Seeing the Future through the Deep Past

woman-gazing-into-a-crystal-ball

We study history not to know the future but to widen our horizons, to understand that our present system is neither natural nor inevitable, and that we consequently have many more possibilities before us than we imagine. (241)

The above is a quote from Ynval Harari’s book Sapiens: A Brief History of Humankind, which I reviewed last time. So that’s his view of history, but what of other fields specifically designed to give us a handle on the future, you know, the kinds of “future studies” futurists claim to be experts in, fields like scenario planning, or even some versions of science-fiction.

Harari probably wouldn’t put much credence on the ability of these fields to predict the future either. The reason being that there are very real epistemological limits to what we can know outside of a limited number of domains.  The reason we are unable to make the same sort of accurate predictions for areas such as history, politics or economics as we do for physics, is that all of the former are examples of Level II chaotic systems. A Level I chaotic system is one where small differences in conditions can result in huge differences in outcomes. Weather is the best example we have of Level I chaos, which is why nearly everyone has at some point in their life wanted to bludgeon the weatherman with his umbrella. Level II chaotic systems make the job of accurate prediction even harder, for, as Harari points out:

Level two chaos is chaos that reacts to predictions about it, and therefore can never be predicted accurately. (240)

Level II chaos is probably the source of many of our philosophical paradoxes regarding, what we can really know, along with free will and its evil deterministic twin, not to mention the kinds of paradoxes we encounter when contemplating time travel, issues we only seem able to resolve in a way that conserves the underlying determinism of nature with our subjective experience of freedom when we assume that there are a multiple or even infinite number of universe that together manifest every possibility. A solution that seems to violate every fiber of our common sense.

Be all that as it may, the one major disappointment of Harari’s Sapiens was his versions of possible futures for humanity,though expressed with full acknowledgement that they were just well reasoned guesses, really weren’t all that different from what we all know already. Maybe we’ll re-engineer our genes even to the point of obtaining biological immortality. Maybe we’ll merge with our machines and become cyborgs. Maybe our AI children will replace us.

It’s not that these are unlikely futures, just commonly held ones, and thinkers who have arrived at them have just as often as not done so without having looked deep into the human past, merely extrapolating from current technological trends. Harari might instead have used his uncovering of the deep past to go in a different direction, not so much to make specific predictions about how the human story will likely end, but to ascertain broad recurring patterns that might narrow down the list of things we should look for in regards to our movement towards the future, and, above all, things whose recurrence we would do best to guard ourselves against.

At least one of these recurring trends identified in Sapiens we should be on the look out for is the Sisyphean character of our actions. We gained numbers and civilization with the Agricultural Revolution, but lost in the process both our health and our freedom, and this Sisyphean aspect did not end with industrialization and the scientific revolution. The industrial revolution that ended our universal scarcity, threatens to boil us all. Our automation of labor has lead us to be crippled by our sedentary lifestyles, our conquest of famine has resulted in widespread obesity, and our vastly expanded longevity has resulted in an epidemic of dementia and Alzheimer’s disease.

It’s a weird “god” indeed that suffers the arrival of a new misfortune the minute an old one is conquered. This is not to argue that our solutions actually make our circumstance worse, rather, it is that our solutions become as much a part of the world that affects us as anything in nature itself, and naturally give rise to some aspects we find problematic and were not intended in the solution to our original problem.

At least some of these problems we will be able to anticipate in advance and because of this they call for neither the precautionary principle of environmentalist, nor the proactionary principle of Max More, but something I’ll call the Design Foresight Principle (DFP). If we used something like the DFP we would design to avoid ethical and other problems that emerge from technology or social policy before they arrive, or at least before a technology is widely adopted. Yet in many cases even a DFP wouldn’t help us because the problem arising from a technology or policy wasn’t obvious until afterward- a classic case of which was DDT’s disastrous effect on bird populations.

This situation where we create something or act in some way in order to solve one problem which in turn causes another isn’t likely a bug, but a deep feature of the universe we inhabit. It not going to go away completely regardless of the extent of our powers. Areas I’d look for this Sisyphean character of human life to rear its head over the next century would include everything from biotechnology, to geoengineering, and even quite laudable attempts to connect the world’s remaining billions in one overarching network.

Another near universal of human history, at least since the Agricultural Revolution Sapiens has been the ubiquity of oppression. Humans, it seems, will almost instantly grasp the potential of any new technology, or form of social organization to start oppressing other humans and animals. Although on the surface far-fetched, it’s quite easy, given the continued existence of slavery, coupled with advances in both neuroscience and genetic engineering to come up with nightmare scenarios where, for instance, alternative small brained humans are biologically engineered and bred to serve as organ donors for humans of the old fashioned sort. One need only combine the claims of technical feasibility by biologists such as George Church of bringing back other hominids such as the Neanderthals, historical research and abuse of animals, and current research using human fetal tissue to grow human organs in pigs to see a nightmare right out of Dr Moreau.

Again far-fetched at the moment, other forms of oppression may be far less viscerally troubling but almost just as bad. As both neural monitoring and the ability to control subjects through optogenetics increases, we might see the rise of “part-time” slavery where one’s freedom is surrendered on the job, or in certain countries perhaps the revival of the institution itself.

The solution here, I think, is to start long before such possibilities manifest themselves, especially in countries with less robust protections regarding worker, human, and animal rights and push hard for research and social policy towards solutions to problems such as the dearth of organs for human beings in need of them that would have the least potentially negative impact on human rights.

Part of the answer to also needs to be in the form of regulation to protect workers from the creep of now largely innocent efforts such as the quantified self movement and its technologies into areas that really would put individual autonomy at risk. The development of near human level AI would seem to be the ultimate solution for human on human oppression, though at some point in the intelligence of our machines, we are might again face the issue of one group of sentient beings oppressing another group for its exclusive benefit.

One seemingly broad trend that I think Harari misidentifies is what he sees as the inexorable move towards a global empire. He states it this way:

 Over millennia, small simple cultures gradually coalesce into bigger and more complex civilizations, so that the world contains fewer and fewer mega-cultures each of which is bigger and more complex. (166)

Since around 200 BC, most humans have lived in empires. It seems likely that in the future, too, most human will live in one. But this time the empire will truly be global. The imperial vision of domination over the entire world could be imminent. (207)

Yet I am far from certain that the movement towards a world empire or state is one that can be seen when we look deep into history. Since their beginnings, empires have waxed and waned. No empire with the scale and depth of integration now stands where the Persian, Roman, or Inca empires once stood. Rather than an unstoppable march towards larger and larger political units we have the rise and collapse of these units covering huge regions.

For the past 500 years the modern age of empires which gave us our globalized world has been a play of ever shifting musical chairs with the Spanish, Portuguese followed by the British and French followed by failed bids by the Germans and the Japanese, followed by the Russians and Americans.

For a quarter century now America has stood alone, but does anyone seriously doubt that this is much more than an interim until the likes of China and India join it? Indeed, the story of early 21st century geopolitics could easily be told as a tale of the limits of American empire.

Harari seems to think a global ruling class is about to emerge on the basis of stints at US universities and hobnobbing at Davos. This is to forget the power of artificial boundaries such as borders, and imagined communities. As scholars of nationalism such as Benedict Anderson have long pointed out you can get strengthened national identity when you combine a lingua franca with a shared education as long as personal opportunities for advancement are based upon citizenship.

Latin American creoles who were denied administrative positions even after they had proven themselves superior to their European-Spanish classmates were barred from becoming members of the elite in Spain itself and thus returned home with a heightened sense of national identity. And just as long as American universities remain the premier educational institutions on earth, which will not be forever, the elite children of other countries will come there for education. They will then have to choose whether to sever their ties with their home country and pursue membership in the American elite, or return home to join the elite of their home country with only tenuous ties to the values of the global power. They will not have the choice to chose both.

Indeed, the only way Harari’s global elite might emerge as a ruling class would be for states to fail almost everywhere. It wouldn’t be the victory of the trend towards “domination over the entire world” but a kind of global neo-feudal order. That is, the two trends we should be looking to history to illuminate when it comes to the future of political order is the much older trend of the rise and fall of empires, or the much younger 500 year trend of the rise and fall of great powers based on states.

One trend that might bolster the chances towards either neo-feudalism or the continued dominance of rival states depending upon how it plays out is the emergence of new forms of money. The management of a monetary system, enforcement of contacts, and protection of property, has always been among the state’s chief functions. As Harari showed us, money, along with writing and mathematics were invented as bureaucratic tools of accounting and management. Yet since the invention of money there has always been this tension between the need for money as a way to facilitate exchange – for which it has to be empty of any information except its value, and the need to record and enforce loans in that medium of exchange- loans and contacts.

This tension between forgetfulness and remembering when it comes to money is one way to see the tug of war between inflation and deflation in the management of it. States that inflate their currency are essentially voting for money has a means of facilitating exchange over the need for money to preserve its values so that past loans and contracts can be met in full.

Digital currencies, of which Bitcoin is only one example, and around which both states and traditional banks are (despite Bitcoin’s fall) are showing increasing interest, by treating money as data allow it to fully combine these two functions as a medium of exchange that can remember. This could either allow states to crush non-state actors, such as drug cartels, that live off the ability of money to forget its origins, or conversely, strengthen those actors (mostly from the realm of business) who claim there is no need for a state because digital currency can make contracts self enforcing. Imagine that rather than money you simply have a digital account which you can only borrow from to make a purchase once it connects itself to a payment system that will automatically withdraw increments until some set date in the future. And imagine that such digital wallets are the only form of money that is actually functional.

There are other trends from deep history we should look to as well to get a sense of what the future may have in store. For instance, the growth of human power has been based not on individual intelligence, but collective organization. New forms of organization using technologies like brain-nets might become available at some future date, and based on the scalability of these technologies might prove truly revolutionary. This will be no less important than the kinds of collective myths that predominate in the future, which, religious or secular will likely continue to determine how we live our lives as they have in the past.

Yet perhaps the most important trend from the deep past for the future will be the one Harari thinks might end desire to make history at all. Where will we go with our mastery over the biochemical keys to our happiness which we formerly sought in everything from drugs to art? It’s a question that deserves a post all to itself.

 

A Global History of Post-humans

Cave painting hand prints

One thing that can certainly not be said either the anthropologist Ynval Harari’s or his new book Sapiens: A Brief History of Humankind is that they lack ambition. In Sapiens, Harari sets out to tell the story of humanity since our emergence on the plans of Africa until the era in which we are living right now today, a period he thinks is the beginning of the end of our particular breed of primate. His book ends with some speculations on our post-human destiny, whether we achieve biological immortality or manage to biologically and technologically engineer ourselves into an entirely different species. If you want to talk about establishing a historical context for the issues confronted by transhumanism, you can’t get better than that.

In Sapiens, Harari organizes the story of humanity by casting it within the framework of three revolutions: the cognitive, the agricultural and the scientific. The Cognitive Revolution is what supposedly happened somewhere between 70,000- 30,000 thousand years ago when a suddenly very creative and  cooperative homo sapiens came roaring out of Africa using their unprecedented social coordination and technological flexibility to invade every ecological niche on the planet.

Armed with an extremely cooperative form of culture, and the ability to make tools, (especially clothing) to fit environments they had not evolved for, homo sapiens was able to move into more northern latitudes than their much more cold adapted Neanderthal cousins, or to cast out on the seas to settle far off islands and continents such as Australia, Polynesia, and perhaps even the Americas.

The speed with which homo sapiens invaded new territory was devastating for almost all other animals. Harari points out how the majority of large land animals outside of Africa (where animals had enough time to evolve weariness of this strange hairless ape) disappeared not long after human beings arrived there. And the casualties included other human species as well.

One of the best things about Harari is his ability to overthrow previous conceptions- as he does here with the romantic notion held by some environmentalist that “primitive” cultures lived in harmony with nature. Long before even the adoption of agriculture, let alone the industrial revolution, the arrival of homo sapiens proved devastating for every other species, including other hominids.

Yet Harari also defies intellectual stereotypes. He might not think the era in which the only human beings on earth were  “noble savages” was a particularly good one for other species, but he does see it as having been a particularly good one for homo sapiens, at least compared to what came afterward, and up until quite recently.

Humans, in the era before the Agricultural Revolution lived a healthier lifestyle than any since. They had a varied diet, and though they only worked on average six hours a day, and were far more active than any of us in modern societies chained to our cubicles and staring at computer screens.

Harari, also throws doubt on the argument that has been made most recently by Steven Piker, that the era before states was one of constant tribal warfare and violence, suggesting that it’s impossible to get an overall impression for levels of violence based on what end up being a narrow range of human skeletal remains. The most likely scenario, he thinks, is that some human societies before agriculture were violent, and some were not, and that even the issue of which societies were violent varied over time rising and falling in respect to circumstances.

From the beginning of the Cognitive Revolution up until the Agricultural Revolution starting around 10,000 years ago things were good for homo sapiens, but as Harari sees it, things really went downhill for us as individuals, something he sees as different from our status as a species, with the rise of farming.

Harari is adamant that while the Agricultural Revolution may have had the effect of increasing our numbers, and gave us all the wonders of civilization and beauty of high culture, its price, on the bodies and minds of countless individuals, both humans, and other animals was enormous. Peasants were smaller, less healthy,  and died younger than their hunter gatherer ancestors. The high culture of the elites of ancient empires was bought at the price of the systematic oppression of the vast majority of human beings who lived in those societies. And, in the first instance of telling this tale with in the context of a global history of humanity that I can think of, Harari tells the story of not just our oppression of each other, but of our domesticated animals as well.

He shows us how inhumane animal husbandry was long before our era of factory farming, which is even worse, but it was these more “natural”, “organic” farmers who began practices such as penning animals in cages, separating mothers from their young, castrating males, and cutting off the noses or out the eyes of animals such a pigs so they could better serve their “divinely allotted” function of feeding human mouths and stomachs.

Yet this begs the question: if the Agricultural Revolution was so bad for the vast majority of human beings, and animals with the exception of a slim class at the top of the pyramid, why did it not only last, but spread, until only a tiny minority of homo sapiens in remote corners continued to be hunter gatherers while the vast majority, up until quite recently were farmers?

Harari doesn’t know. It was probably a very gradual process, but once human societies had crossed a certain threshold there was no going back- our numbers were simply too large to support a reversion to hunting and gathering, For one of the ironies of the Agricultural Revolution is that while it made human beings unhealthy, it also drove up birthrates. This probably happened through rational choice. A hunter gathering family would likely space their children, whereas a peasant family needed all the hands it could produce, something that merely drove the need for more children, and was only checked by the kinds of famines Malthus had pegged as the defining feature of agricultural societies and that we only escaped recently via the industrial revolution.

Perhaps, as Harrai suggest, “We did not domesticate wheat. It domesticated us.” (81) At the only level evolution cares about- the propagation of our genes- wheat was a benefit to humanity, but at the cost of much human suffering and backbreaking labor in which we rid wheat of its rivals and spread the plant all over the globe. The wheat got a better deal, no matter how much we love our toast.

It was on the basis of wheat, and a handful of other staple crops (rice, maize, potatoes) that states were first formed. Harari emphasizes the state’s role as record keeper, combined with enforcer of rules. The state saw its beginning as a scorekeeper and referee for the new complex and crowded societies that grew up around farming.

All the greatest works of world literature, not to mention everything else we’ve ever read, can be traced back to this role of keeping accounts, of creating long lasting records, that led the nascent states that grew up around agriculture to create writing. Shakespeare’s genius can trace its way back to the 7th century B.C. equivalent to an IRS office. Along with writing the first states also created numbers and mathematics, bureaucrats have been bean counters ever since.

The quirk of human nature that for Harari made both the Cognitive and Agricultural Revolution possible and led to much else besides was our ability to imagine things that do not exist, by which he means almost everything we find ourselves surrounded by, not just religion, but the state and its laws, and everything in between has been akin to a fantasy game. Indeed, Harari left me feeling that the whole of both premodern and modern societies was at root little but a game of pretend played by grown ups, with adulthood perhaps nothing more than agreeing to play along with the same game everyone else is engaged in. He was especially compelling and thought provoking when it came to that ultimate modern fantasy and talisman that all of us, from Richard Dawkins to, Abu Bakr al-Baghdadi believes in; namely money.

For Harari the strange thing is that: “Money is the only trust system created by humans that can bridge almost any cultural gap, and does not discriminate on the basis of religion, gender, race, age or sexual orientation.” In this respect it is “the apogee of human tolerance” (186). Why then have so many of its critics down through the ages denounced money as the wellspring human of evil? He explains the contradiction this way:

For although money builds universal trust between strangers, this trust is invested not in humans, communities or sacred values, but in money itself and the impersonal systems that back it. We do not trust the stranger or the next store neighbor- we trust the coins they hold. If they run out of coins, we run out of trust. (188)

We ourselves don’t live in the age of money, so much as the age of Credit (or capital), and it is this Credit which Harari sees as one of the legs of the three-legged stools which he think defines our own period of history. For him we live in the age of the third revolution in human history, the age of the Scientific Revolution that has followed his other two. It is an age built out of an alliance of the forces of Capital-Science- and Empire.

What has made our the age of Credit and different from the material cultures that have come before where money certainly played a prominent role, is that we have adopted lending as the route to economic expansion. But what separates us from past eras that engaged in lending as well, is that ours is based on a confidence that the future will be not just different but better than the past, a confidence that has, at least so far, panned out over the last two centuries largely through the continuous advances in science and technology.

The feature that really separated the scientific revolution from earlier systems of knowledge, in Harari’s view, grew out of the recognition in the 17th century of just how little we actually knew:

The Scientific Revolution has not been a revolution of knowledge. It has above all been a revolution of ignorance. The great discovery that launched the Scientific Revolution was the discovery that humans do not know the answers to their most important questions. (251)

Nothing perhaps better captures the early modern recognition of this ignorance than their discovery of the New World which began us down our own unique historical path towards Empire. Harari sees both Credit and Science being fed and feeding the intermediary institution of Empire, and indeed, that the history of capitalism along with science and technology cannot be understood without reference to the way the state and imperialism have shaped both.

The imperialism of the state has been necessary to enable the penetration of capitalism and secure its gains, and the powers of advanced nations to impose these relationships has been the result largely of more developed science and technology which the state itself has funded. Science was also sometimes used not merely to understand the geography and culture of subject peoples to exploit them, but in the form of 19th century and early 20th century racism was used as a justification for that racism itself. And the quest for globe spanning Empire that began with the Age of Exploration in the 15th century is still ongoing.

Where does Harari think all this is headed?

 Over millennia, small simple cultures gradually coalesce into bigger and more complex civilizations, so that the world contains fewer and fewer mega-cultures each of which is bigger and more complex. (166)

Since around 200 BC, most humans have lived in empires. It seems likely that in the future, too, most human will live in one. But this time the empire will truly be global. The imperial vision of domination over the entire world could be imminent. (207)

Yet Harari questions not only whether the scientific revolution or the new age of economic prosperity, not to mention the hunt for empire, have actually brought about a similar amount of misery, if not quite suffering, as the Agricultural Revolution that preceded it.

After all, the true quest of modern science is really not power, but immortality. In Harari’s view we are on the verge of fulfilling the goal of the “Gilgamesh Project”.

Our best minds are not wasting their time trying to give meaning to death. Instead, they are busy investigating the physiological, hormonal and genetic systems responsible for disease and old age. They are developing new medicines, revolutionary treatments and artificial organs that will lengthen our lives and might one day vanquish the Grim Reaper himself. (267)

The quest after wealth, too, seems to be reaching a point of diminishing returns. If the objective of material abundance was human happiness, we might ask why so many of us are miserable? The problem, Harari thinks, might come down to biologically determined hedonic set-points that leave a modern office worker surrounded by food and comforts ultimately little happier to his peasant ancestor who toiled for a meager supper from sunset to sunrise. Yet perhaps the solution to this problem is at our fingertips as well:

 There is only one historical development that has real significance. Today when we realize that the keys to happiness are in the hands of our biochemical system, we can stop wasting our time on politics, social reforms, putsches, and ideologies and focus instead on the only thing that truly makes us happy: manipulating our biochemistry.  (389)

Still, even should the Gilgamesh Project succeed, or we prove capable of mastering our biochemistry, Harari sees a way the Sisyphean nature may continue to have the last laugh. He writes:

Suppose that science comes up with cures for all diseases, effective anti-ageing therapies and regenerative treatments that keep people indefinitely young. In all likelihood, the immediate result will be an epidemic of anger and anxiety.

Those unable to afford the new treatments- the vast majority of people- will be besides themselves with rage. Throughout history, the poor and oppressed comforted themselves with the thought that at least death is even handed- that the rich and powerful will also die. The poor will not be comfortable with the thought that they have to die, while the rich will remain young and beautiful.

But the tiny minority able to afford the new treatments will not be euphoric either. They will have much to be anxious about. Although the new therapies could extend life and youth they will not revive corpses. How dreadful to think that I and my loved ones can live forever, but only if we don’t get hit by a truck or blown to smithereens by a terrorist! Potentially a-mortal people are likely to grow adverse to taking even the slightest risk, and the agony of losing a spouse, child or close friend will be unbearable.( 384-385).

Along with this, Harari reminds us that it might not be biology that is most important for our happiness, but our sense of meaning. Given that he thinks all of our sources of meaning are at bottom socially constructed illusions, he concludes that perhaps the only philosophically defensible position might be some form of Buddhism- to stop all of our chasing after desire in the first place.

The real question is whether the future will show if all our grasping has ended up in us reaching our object or has led us further down the path of illusion and pain that we need to outgrow to achieve a different kind of transcendence.

 

Truth and Prediction in the Dataclysm

The Deluge by Francis Danby. 1837-1839

Last time I looked at the state of online dating. Among the figures was mentioned was Christian Rudder, one of the founders of the dating site OkCupid and the author of a book on big data called Dataclysm: Who We Are When We Think No One’s Looking that somehow manages to be both laugh-out-loud funny and deeply disturbing at the same time.

Rudder is famous, or infamous depending on your view of the matter, for having written a piece about his site with the provocative title: We experiment on human beings!. There he wrote: 

We noticed recently that people didn’t like it when Facebook “experimented” with their news feed. Even the FTC is getting involved. But guess what, everybody: if you use the Internet, you’re the subject of hundreds of experiments at any given time, on every site. That’s how websites work.

That statement might set the blood of some boiling, but my own negative reaction to it is somewhat tempered by the fact that Rudder’s willingness to run his experiments on his sites users originates, it seems, not in any conscious effort to be more successful at manipulating them, but as a way to quantify our ignorance. Or, as he puts it in the piece linked to above:

I’m the first to admit it: we might be popular, we might create a lot of great relationships, we might blah blah blah. But OkCupid doesn’t really know what it’s doing. Neither does any other website. It’s not like people have been building these things for very long, or you can go look up a blueprint or something. Most ideas are bad. Even good ideas could be better. Experiments are how you sort all this out.

Rudder eventually turned his experiments on the data of OkCupid’s users into his book Dataclysm which displays the same kind of brutal honesty and acknowledgement of the limits of our knowledge. What he is trying to do is make sense of the deluge of data now inundating us. The only way we have found to do this is to create sophisticated algorithms that allow us to discern patterns in the flood.  The problem with using algorithms to try and organize human interactions (which have themselves now become points of data) is that their users are often reduced into the version of what being a human beings is that have been embedded by the algorithm’s programmers. Rudder, is well aware and completely upfront about these limitations and refuses to make any special claims about algorithmic wisdom compared to the normal human sort. As he puts it in Dataclysm:

That said, all websites, and indeed all data scientists objectify. Algorithms don’t work well with things that aren’t numbers, so when you want a computer to understand an idea, you have to convert as much of it as you can into digits. The challenge facing sites and apps is thus to chop and jam the continuum of the of human experience into little buckets 1, 2, 3, without anyone noticing: to divide some vast, ineffable process- for Facebook, friendship, for Reddit, community, for dating sites, love- into a pieces a server can handle. (13)

At the same time, Rudder appears to see the data collected on sites such as OkCupid as a sort of mirror, reflecting back to us in ways we have never had available before the real truth about ourselves laid bare of the social conventions and politeness that tend to obscure the way we truly feel. And what Rudder finds in this data is not a reflection of the inner beauty of humanity one might hope for, but something more like the mirror out of A Picture of Dorian Grey.

As an example take what Rudder calls” Wooderson’s Law” after the character from Dazed and Confused who said in the film “That’s what I love about these high school girl, I get older while they stay the same age”. What Rudder has found is that heterosexual male attraction to females peaks when those women are in their early 20’s and thereafter precipitously falls. On OkCupid at least, women in their 30’s and 40’s are effectively invisible when competing against women in their 20’s for male sexual attraction. Fortunately for heterosexual men, women are more realistic in their expectations and tend to report the strongest attraction to men roughly their own age, until sometime in men’s 40’s where males attractiveness also falls off a cliff… gulp.

Another finding from Rudder’s work is not just that looks rule, but just how absolutely they rule. In his aforementioned piece, Rudder lays out that the vast majority of users essentially equate personality with looks. A particularly stunning women can find herself with a 99% personality rating even if she has not one word in her profile.

These are perhaps somewhat banal and even obvious discoveries about human nature Rudder has been able to mine from OkCupid’s data, and to my mind at least, are less disturbing than the deep seated racial bias he finds there as well. Again, at least among OkCupid’s users, dating preferences are heavily skewed against black men and women. Not just whites it seems, but all other racial groups- Asians, Hispanics would apparently prefer to date someone from a race other than African- disheartening for the 21st century.

Rudder looks at other dark manifestations of our collective self than those found in OkCupid data as well. Try using Google search as one would play the game Taboo. The search suggestions that pop up in the Google search bar, after all, are compiled on the basis of Google user’s most popular searches and thus provide a kind of gauge on what 1.17 billion human beings are thinking. Try these some of which Rudder plays himself:

“why do women?”

“why do men?”

“why do white people?”

“why do black people?”

“why do Asians?”

“why do Muslims?”

The exercise gives a whole new meaning to Nietzsche’s observation that “When you stare into the abyss, the abyss stares back”.

Rudder also looks at the ability of social media to engender mobs. Take this case from Twitter in 2014. On New Years Eve of that year a young woman tweeted:

“This beautiful earth is now 2014 years old, amazing.”

Her strength obviously wasn’t science in school, but what should have just led to collective giggles, or perhaps a polite correction regarding terrestrial chronology, ballooned into a storm of tweets like this:

“Kill yourself”

And:

“Kill yourself you stupid motherfucker”. (139)

As a recent study has pointed out the emotion second most likely to go viral is rage, we can count ourselves very lucky the emotion most likely to go viral is awe.

Then there’s the question of the structure of the whole thing. Like Jaron Lanier, Rudder is struck by the degree to which the seemingly democratized architecture of the Internet appears to consistently manifest the opposite and reveal itself as following Zipf’s Law, which Rudder concisely reduces to:

rank x number = constant (160)

Both the economy and the society in the Internet age are dominated by “superstars”, companies (such as Google and FaceBook that so far outstrip their rivals in search or social media that they might be called monopolies), along with celebrities, musical artist, authors. Zipf’s Law also seems to apply to dating sites where a few profiles dominate the class of those viewed by potential partners. In the environment of a networked society where invisibility is the common fate of almost all of us and success often hinges on increasing our own visibility we are forced to turn ourselves towards “personal branding” and obsession over “Klout scores”. It’s not a new problem, but I wonder how much all this effort at garnering attention is stealing time from the effort at actual work that makes that attention worthwhile and long lasting.

Rudder is uncomfortable with all this algorithmization while at the same time accepting its inevitability. He writes of the project:

Reduction is inescapable. Algorithms are crude. Computers are machines. Data science is trying to make sense of an analog world. It’s a by-product of the basic physical nature of the micro-chip: a chip is just a sequence of tiny gates.

From that microscopic reality an absolutism propagates up through the whole enterprise, until at the highest level you have the definitions, data types and classes essential to programming languages like C and JavaScript.  (217-218)

Thing is, for all his humility at the effectiveness of big data so far, or his admittedly limited ability to draw solid conclusions from the data of OkCupid, he seems to place undue trust in the ability of large corporations and the security state to succeed at the same project. Much deeper data mining and superior analytics, he thinks, separate his efforts from those of the really big boys. Rudder writes:

Analytics has in many ways surpassed the information itself as the real lever to pry. Cookies in your web browser and guys hacking for your credit card numbers get most of the press and our certainly the most acutely annoying of the data collectors. But they’ve taken hold of a small fraction of your life and for that they’ve had to put in all kinds of work. (227)

He compares them to Mike Myer’s Dr. Evil holding the world hostage “for one million dollars”

… while the billions fly to the real masterminds, like Axicom. These corporate data marketers, with reach into bank and credit card records, retail histories, and government fillings like tax accounts, know stuff about human behavior that no academic researcher searching for patterns on some website ever could. Meanwhile the resources and expertise the national security apparatus brings to bear makes enterprise-level data mining look like Minesweeper (227)

Yet do we really know this faith in big data isn’t an illusion? What discernable effects that are clearly traceable to the juggernauts of big data ,such as Axicom, on the overall economy or even consumer behavior? For us to believe in the power of data shouldn’t someone have to show us the data that it works and not just the promise that it will transform the economy once it has achieved maximum penetration?

On that same score, what degree of faith should we put in the powers of big data when it comes to security? As far as I am aware no evidence has been produced that mass surveillance has prevented attacks- it didn’t stop the Charlie Hebo killers. Just as importantly, it seemingly hasn’t prevented our public officials from being caught flat footed and flabbergasted in the face of international events such as the revolution in Egypt or the war in Ukraine. And these later big events would seem to be precisely the kinds of predictions big data should find relatively easy- monitoring broad public sentiment as expressed through social media and across telecommunications networks and marrying that with inside knowledge of the machinations of the major political players at the storm center of events.

On this point of not yet mastering the art of being able to anticipate the future despite the mountains of data it was collecting,  Anne Neuberger, Special Assistant to the NSA Director, gave a fascinating talk over at the Long Now Foundation in August last year. During a sometimes intense q&a she had this exchange with one of the moderators, Stanford professor, Paul Saffo:

 Saffo: With big data as a friend likes to say “perhaps the data haystack that the intelligence community has created has grown too big to ever find the needle in.”

Neuberger : I think one of the reasons we talked about our desire to work with big data peers on analytics is because we certainly feel that we can glean far more value from the data that we have and potentially collect less data if we have a deeper understanding of how to better bring that together to develop more insights.

It’s a strange admission from a spokesperson from the nation’s premier cyber-intelligence agency that for their surveillance model to work they have to learn from the analytics of private sector big data companies whose models themselves are far from having proven their effectiveness.

Perhaps then, Rudder should have extended his skepticism beyond the world of dating websites. For me, I’ll only know big data in the security sphere works when our politicians, Noah like, seem unusually well prepared for a major crisis that the rest of us data poor chumps didn’t also see a mile away, and coming.

 

Sex and Love in the Age of Algorithms

Eros and Psyche

How’s this for a 21st century Valentine’s Day tale: a group of religious fundamentalists want to redefine human sexual and gender relationships based on a more than 2,000 year old religious text. Yet instead of doing this by aiming to seize hold of the cultural and political institutions of society, a task they find impossible, they create an algorithm which once people enter their experience is based on religiously derived assumptions users cannot see. People who enter this world have no control over their actions within it, and surrender their autonomy for the promise of finding their “soul mate”.

I’m not writing a science-fiction story- it’s a tale that’s essentially true.

One of the first places, perhaps the only place, where the desire to compress human behavior into algorithmically processable and rationalized “data”, has run into a wall was in the ever so irrational realms of sex and love. Perhaps I should have titled this piece “Cupid’s Revenge”, for the domain of sex and love has proved itself so unruly and non-computable that what is now almost unbelievable has happened- real human beings have been brought back into the process of making actual decisions that affect their lives rather than relying on silicon oracles to tell them what to do.

It’s a story not much known and therefore important to tell. The story begins with the exaggerated claims of what was one of the first and biggest online dating sites- eHarmony. Founded in 2000 by Neil Clark Warren, a clinical psychologist and former marriage counselor, eHarmony promoted itself as more than just a mere dating site claiming that it had the ability to help those using its service find their “soul mate”. As their senior research scientist, Gian C. Gonzaga, would put it:

 It is possible “to empirically derive a matchmaking algorithm that predicts the relationship of a couple before they ever meet.”

At the same time it made such claims, eHarmony was also very controlling in the way its customers were allowed to use its dating site. Members were not allowed to search for potential partners on their own, but directed to “appropriate” matches based on a 200 item questionnaire and directed by the site’s algorithm, which remained opaque to its users. This model of what dating should be was doubtless driven by Warren’s religious background, for in addition to his psychological credentials, Warren was also a Christian theologian.

By 2011 eHarmony garnered the attention of sceptical social psychologists, most notably, Eli J. Finkel, who, along with his co-authors, wrote a critical piece for the American Psychological Association in 2011 on eHarmony and related online dating sites.

What Finkle wanted to know was if claims such as that of eHarmony that it had discovered some ideal way to match individuals to long term partners actually stood up to critical scrutiny. What he and his authors concluded was that while online dating had opened up a new frontier for romantic relationships, it had not solved the problem of how to actually find the love of one’s life. Or as he later put it in a recent article:

As almost a century of research on romantic relationships has taught us, predicting whether two people are romantically compatible requires the sort of information that comes to light only after they have actually met.

Faced with critical scrutiny, eHarmony felt compelled to do something, to my knowledge, none of the programmers of the various algorithms that now mediate much of our relationship with the world have done; namely, to make the assumptions behind their algorithms explicit.

As Gonzaga explained it eHarmony’s matching algorithm was based on six key characteristics of users that included things like “level of agreeableness”  and “optimism”. Yet as another critic of eHarmony Dr. Reis told Gonzaga:

That agreeable person that you happen to be matching up with me would, in fact, get along famously with anyone in this room.

Still, the major problem critics found with eHarmony wasn’t just that it made exaggerated claims for the effectiveness of its romantic algorithms that were at best a version of skimming, it’s that it asserted nearly complete control over the way its users defined what love actually was. As is the case with many algorithms, the one used by eHarmony was a way for its designers and owners to constrain those using it to impose, rightly or wrongly, their own value assumptions about the world.

And like many classic romantic tales, this one ended with the rebellion of messy human emotion over reason and paternalistic control. Social psychologist weren’t the only ones who found eHarmony’s model constraining and weren’t the first to notice its flaws. One of the founders of an alternative dating site, Christian Rudder of OkCupid, has noted that much of what his organization has done was in light of the exaggerated claims for the efficacy of their algorithms and top-down constraints imposed by the creators of eHarmony. But it is another, much maligned dating site, Tinder, that proved to be the real rebel in this story.

Critics of Tinder, where users swipe through profile pictures to find potential dates have labeled the site a “hook-up” site that encourages shallowness. Yet Finkle concludes:

Yes, Tinder is superficial. It doesn’t let people browse profiles to find compatible partners, and it doesn’t claim to possess an algorithm that can find your soulmate. But this approach is at least honest and avoids the errors committed by more traditional approaches to online dating.

And appearance driven sites are unlikely to be the last word in online dating especially for older Romeos and Juliets who would like to go a little deeper than looks. Psychologist, Robert Epstein, working at the MIT Media Lab sees two up and coming trends that will likely further humanize the 21st century dating experience. The first is the rise of non-video game like virtual dating environments. As he describes it:

….so at some point you will be able to have, you know, something like a real date with someone, but do it virtually, which means the safety issue is taken care of and you’ll find out how you interact with someone in some semi-real setting or even a real setting; maybe you can go to some exotic place, maybe you can even go to the Champs-Elyséesin Paris or maybe you can go down to the local fast-food joint with them, but do it virtually and interact with them.

The other, just as important, but less tech-sexy change Epstine sees coming is bringing friends and family back into the dating experience:

Right now, if you sign up with the eHarmony or match.com or any of the other big services, you’re alone—you’re completely alone. It’s like being at a huge bar, but going without your guy friends or your girl friends—you’re really alone. But in the real world, the community is very helpful in trying to determine whether someone is right for you, and some of the new services allow you to go online with friends and family and have, you know, your best friend with you searching for potential partners, checking people out. So, that’s the new community approach to online dating.

As has long been the case, sex and love have been among the first set of explorers moving out into a previously unexplored realm of human possibility. Yet sex and love are also because of this the proverbial canary in the coal mine informing us of potential dangers. The experience of online dating suggest that we need to be sceptical of the exaggerated claims of the various algorithms that now mediate much of lives and be privy to their underlying assumptions. To be successful algorithms need to bring our humanity back into the loop rather than regulate it away as something messy, imperfect, irrational and unsystematic.

There is another lesson here as well, for the more something becomes disconnected from our human capacity to extend trust through person-to-person contact and through taping into the wisdom of our own collective networks of trust the more dependent we become on overseers who in exchange for protecting us from deception demand the kinds of intimate knowledge from us only friends and lovers deserve.

 

Big Data as statistical masturbation

Infinite Book Tunnel

It’s just possible that there is a looming crisis in yet another technological sector whose proponents have leaped too far ahead, and too soon, promising all kinds of things they are unable to deliver. It strange how we keep ramming our head into this same damned wall, but this next crisis is perhaps more important than deflated hype at other times, say our over optimism about the timeline for human space flight in the 1970’s, or the “AI winter” in the 1980’s, or the miracles that seemed just at our fingertips when we cracked the Human Genome while pulling riches out of the air during the dotcom boom- both of which brought us to a state of mania in the 1990’s and early 2000’s.

The thing that separates a potentially new crisis in the area of so-called “Big-Data” from these earlier ones is that, literally overnight, we have reconstructed much of our economy, national security infrastructure and in the process of eroding our ancient right privacy on it’s yet to be proven premises. Now, we are on the verge of changing not just the nature of the science upon which we all depend, but nearly every other field of human intellectual endeavor. And we’ve done and are doing this despite the fact that the the most over the top promises of Big Data are about as epistemologically grounded as divining the future by looking at goat entrails.

Well, that might be a little unfair. Big Data is helpful, but the question is helpful for what? A tool, as opposed to a supposedly magical talisman has its limits, and understanding those limits should lead not to our jettisoning the tool of large scale data based analysis, but what needs to be done to make these new capacities actually useful rather than, like all forms of divination, comforting us with the idea that we can know the future and thus somehow exert control over it, when in reality both our foresight and our powers are much more limited.

Start with the issue of the digital economy. One model underlies most of the major Internet giants- Google, FaceBook and to a lesser extent Apple and Amazon, along with a whole set of behemoths who few of us can name but that underlie everything we do online, especially data aggregators such as Axicom. That model is to essentially gather up every last digital record we leave behind, many of them gained in exchange for “free” services and using this living archive to target advertisements at us.

It’s not only that this model has provided the infrastructure for an unprecedented violation of privacy by the security state (more on which below) it’s that there’s no real evidence that it even works.

Just anecdotally reflect on your own personal experience. If companies can very reasonably be said to know you better than your mother, your wife, or even you know yourself, why are the ads coming your way so damn obvious, and frankly even oblivious? In my own case, if I shop online for something, a hammer, a car, a pair of pants, I end up getting ads for that very same type of product weeks or even months after I have actually bought a version of the item I was searching for.

In large measure, the Internet is a giant market in which we can find products or information. Targeted ads can only really work if they are able refract in their marketed product’s favor the information I am searching for, if they lead me to buy something I would not have purchased in the first place. Derek Thompson, in the piece linked to above points out that this problem is called Endogeneity, or more colloquially: “hell, I was going to buy it anyway.”

The problem with this economic model, though, goes even deeper than that. At least one-third of clicks on digital ads aren’t human beings at all but bots that represent a way of gaming advertising revenue like something right out of a William Gibson novel.

Okay, so we have this economic model based on what at it’s root is really just spyware, and despite all the billions poured into it, we have no idea if it actually affects consumer behavior. That might be merely an annoying feature of the present rather than something to fret about were it not for the fact that this surveillance architecture has apparently been captured by the security services of the state. The model is essentially just a darker version of its commercial forbearer. Here the NSA, GCHQ et al hoover up as much of the Internet’s information as they can get their hands on. Ostensibly, their doing this so they can algorithmically sort through this data to identify threats.

In this case, we have just as many reasons to suspect that it doesn’t really work, and though they claim it does, none of these intelligence agencies will actually look at their supposed evidence that it does. The reasons to suspect that mass surveillance might suffer similar flaws as mass “personalized” marketing, was excellently summed up   in a recent article in the Financial Times Zeynep Tufekci when she wrote:

But the assertion that big data is “what it’s all about” when it comes to predicting rare events is not supported by what we know about how these methods work, and more importantly, don’t work. Analytics on massive datasets can be powerful in analysing and identifying broad patterns, or events that occur regularly and frequently, but are singularly unsuited to finding unpredictable, erratic, and rare needles in huge haystacks. In fact, the bigger the haystack — the more massive the scale and the wider the scope of the surveillance — the less suited these methods are to finding such exceptional events, and the more they may serve to direct resources and attention away from appropriate tools and methods.

I’ll get to what’s epistemologically wrong with using Big Data in the way used by the NSA that Tufekci rightly criticizes in a moment, but on a personal, not societal level, the biggest danger from getting the capabilities of Big Data wrong seems most likely to come through its potentially flawed use in medicine.

Here’s the kind of hype we’re in the midst of as found in a recent article by Tim Mcdonnell in Nautilus:

We’re well on our way to a future where massive data processing will power not just medical research, but nearly every aspect of society. Viktor Mayer-Schönberger, a data scholar at the University of Oxford’s Oxford Internet Institute, says we are in the midst of a fundamental shift from a culture in which we make inferences about the world based on a small amount of information to one in which sweeping new insights are gleaned by steadily accumulating a virtually limitless amount of data on everything.

The value of collecting all the information, says Mayer-Schönberger, who published an exhaustive treatise entitled Big Data in March, is that “you don’t have to worry about biases or randomization. You don’t have to worry about having a hypothesis, a conclusion, beforehand.” If you look at everything, the landscape will become apparent and patterns will naturally emerge.

Here’s the problem with this line of reasoning, a problem that I think is the same, and shares the same solution to the issue of mass surveillance by the NSA and other security agencies. It begins with this idea that “the landscape will become apparent and patterns will naturally emerge.”

The flaw that this reasoning suffers has to do with the way very large data sets work. One would think that the fact that sampling millions of people, which we’re now able to do via ubiquitous monitoring, would offer enormous gains over the way we used to be confined to population samples of only a few thousand, yet this isn’t necessarily the case. The problem is the larger your sample size the greater your chance at false correlations.

Previously I had thought that surely this is a problem that statisticians had either solved or were on the verge of solving. They’re not, at least according to the computer scientist Michael Jordan, who fears that we might be on the verge of a “Big Data winter” similar to the one AI went through in the 1980’s and 90’s. Let’s say you had an extremely large database with multiple forms of metrics:

Now, if I start allowing myself to look at all of the combinations of these features—if you live in Beijing, and you ride bike to work, and you work in a certain job, and are a certain age—what’s the probability you will have a certain disease or you will like my advertisement? Now I’m getting combinations of millions of attributes, and the number of such combinations is exponential; it gets to be the size of the number of atoms in the universe.

Those are the hypotheses that I’m willing to consider. And for any particular database, I will find some combination of columns that will predict perfectly any outcome, just by chance alone. If I just look at all the people who have a heart attack and compare them to all the people that don’t have a heart attack, and I’m looking for combinations of the columns that predict heart attacks, I will find all kinds of spurious combinations of columns, because there are huge numbers of them.

The actual mathematics of sorting out spurious from potentially useful correlations from being distinguished is, in Jordan’s estimation, far from being worked out:

We are just getting this engineering science assembled. We have many ideas that come from hundreds of years of statistics and computer science. And we’re working on putting them together, making them scalable. A lot of the ideas for controlling what are called familywise errors, where I have many hypotheses and want to know my error rate, have emerged over the last 30 years. But many of them haven’t been studied computationally. It’s hard mathematics and engineering to work all this out, and it will take time.

It’s not a year or two. It will take decades to get right. We are still learning how to do big data well.

Alright, now that’s a problem. As you’ll no doubt notice the danger of false correlation that Jordan identifies as a problem for science is almost exactly the same critique Tufekci  made against the mass surveillance of the NSA. That is, unless the NSA and its cohorts have actually solved the statistical/engineering problems Jordan identified and haven’t told us, all the biggest data haystack in the world is going to lead to is too many leads to follow, most of them false, and many of which will drain resources from actual public protection. Perhaps equally troubling: if security services have solved these statistical/engineering problems how much will be wasted in research funding and how many lives will be lost because medical scientists were kept from the tools that would have empowered their research?

At least part of the solution to this will be remembering why we developed statistical analysis in the first place. Herbert I. Weisberg with his recent book Willful Ignorance: The Mismeasure of Uncertainty has provided a wonderful, short primer on the subject.

Statistical evidence, according to Weisberg was first introduced to medical research back in the 1950’s as a protection against exaggerated claims to efficacy and widespread quackery. Since then we have come to take the p value .05 almost as the truth itself. Weisberg’s book is really a plea to clinicians to know their patients and not rely almost exclusively on statistical analyses of “average” patients to help those in their care make life altering decisions in terms of what medicines to take or procedures to undergo. Weisberg thinks that personalized medicine will over the long term solve these problems, and while I won’t go into my doubts about that here, I do think, in the experience of the physician, he identifies the root to the solution of our Big Data problem.

Rather than think of Big Data as somehow providing us with a picture of reality, “naturally emerging” as Mayer-Schönberger quoted above suggested we should start to view it as a way to easily and cheaply give us a metric for the potential validity of a hypothesis. And it’s not only the first step that continues to be guided by old fashioned science rather than computer driven numerology but the remaining steps as well, a positive signal  followed up by actual scientist and other researchers doing such now rusting skills as actual experiments and building theories to explain their results. Big Data, if done right, won’t end up making science a form of information promising, but will instead be used as the primary tool for keeping scientist from going down a cul-de-sac.

The same principle applied to mass surveillance means a return to old school human intelligence even if it now needs to be empowered by new digital tools. Rather than Big Data being used to hoover up and analyze all potential leads, espionage and counterterrorism should become more targeted and based on efforts to understand and penetrate threat groups themselves. The move back to human intelligence and towards more targeted surveillance rather than the mass data grab symbolized by Bluffdale may be a reality forced on the NSA et al by events. In part due to the Snowden revelations terrorist and criminal networks have already abandoned the non-secure public networks which the rest of us use. Mass surveillance has lost its raison d’etre.

At least it terms of science and medicine, I recently saw a version of how Big Data done right might work. In an article for Qunta and Scientific American by Veronique Greenwood she discussed two recent efforts by researchers to use Big Data to find new understandings of and treatments for disease.

The physicist (not biologist) Stefan Thurner has created a network model of comorbid diseases trying to uncover the hidden relationships between different, seemingly unrelated medical conditions. What I find interesting about this is that it gives us a new way of understanding disease, breaking free of hermetically sealed categories that may blind us to underlying shared mechanisms by medical conditions. I find this especially pressing where it comes to mental health where the kind of symptom listing found in the DSM- the Bible for mental health care professionals- has never resulted in a causative model of how conditions such as anxiety or depression actually work and is based on an antiquated separation between the mind and the body not to mention the social and environmental factors that all give shape to mental health.

Even more interesting, from Greenwood’s piece, are the efforts by Joseph Loscalzo of Harvard Medical School to try and come up with a whole new model for disease that looks beyond genome associations for diseases to map out the molecular networks of disease isolating the statistical correlation between a particular variant of such a map and a disease. This relationship between genes and proteins correlated with a disease is something Loscalzo calls a “disease module”.

Thurner describes the underlying methodology behind his, and by implication Loscalzo’s,  efforts to Greenwood this way:

Once you draw a network, you are drawing hypotheses on a piece of paper,” Thurner said. “You are saying, ‘Wow, look, I didn’t know these two things were related. Why could they be? Or is it just that our statistical threshold did not kick it out?’” In network analysis, you first validate your analysis by checking that it recreates connections that people have already identified in whatever system you are studying. After that, Thurner said, “the ones that did not exist before, those are new hypotheses. Then the work really starts.

It’s the next steps, the testing of hypotheses, the development of a stable model where the most important work really lies. Like any intellectual fad, Big Data has its element of truth. We can now much more easily distill large and sometimes previously invisible  patterns from the deluge of information in which we are now drowning. This has potentially huge benefits for science, medicine, social policy, and law enforcement.

The problem comes from thinking that we are at the point where our data crunching algorithms can do the work for us and are about to replace the human beings and their skills at investigating problems deeply and in the real world. The danger there would be thinking that knowledge could work like self-gratification a mere thing of the mind without all the hard work, compromises, and conflict between expectations and reality that goes into a real relationship. Ironically, this was a truth perhaps discovered first not by scientists or intelligence agencies but by online dating services. To that strange story, next time….

There are two paths to superlongevity: only one of them is good

Memento Mori Ivories

Looked at in the longer historical perspective we have already achieved something our ancestors would consider superlongevity. In the UK life expectancy at birth averaged around 37 in 1700. It is roughly 81 today. The extent to which this is a reflection of decreased child mortality versus an increase in the survival rate of the elderly I’ll get to a little later, but for now, just try to get your head around the fact that we have managed to nearly double the life expectancy of human beings in a little over two centuries.

By itself the gains we have made in longevity are pretty incredible, but we have also managed to redefine what it means to be old. A person in 1830 was old at forty not just because of averages, but by the conditions of his body. A revealing game to play is to find pictures of adults from the 19th century and try to guess their ages. My bet is that you, like myself, will consistently estimate the people in these photos to be older than they actually were when the picture was taken. This isn’t a reflection of their lack of Botox and Photoshop, so much as the fact that they were missing the miracle of modern dentistry, were felled, or at least weathered, by diseases which we now consider mere nuisances. If I were my current age in 1830 I would be missing most of my teeth and the pneumonia I caught a few years back would have surely killed me, having been a major cause of death in the age of Darwin and Dickens.

Sixty or even seventy year olds today are probably in the state of health that a forty year old was in the 19th century. In other words we’ve increased the healthspan, not just the lifespan. Sixty really is the new forty, though what is important is how you define “new”. Yet get passed eighty in the early 21st century and you’re almost right back in the world where our ancestors lived. Experiencing the debilitations of old age that is the fate of those of us lucky enough to survive through the pleasures of youth and middle age. The disability of the old is part of the tragic aspect of life, and as always when it comes to giving poetic shape to our comic/ tragic existence, the Greeks got to the essence of old age with their myth of Tithonus.

Tithonus was a youth who had the ill fortune of inspiring the love of the goddess of spring Eos. (Love affairs between gods and mortals never end well). Eos asked Zeus to grant the youth immortality, which he did, but, of course, not in the way Eos intended. Tithonus would never die, but he also would continue to age becoming not merely old and decrepit, but eventually shrivel away to a grasshopper hugging a room’s corner. It is best not to ask the gods for anything.

Despite our successes, those of us lucky enough to live into our 7th and 8th decades still end up like poor old Tithonus. The deep lesson of the ancient myth still holds- longevity is not worth as much as we might hope if not also combined with the health of youth, and despite all of our advances, we are essentially still in Tithonus’ world.

Yet perhaps not for long. At least if one believes the story told by Jonathan Weiner in his excellent book Long for this World.  I learned much about our quest for long life and eternal youth from Long for this World, both its religious and cultural history, and the trajectory and state of its science. I never knew that Jewish folklore had a magical city called Luz where the death unleashed in Eden was prevented from entering, and that existed until  all its inhabitants became so bored that they walked out from its walls and we struck down by the Angel of Death waiting eagerly outside.

I did not know that Descartes, who had helped unleash the scientific revolution, thought that gains in knowledge were growing so fast that he would live to be 1,000. (He died in 1650 at 54). I did not realize that two other key figures of the scientific revolution Roger and Francis Bacon (no relation) thought that science would restore us to the knowledge before the fall (prelapsarian) which would allow us to live forever, or the depth to which very different Chinese traditions had no guilt at all about human immorality and pursued the goal with all sorts of elixirs and practices, none of which, of course, worked. I was especially taken with the story of how Pennsylvania’s most famous son- Benjamin Franklin- wanted to be “pickled” and awoken a century later.

Reviewing the past, when even ancient Egyptian hieroglyphs offer up recipes for “guaranteed to work” wrinkle creams, shows us just how deeply human the longing for agelessness is. It wasn’t invented by Madison Avenue or Dr Oz if even the attempts to find a fountain of youth by the ancients seem no less silly than many of our own. The question, I suppose, is the one that most risks the accusation that one is a fool: “Is this time truly different?” Are we, out of all the generations that have come before us believing the discovery of the route to human “immortality” (and every generation since the rise of modern science has had those who thought so) actually the ones who will achieve this dream?

Long for this World is at its heart a serious attempt to grapple with this question and tries to give us a clear picture of longevity science built around the theoretical biologist, Aubrey de Grey, who will either go down in history as a courageous prophet of a new era of superlongevity, or as just another figure in our long history of thinking biological immortality is at our fingertips when all we are seeing is a mirage.

One thing we have on our ancestors who chased this dream is that we know much, much, more about the biology of aging. Darwinian evolution allowed us to be able to conceive non- poetic theories on the origins of death. In the 1880’s the German biologist, August Weismann in his essay “Upon the Eternal Duration of Life”, provided a kind of survival of the fittest argument for death and aging. Even an ageless creature, Weismann argued, would overtime have to absorb multiple shocks eventually end up disabled. The the longer something lives the more crippled and worn out it becomes. Thus, it is in the interest of the species that death exists to clear the world of these disabled- very damned German- the whole thing.

Just after World War II the biologist Peter Medawar challenged the view of  Weismann. For Medawar if you look at any species selective pressures are really only operating when the organism is young. Those who can survive long enough to breed are the only ones that really count when it comes to natural selection. Like versions of James Dean or Marilyn Monroe, nature is just fine if we exit the world in the bloom of youth- as long, that is, as we have passed our genes.

In other words, healthful longevity has not really been something that natural selection has been selecting most organisms for, and because of this it hasn’t been selecting against bad things that can happen to old organisms either, as we’re finding when, by saving people from heart attacks in their 50’s, we destin them to die of diseases that were rare or unknown in the past like Alzheimers. In a sense we’re the victim of natural selection not caring about the health of those past reproductive age or their longevity.

Well, this is only partly true. Organisms that live in conditions where survival in youth is more secure end up with stretched longevity for their size. Some bats can live decades when similar sized mice have a lifespan of only a couple of years. Tortoises can live for well over a century while alligators of the same weight live from 30-50 years.

Stretching healthful longevity is also something that occurs when you starve an animal. We’ve know for decades that lifespan (in other animals at least) can be increased through caloric restriction. Although the mechanism is unclear, the Darwinian logic is not. Under conditions of starvation it’s a bad idea to breed and the body seems to respond by slowing development waiting for the return of food and a good time to mate.

Thus, there is no such thing as a death clock, lifespan is malleable and can be changed if we just learn how to work the dials. We should have known this from our historical experience over the last two-hundred years in which we doubled the human lifespan, but now we know that nature itself does it all the time and not by, like we do , by addressing the symptoms of aging but by resetting the clock of life itself.

We might ourselves find it easy to reset our aging clock if there weren’t multiple factors that play a role in its ticking. Aubrey de Grey has identified seven- the most important of which (excluding cancerous mutations) are probably the accumulation of “junk” within cells and the development of harmful “cross links” between cells. Strange thing about these is that they are not something that suddenly appears when we are actually “old” but are there all along, only reaching levels when they become noticeable and start to cause problems after many decades. We start dying the day we are born.

As we learn in Long for This World, there is hope that someday we may be able to effectively intervene against all these causes of aging. Every year the science needed to do so advances. Yet as Aubrey de Grey has indicated, the greatest threat to this quest for biological immortality is something we are all too familiar with – cancer.

The possibility of developing cancer emerges from the very way our cells work. Over a lifetime our trillions of cells replicate themselves an even more mind bogglingly high number of times. It is almost impossible that every copying error will be caught before it takes on a life of its own and becomes a cancerous growth. Increasing lifespan only increases the amount of time such copying errors can occur.

It’s in Aubrey de Grey’s solution to this last and most serious of super-longevity’s medical hurdles that Weiner’s faith in the sense of that project breaks down, as does mine. De Grey’s cure for cancer goes by the name of WILT- whole body interdiction of the lengthening of telomeres. A great deal of the cancers that afflict human beings achieve their deadly replication without limit by taking control of the telomerase gene. De Grey’s solution is to strip every human gene of its telomeres, something that, even if successful in preventing cancerous growths, would also leave us without red and white blood cells. In order to allow us to live without these cells, de Grey proposes regular infusions of stem cells. What this leave us with would be a life of constant chemotherapy and invasive medical interventions just to keep us alive. In other words, a life when even healthy people relate to their bodies and are kept alive by medical interventions that are now only experienced by the terminally ill.

I think what shocks Weiner about this last step in SENS is the that it underscores just how radical the medical requirements of engineering superlongevity might become. It’s one thing to talk about strengthening the cell’s junk collector the lysosome by adding an enzyme or through some genetic tweak, it’s another to talk about removing the very cells and structures which define human biology, cells and platelets, which have always been essential for human life and health.

Yet, WILT struck me with somewhat different issues and questions. Here’s how I have come to understand it. For simplicities sake, we might be said to have two models of healthcare, both of which have contributed to the gains we have seen in human health and longevity since 1800. As is often noted, a good deal of this gain in longevity was a consequence of improving childhood mortality. Having less and less people die at the age of five drastically improves the average lifespan. We made these gains largely through public health: things like drastically improved sanitation, potable water, vaccinations, and, in the 20th century antibiotics.

This set of improvements in human health were cheap, “easy”, and either comprised of general environmental conditions, or administered at most annually- like the flu shoot. These features allowed this first model of healthcare to be distributed broadly across the population leading to increased longevity by saving the lives primarily of the young. In part these improvements, and above all the development of antibiotics, also allowed longevity increases from at older end of the scale, which although less pronounced than improvements in child mortality, are, nonetheless very real. This is my second model of healthcare and includes things everything from open heart surgery, to chemo and radiation treatments for cancer, to lifelong prescription drugs to treat chronic conditions.

As opposed to the first model, the second one is expensive, relatively difficult, and varies greatly among different segments of the population. My Amoxicillin and Larry Page’s Amoxicillin are the same, but the medical care we would receive to treat something like cancer would be radically different.

We actually are making greater strides in the battle against cancer than at any time since Nixon declared war on the scourge way back in the 1970’s. A new round of immunosuppressive drugs that are proving so successful against a host of different cancers that John LaMattina, former head of research and development for Pfizer has stated that “We are heading towards a world where cancer will become a chronic disease in much the same way as we have seen with diabetes and HIV.”

The problem is the cost which can range up to 150,000 per year. The costs of the new drugs are so expensive that the NHS has reduced the amount they are willing to spend on them by 30 percent. Here we are running up against the limits to second model of healthcare, a limit that at some point will force societies to choose between providing life preserving care for all, or only to those rich enough to afford it.

If the superlongevity project is going to be a progressive project it seems essential to me that it look like the first model of healthcare rather than the second. Otherwise it will either leave us with divergences in longevity within and between societies that make us long nostalgically for the “narrowness” of current gap between today’s poorest and richest societies, or it will bankrupt countries that seek to extend increased longevity to everyone.

This would require a u-turn from the trajectory of healthcare today which is dominated and distorted by the lucrative world of the second model. As an example of this distortion: the physicists, Paul Davies, is working on a new approach to cancer that involves attempting to attack the disease with viruses. If successful this would be a good example of model one. Using viruses (in a way the reverse of immunosuppressives) to treat cancer would likely be much cheaper than current approaches to cancer involving radiation, chemotherapy, and surgery due to the fact that viruses can self-replicate after being engineered rather than needing to be expensively and painstakingly constructed in drug labs. The problem is that it’s extremely difficult for Davies to get funding for such research precisely because there isn’t that much money to be made in it.

In an interview about his research, Davies compared his plight to how drug companies treat aspirin. There’s good evidence to show that plain old aspirin might be an effective preventative against cancer. Sadly, it’s almost impossible to find funding for large scale studies of aspirin’s efficacy in preventing cancer because you can buy a bottle of the stuff for a little over a buck, and what multi-billion dollar pharmaceutical company could justify profit margins as low as that?

The distortions of the second model are even more in evidence when it comes to antibiotics. Here is one of the few places where the second model of healthcare is dependent upon the first. As this chilling article by Maryn Mckenna drives home we are in danger of letting the second model lead to the nightmare of a sudden sharp reversal of the health and longevity gains of the last century.

We are only now waking up to the full danger implicit in antibiotic resistance. We’ve so over prescribed these miracle treatments both to ourselves and our poor farms animals who we treat as mere machines and “grow” in hellish sanitary conditions that bacteria have evolved to no longer be treatable with the suite of antibiotics we have, which are now a generation old, or older. If you don’t think this is a big deal, think about what it means to live in a world where a toothache can kill you and surgeries and chemotherapy can no longer be performed. A long winter of antibiotic resistance would just mean that many of our dreams of superlongevity this century would be moot. It would mean many of us might die quite young from common illnesses, or from surgical and treatment procedures that have combined given us the longevity we have now.

Again, the reason we don’t have alternatives to legacy antibiotics is that pharmaceutical companies don’t see any profit in these as opposed to, say Viagra. But the other part of the reason for their failure, is just as interesting. It’s that we have overtreated ourselves because we find the discomfort of being even mildly sick for a few days unbearable. It’s also because we want nature, in this case our farm animals, to function like machines. Mechanical functioning means regularity, predictability, standardization and efficiency and we’ve had to so distort the living conditions, food, and even genetics of the animals we raise that they would not survive without our constant medical interventions, including antibiotics.

There is a great deal of financial incentive to build solutions to human medical problems around interminable treatments rather than once and done cures or something that is done only periodically. Constant consumption and obsolescence guarantees revenue streams.  Not too long ago, Danny Hillis, who I otherwise have the deepest respect for, gave an interview on, among other things, proteomics, which, for my purposes here, essentially means the minute analysis of bodily processes with the purpose of intervening the moment things begin to go wrong- to catch diseases before they cause us to exhibit symptoms. An audience member asked a thought provoking question, which when followed up by the interviewer Alexis Madrigal, seemed to leave the otherwise loquacious Hillis, stumped. How do you draw the line between illness without symptoms and what the body just naturally does? The danger is you might end up turning everyone, including the healthy, into “patients” and “profit centers”.

We already have a world where seemingly healthy people needed to constantly monitor and medicate themselves just to keep themselves alive, where the body seems to be in a state of almost constant, secret revolt. This is the world as diabetics often experience it, and it’s not a pretty one.  What I wonder is if, in a world in which everyone sees themselves as permanently sick- as in the process of dying- and in need of medical intervention to counter this sickness if we will still remember the joy of considering ourselves healthy? This is medicine becoming subsumed under our current model of consumption.   

Everyone, it seems, has woken up to the fact that consumer electronics has the perfect consumption sustaining model. If things quickly grow “old” to the point where they no longer work with everything else you own, or become so rare that one is unable to find replacement parts, then one if forced to upgrade if merely to insure that your stuff still works. Like the automotive industry, healthcare now seems to be embracing technological obsolescence as a road to greater profitability. Insurance companies seem poised to use devices like the Apple watch to sort and monitor customers, but that is likely only the beginning.

Let me give you my nightmare scenario for a world of superlongevity. It’s a world largely bereft of children where our relationship to our bodies has become something like the one we have with our smart phones, where we are constantly faced with the obsolescence of the hardware and the chemicals, nano-machines and genetically engineered organisms under our own skins and in near continuous need of upgrades to keep us alive. It is a world where those too poor to be in the throes of this cycle of upgrades followed by obsolescence followed by further upgrades are considered a burden and disposable in  the same way August Weismann viewed the disabled in his day.  It’s a world where the rich have brought capitalism into the body itself, an individual life preserved because it serves as a perpetual “profit center”.

The other path would be for superlongevity to be pursued along my first model of healthcare focusing its efforts on understanding the genetic underpinnings of aging through looking at miracles such as the bowhead whale which can live for two centuries and gets cancer no more often than we do even though it has trillions more cells than us. It would focus on interventions that were cheap, one time or periodic, and could be spread quickly through populations. This would be a progressive superlongevity.  If successful, rather than bolster, it would bankrupt much of the system built around the second model of healthcare for it would represent a true cure rather than a treatment of many of the diseases that ail us.

Yet even superlongevity pursued to reflect the demands for justice seems to confront a moral dilemma that seems to be at the heart of any superlongevity project. The morally problematic features of superlongevity pursued along the second model of healthcare is that it risks giving long life only to the few. Troublingly, even superlongevity pursued along the first model of healthcare ends up in a similar place, robbing from future generations of both human beings and other lifeforms the possibility of existing, for it is very difficult to see how if a near future generation gains the ability to live indefinitely how this new state could exist side-by-side with the birth of new people or how such a world of many “immortals” of the types of highly consuming creatures we are is compatible with the survival of the diversity of the natural world.

I see no real solution to this dilemma, though perhaps as elsewhere, the limits of nature will provide one for us, that we will discover some bound to the length of human life which is compatible with new people being given the opportunity to be born and experience the sheer joy and wonder of being alive, a bound that would also allow other the other creatures with whom we share our planet to continue to experience these joys and wonders as well. Thankfully, there is probably some distance between current human lifespans and such a bound, and thus, the most important thing we can do for now, is try to ensure that research into superlongevity has the question of sustainable equity serve as its ethical lodestar.

 Image: Memento Mori, South Netherlands, c. 1500-1525, the Thomson collection

Why Europe Shouldn’t Print the Cartoons

The horrendous murders in Paris appear to have ignited a firestorm of defenders of free speech urging us to “print the cartoons”, an understandable, and likely to be unheeded plea, at least by the West’s major newspapers. That is all for the good, for contrary to claims that not re-printing cartoons inflammatory to many Muslims amounts to cowardice, (a claim I do not understand given how many journalists at these institutions have risked or lost their lives covering conflicts) printing them in seeming defiant defense of free speech is exactly what the terrorists wish we would do.

Islamists need for there to be a violent confrontation between their version of the world and the one born in the West, they need for Muslim minorities in Western countries to feel besieged, their religion disparaged, their value as human beings reduced to that of a threatening other.

France’s population of 5 million Muslims is perhaps the most secular group of Muslims in the world.  The overwhelming majority aren’t looking for a Caliphate they’re just looking for a job. They are not, as a best selling recent work of French speculative fiction, Soumission (Submission) depicts, likely to create a future Islamized France.

Rather, a handful of crazies might have managed to make a European nightmare of 21st century Ottomans at the gates of Vienna seem real, but only if Europeans let it.

It’s a nightmare that won’t benefit the Islamists much, but could greatly benefit the European right which had already identified Europe’s Muslim minority as the scapegoat for the continent’s decline. Neo-fascist parties such as Marie Le Pen’s National Front in France itself, or Nigel Farage’s UKIP in the UK. Europe is going through a very troubling identity crisis where even countries that should surely know better, namely Germany, have seen the rise of things like “Pegida” — Patriotic Europeans Against the Islamization of the West- which bring thousands to the streets in anti-immigrant, anti-Muslim marches. Islamists and the right need each other like the communists and Nazis in order to make fanatics out of the rest of us. I sincerely hope that neither the Muslims nor the non- Muslims of Europe will let them do it.