, arrest, even death, of many genuine scientists".
At the opposite (yet equally discredited) end of the genetic theory spectrum was the Galtonian eugenic movement, which from 1883 onward grew in popularity in many countries until the 1948 Universal Declaration of Human Rights, ("the most translated document in the world") stated that "Men and women of full age, without any limitation due to race, nationality or religion, have the right to marry and to found a family." Nevertheless, forced sterilizations persisted into the 1970s. The "shorthand abstraction" is that Lysenkoism overestimated the impact of environment and eugenics overestimated the role of genetics.
One form of scientific blindness occurs, as above, when a theory displays exceptional political or religious appeal. But another source of blindness arises when we rebound from catastrophic failures of pseudoscience (or science).
We might conclude from the two aforementioned genetic disasters that we only need to police abuses of our human germ-line inheritance. Combining the above with the ever-simmering debate on Darwin, we might develop a bias that human evolution has stopped or that "design" has no role.
But we are well into an unprecedented new phase of evolution in which we must generalize beyond our DNA-centric world-view. We now inherit acquired characteristics. We always have, but now this feature is dominant and exponential. We apply eugenics at the individual family level (where it is a right) not the governmental level (where it is a wrong). Moreover, we might aim for the same misguided targets that eugenics chose (i.e. uniformity around "ideal" traits), via training and medications.
Evolution has accelerated from geologic speed to internet speed — still employing random mutation and selection, but also using non-random intelligent design — which makes it even faster. We are losing species — not just by extinction, but by merger. There are no longer species barriers between humans, bacteria and plants — or even between humans and machines.
Short-hand abstractions are only one device that we employ to construct the "Flynn Effect". How many of us noticed the minor milestone when the SAT tests first permitted calculators? How many of us have participated in conversations semi-discreetly augmented by Google or text messaging? Even without invoking artificial intelligence, how far are we from commonplace augmentation of our decision-making the way we have augmented our math, memory, and muscles?