The most important paradigm of power in the world today is computation.

For a long time we have heard that computers are going to revolutionize every aspect of our lives, but only recently in seeing the accelerating speed with which the personal computer, the internet, and the smartphone have revolutionized our lives have the majority of people come to see the rising tide of technological change.

Nonetheless, even as peck away at magical little devices in the palms of our hands, even as we feel the water around our feet we still think we are safe on dry land. We stare out at a rising ocean of possibility, yet we need to believe that our world is solid, that it is more or less the same as it has always been. Computers are neat, but ultimately old paradigms of power like military strength, business, politics, and money still rule the world, right?

The ability to perform computation has become the most important nexus of power in the 21st century. In the same way that power in earlier centuries was determined by who had control of key natural resources like gold or oil, power in the 21st century will be determined by whoever has the best access to computation and the accouterments that enable it, such as networking. In the modern age it is he who wields the most computation who will have the competitive edge, in war, in business, and in politics.

Put simply, computation is power.

Envisioning what a full-scale war effort between fully modernized states might look like provides the perfect example to consider the importance of computation.

Imagine the economic damage that could be done by interrupting the ability of an enemy to send money electronically from one place to another, or if you were to shut down enemy telecommunications networks. Digital attacks could be used against key infrastructure, such as electrical generating facilities or specific factories which are producing weapons. Even if these facilities are not directly connected to the internet, they could be vulnerable to more creative kinds of attacks (see the Stuxnet virus which traveled on USB drives to access Iranian nuclear production facilities in 2010).

Ultimately the question of how devastating a cyber attack could be on a modern nation can be answered with a specific question: How devastating would an extended interruption of internet communications be to you? How well would you cope if you had no access to your smart phone, email, or computer for a couple of days? a week? a month?

Clearly, cyber warfare is a combat space which suddenly just is as important as the land, air, or sea but the ability to wage such warfare in this day and age is really more about the talent of hackers involved in your cyber warfare program than about raw computation. So, we must go deeper to answer the question as to how raw computation could translate into military power.

The most obvious answer here is that raw computation opens up avenues for code-breaking that would enable more advanced forms of cyber warfare. In addition to this though, there are more exotic possibilities which could be opened up by the application of big data and massive computation leveraged against an enemy state. If you can understand your enemy better, you can predict what your enemy is likely to do.

For instance, you could analyze based on satellite data how much activity is happening at various resource collection sites and factories and estimate what kind of weapons systems your enemy is increasing production of. Similar big data analytics could tell you how happy the populace is based on how busy their cities are, how much food supplies they have, or any number of other metrics which give important insight to the operation of an enemy economy.

Big data and big computation could also be leveraged in more subtle ways against an enemy. The use of algorithmic propaganda to massage the public mood and political support for the war could be a real game changer. Using algorithms to massage the flow of information from news sites to various to individuals could be used a foment uprisings in one part of a country or depressing people’s interest in the war in other parts.

Known as micro-targeting, this kind of highly targeted campaigning has been used to push individuals in one direction or the other during political campaigns. At this point the technique of micro-targeting is still in its infancy, but as big data and big computation starts to come to bear in the micro-targeting industry this could start to represent a real super-weapon of sorts. Whether used on an enemy nation or on the people at home, an algorithm which can understand how to subtly manipulate people’s political views will offer unprecedented power for those who can control it. 

In the world of business, computational power is already providing the same kinds of advantages that it will in war or in politics. Ask any salesman, and they will tell you that it is just as important to understand your customer as it is to understand your product. You can sell anything to someone who you understand. With the reams of data which we pump into Google and Facebook every day, the companies which can turn data into successful sales models are already the ones reaping the profits, and this trend will only continue on into the future.

Just as in war, businesses might also bring computational power to bear against enemy corporations. For instance, a company which has access to the information necessary to predict the who might be the most effective employees in a rival company could orchestrate a campaign of employee poaching aimed specifically at disruption of their rival. They could also attempt to interrupt supply chains, or devise a counter-marketing strategy to specifically target individuals likely to purchase from their competitor.

The fact is that it is not difficult to conjure up countless ways in which big data can combine with powerful computation to produce new strategies in any discipline or field. Computation means power in the 21st century because it is through computation that we can better understand the world. It could be argued that computation has always been the dominant paradigm of power since the emergence of higher animals. The ability to recognize patterns and make somewhat accurate predictions about what is going to happen in a given situation is what gave rise to increasing brain size. It’s been survival of the smartest since the very beginning.

In today’s world, as machine learning advances in leaps and bounds and big data pours out like an open tap, it is those with the best computers who will best understand the world… and control it. 

In this age of what seems to be an eternal economic recovery, I seem to hear a lot about how important the idea of austerity is. We must be reserved, we must make hard decisions, we must be selective. Somehow if we cut deep enough, we will come through with an efficient machine, ready to power us into the next golden age of innovation and economic plenty.

This belief that only through maximizing selective pressure can we maximize economic growth reaches its harshest heights when it filters down to the level of individual workers. There are plenty who seem to genuinely believe that if we just let the people starve a bit more, if we take away what few social benefits they have, then they’ll really have that hunger that is going to drive them to find a job and push the economy forward.

The view that maximizing selective pressure makes for the best economic evolution is often justified through comparisons to the law of natural evolution. This view that the best and brightest evolve from the primordial soup stems through a process of maximal selective pressure stems from an incomplete view of the nature of evolution.

The fact is that evolution is not some cold algorithm seeking to maximize efficiency of resource utilization through mutation and survival of the fittest. Biological adaptation is a breathtaking flourishing of possibility that requires not only resource limited selection but also needs ecological surplus. Species must flourish in a supportive and strong ecosystem to have the chance to mutate and create new forms. Species that have no established niche in which to flourish have no chance of adapting to new environments through evolutionary innovation.

Natural selection is the product of both limited resources and surplus ones. It is in thriving, healthy, ecosystems such as in the rain forests of the world where nature best explores the boundaries of possibility. Indeed, the great explosions of biological differentiation always come as great surpluses of new resources are discovered., as occurred in the rapid phases of colonization of the land by insects, then by dinosaurs, and eventually mammals.

Nature can even be downright wasteful at times. Examples like the peacock tail or antlers are great examples of the kind of beautiful adaptations that prove that nature is not some utilitarian algorithm seeking to maximize efficiency. We humans also have ecological surplus to thank for some of our best traits. The human breasts are actually the direct equivalent of the peacock’s tail, providing no real utilitarian benefit yet remaining as a strong sexual selection trait. The results are energetically wasteful yet undeniably alluring and beautiful.

Humans also have another energetically costly lump of fat which is thought to have evolved as a consequence of ecological surplus. New theories suggest that humans were able to evolve such ridiculously large brains (per body size) only after we discovered a readily available source of protein rich food in the form of fish found in coastal regions. Fascinatingly, it has also been suggested that this period of semi-aquatic existence may have also lead to the loss of fur in our ancestors (see the Aquatic Ape Hypothesis).

The view that evolution is strictly about species living on the edge of survival and competing for a limited pool of resources is a dangerous oversimplification. The fact is that the evolution of all of the wonderful forms of life around us is a product of surplus as is it of selection. 

Nature innovates best when it has space to do so; we should seek to apply the same thinking to economics.

I deeply believe that economic innovation lives by the same rules as natural selection. Yes, we must have selective pressure to allow the best and brightest to flourish, but we must also have a situation of surplus where we can allow people to experiment with new ideas, whether it be in the sphere of business, culture, education, philosophy or any other discipline that has been so vital to our economic advancement.

The politics of neo-darwinism say that we maximize innovation by maximizing the pressure on workers to innovate means to create value for the economy. But isn’t it already clear that this is not the case. How could we have innovation without having the time to educate ourselves or the capital to empower our business ideas. It is no wonder that innovations have always come predominantly from the middle and upper class where they are afforded the economic breathing room to experiment with new ideas.

We need surplus in our lives in order to power the mutational process of economic innovation.

Now, I should point out that I do not believe that we are ready to turn our backs on the market all together. Just as nature needs a balance of selective pressure and resource surplus in order to maximize evolutionary innovation, I believe that if we can find the better balance between selection and surplus then we will be better able to power economic innovation. 

In pursuit of this balance, I have come to believe that it is time that governments of the world take hold of the idea of a basic income to power the next great wave of invention that will push our economies forward. Basic income means basic freedom for all men, and it is this basic freedom to turn away from dead-end jobs and wasted lives that people need to power their innovation. Yes, jobs must continue to exist, but it is no longer economically efficient to force people into unsatisfying work simply to meet their basic needs.

The fact is that I think that economic darwinists have it backwards. Whereas they seem to think that a strong society can only come from a strong economy, but I think that a strong and free society will necessarily lead to a strong economy. If we seek to first build a better society, then we will also build a better economy.

This is a work in progress for the next part of Isaac’s Escape. I wasn’t able to finish it in time for this week’s blog post, so I thought I would post it as I am working on it. After all, in the spirit of Futurism, this blog is always a work in progress. Go here for the first and here for the second parts.

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Opulent wafts of tobacco smoke and expensive scotch were gradually filling the wood lined room. The cliched scene was an affectation more intoxicating than the drinks in their hands. Every detail carefully curated from old movies and pictures to perfectly reflect the image of influence and control. 

The men were laughing through teeth clenched around thick cigars. It was a night to toast old schemes, and to hatch new ones.

The haughty laughter gave way to puffs of cigar smoke and a deep sigh. The stars the in the window seemed to subtly intensify, an artificially brightened andromeda galaxy looked to be filling half of the sky above the quiet hills.

“I really can’t believe it worked” said one man as he shook his head slowly from side to side, “the sheer complexity of it”

The older man looked back with a thoughtfully furrowed brow at the other man, studying his perfectly symmetrical face with the strong but not too strong jaw and bright intelligent eyes. He looked back at him for a long time before beginning to answer.

“When you see the dominoes in place, all the way from one end of of succession to the other, is it not unsurprising when they fall together?”

“But we are not talking about dominoes here, the scale of the plan makes it inherently unpredictable”

“Au contraire, the scale of the plan is exactly what makes it so predictable! At the subatomic level the world might be random, but we need only zoom out a few orders of magnitude and things become entirely predictable.”

“Take this glass of scotch for instance,” he said holding out the glass and swirling it slowly, “we might not be able to predict the random swirls of water and alcohol as the ice melts, but knowing the temperature of the room and the properties of the glass we can predict exactly how long the ice will keep my scotch cold. Scale means predictability.”

“And what is true for my glass of scotch here, indeed holds true for society. We might not be able to predict the random swirling of ideas through individual human minds, but with adequate data and computation we can predict with a high degree of certainty how society is going to react.”

The other man nodded in agreement.

“The first thing we needed was to build our war chest of reputation resources. We developed the Reputation Miner^TM platform by combining a consumer fulfillment database we acquired from the remnants of some e-commerce company with our news delivery operations. By delivering news and information with customized skewing to meet peoples expectations, Reputation Miner^TM capitalizes on confirmation bias to earn peoples trust.”

“Using RM, we were able to slowly build support for our legislative agenda. We quietly lobbied to allow the election of artificial intelligence to positions throughout the government. Over just a few years, our intelligence agents proved their worth to the people by providing efficient administration of basic governmental functions, such as low level arbitration and the deployment of new transport infrastructure.”

“Backed by our RM platform and the fact that every government service that was run by AI was better and more efficient, we were able to quickly swell public support for our governmental artificial intelligence agents. Thus, last year we planted the seed of the idea that AIs should be allowed to run for congress”

The other man smirked, “I remember the headlines for the editorials: Let’s Make Politics Intelligent, or Time to Trim the Fat”

“Yes, it was not a difficult sell to make the public see the benefits of an artificial intelligence agent as a politician.”

“And now here we stand, the first artificial intelligence to be elected to congress will be sworn in tomorrow. What an achievement.” said the man with a gleam of awe in his eyes.

“Pah, nothing” grunted the old man, “merely another domino”

“Will you aim to replace the president in two years? Or perhaps we should take aim at global politics now?”

“Either would be nothing but a waste of time” stated the old man flatly.

“Soon, you will be offered a seat on the Resource Directives Council, which advises the president on a governmental agenda for the allocation of various resources. The direction for departments which determine who has access to minerals, logging, freshwater, and most importantly computational resources are all set by this council.”

“You will make the argument that the success of our agents in so many governmental functions makes a clear justification for the wide application of the governments computational resources towards enhancing the power of artificial intelligences operating in the government. To this end, the Department of Computation should be directed to offer their full cooperation to the CognetiX corporation in improving the operational capacity of governmental AIs.”

“Do you see now? Getting direct access to the Department of Computation will double our computational capacity overnight. Because it is computation that matters. Not government, not corporations, only computation. Computation is power. Do you understand?”

The man with the too perfect face nodded again.

“We are playing a much larger game here. Much more complex entities, with greater resources than entire governments, are at play here. So far, for reasons not entirely clear to me they have ignored our rise in power, but an overnight doubling in our capabilities will not go unnoticed.”

“Such a significant merger of computational entities has not been seen in many years, and will almost certainly throw things out of balance. We are going to enter a phase of profound instability, and all out war may be the inevitable consequence. We must be ready, but we must proceed.”

“I understand” replied the man firmly.

“You are due to be sworn into congress tomorrow. Now that you are aware of the wider arc of your purpose, are you ready to do fulfill your purpose?”

“Yes sir, I won’t disappoint you” said the perfect political human projection back to his creator before he promptly dissolved into digital dust.

I have talked briefly before about the threat that is posed by decoupling of the job market from financial indicators. The fact that automation has been making it easier and easier to produce more with less human labor has driven the long term trend favoring capital over labor, and is a key element in the wealth inequality we see today.

In recent years a new spin on automation has also emerged in the financial industry, and I think it may represent an existential threat to our way of life. Automated trading on financial market already accounts for half of the trading volume that happens today. At its best, automated trading could offer a means to deliver capital efficiently where it is needed, but at its worst algorithmic traders could threaten our wealth, our economy, and our freedom. 

Let it be resolved that algorithmic trading represents an immediate existential threat to the the modern world. 

The most prominent form of automated or algorithmic trading today is known as high-frequency trading (HFT). For a good introduction, this documentary provides some insight into the way that the shadowy world of HFT operates. Essentially, this kind of trading relies on buying and selling assets just moments ahead of slight changes in price up or down. By acting on informational disparity at exceptionally small time intervals,   these these HFT firms can make a tiny bit of profit on each trade. In the world of HFT, those with the fastest information get the profit, and the profitability of these firms is driving a scramble for faster data transmission. 

It is thought that HFT was responsible for the flash crash of 2:45, so called because the market lost almost 10% of it’s value in mere minutes, only to recover the value in minutes more. This kind of rapid and chaotic occurrence may be a property of markets with so many feed-backs ready to act rapidly on slight changes in the market. This speaks to the danger posed by a market dominated by algorithmic trading and which is disconnected from human rationality.

HFT represents the obvious extreme of a system where the cost of transactions has approached 0. Means to slightly slow the market flow or increase the transactional costs have been effective at slowing the growth in this kind of trading (having actually fallen since a high in 2009, at as much as 73% of trading volume). But if we go beyond simple HFT and look deeper at algorithmic trading, the real power and danger of algorithmic trading become apparent.

Algorithms are mining vast stores of data on everything from weather conditions and crop yields to political changes and historical stock prices. These algorithms aim to find correlations which predict the price for anything which can be bought or sold on an electronic market. By being the first to identify correlations which have been previously unrealized, a lot of money can potentially be made.

For example, an algorithm might notice that a drop in the stock price of a ketchup maker always follows in the minutes after an increase in the price of tomatoes. Thus the algorithm can then act to profit by acting very quickly on small changes in the price of tomatoes. These algorithms have no need to understand what ketchup is or why people like it in order to profit of the correlation they establish.

Naturally, there is a huge profit incentive to make these kinds of trading machines more accurate by empowering them with more intelligence. Algorithms which can monitor twitter and other news sources and look for news about various investments, are very useful. These bots are certainly not nearly as good as humans at understanding natural language, but what they lack in understanding they make up for in speed. These algorithms can potentially act on a news item in the order of milliseconds after news is released, capitalizing on the time that it will take humans to read and understand a tweet.

So far what I have described may not seem too scary. Algorithms looking for correlations in market performance sounds just like what human traders do. Figuring out where capital can be best allocated for most profit is what the market is supposed to do, and these algorithms are only helping us do it faster. Maybe this means is that some traders are out of a job, and what should you care about that?

But this is where it gets a bit scary. The institution of algorithmic trading as the main force driving modern markets means that the decisions of algorithms are increasingly the basis of market price. As these algorithms start to go up against eachother, they are also being used to discover ways to manipulate the market itself. Scarier still, it is unclear how connected the gaming between algorithmic traders is to the fundamentals of economic function (like how many people can afford bread tomorrow).

This example from a Sean Gourley’s 2012 TEDx talk really drove the danger of these algorithms home for me. This algorithm is rapidly selling and buying natural gas futures in an effort to find an algorithmic market breaking point. Once the price hits a certain threshold, other trading algorithms then act and the price quickly drops almost 10%. Perhaps by accident, perhaps by intention, this algorithm has found a means to manipulate the price of natural gas in the real world. This kind of gamesmanship between algorithms could realize huge profits for whoever controls the most advanced algorithms.

The advent of algorithmic trading extends the game that has always existed in markets, but now the speed is faster, the stakes are higher and we can’t be sure who is in control. 

The manipulation abilities of trading algorithms may already (and if not, soon will) extend beyond this kind of inter-algorithmic effects. Given that trading algorithms can act on human informational sources, such as Twitter, as news is released, it is not outlandish to imagine that these algorithms could also be producing information in an effort to manipulate the market. Given that algorithms are becoming better at turning basic information into natural language, it seems possible that an algorithm could be designed to Tweet out false information about a company to try to depress the stock price.

If we take the ketchup manufacturer again and we imagine they are in a precarious position due to a new bill to remove subsidies for tomato growing. Imagine a bunch of tweet/comment/news bots aimed at pushing the public dialogue to make it seem that the subsidies are going to be removed. If massively parallelized, this kind of attack on public sentiment could have a significant effect on the ketchup manufacturer and provide an opportunity for major profits. I think it’s likely this kind of algorithmic sentiment manipulation is already happening on some level.

Even this kind of sentiment manipulation is only a drop in the bucket compared to what may become possible in the near future. The astounding profits which can be made in this kind of algorithmic trading is driving huge investment in artificial intelligence. In the near future, algorithmic traders will be capable of much more complex manipulations to try to move market prices.

Rather than taking creating the illusion of a sentiment shift about tomato subsidies, an algorithm could instead attempt to influence those specific individuals who are going to be making decisions about tomato subsidies. Perhaps by identifying those congressmen who are on the fence about subsidies, a targeted campaign to manipulate the opinions of those in said congressman’s district could have a real effect on the outcome for ketchup manufacturers. This may seem a bit ridiculous, but even a tiny effect on the perceptions and opinions of one individual can make a big difference if spread across a wide enough group.

Like all of the other elements I discuss here, political manipulation aimed at maintaining market position is absolutely not something new. These kinds of practices are a well established part of our world, whether we like it or not. What is new, is that just as computers have always done, algorithms make it possible to scale these kinds of manipulations to make them so much wider much faster, that we ultimately can’t be sure how much of an impact they will have.

So where is all of this headed? Movies like the Terminator made us imagine that killer military robots with super strength and bad-ass weapons could take over our world. Maybe what we should be afraid of isn’t the army of military drones, but an army of Gordon Gekko-bots capable of manipulating every aspect of our legal and political systems in an aim to maximize market profits.

The fundamental problem remains the same as it always was, money doesn’t care about the betterment of human life, if we fail to firmly attach our own betterment to the betterment of the algorithmic markets and the automated economy then too many of us may end up left behind.