Your money or your ‘likes’

Facebook recently did a brave thing. In its Initial Public Offering (IPO), it offered shares in itself publicly on a stock market. This allows people it has no control over to assess the value of the company for themselves, which comes in part from estimates of future earnings. Facebook’s earnings, of course, come from the narrowly-targeted advertising that it plants under your nose: because you have shared information about yourself through the site, it knows what you do, where you do it, with whom you do it, and what you like about it. Selling that information is an intrinsic part of its business, as with Google and so many other online businesses.

Last year facebook made over $1billion. The genius of many tech companies today is in monetising non-financial transactions. (picture: CNN Money)

Unless you’ve been living under a rock for the past five years, you’ll have noticed the explosion in the monetisation of Big Data. This has a lot of implications for healthcare, manufacturing and retail, but for the internet it means that online services can be ‘free’ to the user, with the only ‘subscription charge’ being the very data that you give the service in the course of using it. In theory – and this is what Facebook, Google et al. would prefer you to think – you are therefore getting a great service at minimal cost or inconvenience to yourself, while less space on the web page needs to be given to advertising because you’re more likely to ‘convert‘. Advertising works better, people get to connect online. Win-win.

But it is precisely this ‘usage’ of people’s personal data that gets under people’s skin. The lack of anything the user understands as explicit permission, and the (ideally) uncanny relevance of the advertising they see, spooks website users and, at worst, makes them feel violated: ‘how dare the company use this information that I have given them in good faith? I feel like I’m being watched everywhere I go!’

In my opinion, this viewpoint is both naïve and pessimistic. It’s defeatist. It fits a world view in which the consumer is ruthlessly exploited and forever dancing to the tune of the clever corporates, whose ‘big data’ statistics see through the irrationalities of human cognition and sociability and can trap you in their web without you ever knowing.

I’d like to offer a different framework for thinking about this, which I feel is more helpful, proactive and optimistic.

First of all, realise that it’s not an actual human being reading your data or your emails or your searches. It’s a computer that has been programmed with some clever stats and algorithms that improve the more they get used – this is called machine learning.

Second, and more importantly, accept that you don’t ever get something for nothing. Anything that says it’s ‘free’ is lying about it, even if implicitly, or unknowingly. This fact is shocking, perhaps. In the nicest possible way: you need to get over this.

Every social interaction is essentially a transaction. Sometimes – only sometimes – we use money. Money is useful to me because it allows the work I do at my desk in the office to be exchanged for other things like coffee, food and rent. But I also think I tend to only maintain relationships that are helpful, nourishing or inspirational to me, and that I feel I can contribute to in some way. It’s a kind of two-way deal, partly informed by totally irrational but very real and wonderful things like personal affinity or love. If the deal falls down on either side, if one party stops wanting or being able to provide what the other side needs, the relationship won’t keep going for long.

Back to social media, then: if we acknowledge that every kind of interaction is a transaction of some kind, then you’ll only be happy to proceed if you can see or justifiably expect a net benefit for yourself.*

(And yes, this does leaves room for a social conscience. All relationships flow both ways.)

Maybe the question then is ‘how much are your data worth’? …but as this is a personal question, and I’m also writing this late at night, I’m not going to go into it here. The main point is that you are in control of the data you put onto Facebook. Sure, it is a profit-making enterprise so it cannot be said to operate exclusively for the public good, but it can’t make a profit if it has no users. You need to know that when you use ‘free’ website services you are entering into some kind of transaction, even though you aren’t paying money. You need to be happy that it’s a good deal for you, and if not you need to know what to do about it.

Humans are creatures of bounded rationality, which means we have lots of systematic flaws, biases and irrational behaviours. I for one always have awkward moments where I realise we’ve been working against our own interests. We can find ourselves spending hours on Facebook, our attention spans shortening and our personal data haemmoraged into the ether. But if we can train our own rationality and good sense, we can spot when we’re being exploited. We can turn around and protest. We can create ambitions for our own futures. We are not sheep. We are collaborative, planning, physical creatures driven by curiosity and delight. That’s exactly why Facebook is popular.

*there’s a name for this kind of ‘transactional’ world view: more or less, it’s called economics.

Open Information vs. Big Data

Freedom of speech and freedom of information are enormously important things to debate and defend. It is clear that papers published in the course of government-funded scientific research should be available to the public by default, for example, or that crime and school statistics should be accessible. (You can read some of the arguments for and against this viewpoint on the Guardian’s FoI website.)

Having established that freedom of information is a Good Thing, what about freedom of data?

Maybe I should backtrack here, and ask: what is data, as opposed to information? (*ahem* more properly, what are data – the word is from the Latin datum  ‘thing that has been given’, plural data – so many people use the plural in English. Back to the point…)

Data are recorded results, the outcome from some measurement or calculation. Each point on a graph is a datum, but one point doesn’t really tell you much about the thing you’re recording. Even a whole bunch of points aren’t particularly helpful. But if you take the scattered points and use them to show a relationship between age and height, say – if you do some work to the data to make sense of it – you can turn it into information.

Information is interpreted data. It is communicable and ideally useful knowledge, an insight into the behaviour of a system.

Since the 1980s, more and more data collection has been automated, and data sets have gotten exponentially bigger – we’re not talking megabytes here, but terabytes, exabytes, zettabytes – that become hard to deal with by conventional database means. These data come from all kinds of things – new scientific experiments like CERN, simulations, Tesco clubcards, iPhone logs, your web browser – almost anything using technology more sophisticated than a microwave, and in a few years, probably that too.

According to Wikipedia, we’re collectively creating about 2.5 quintillion bytes of data every day (1 quintillion = 1000 trillion) and by 2014 that will have doubled. We’re in the realm of ‘big data’ here – data sets that are so big they take too long to do even simple operations using conventional software. They are general hard to process, and even harder to visualise (despite a few great examples of such).

How can we reconcile this fact of cumbersome and ever-growing data sets with the principle of promoting and defending freedom of information? Should freedom of information apply to the data, the information or both?

Outside the USA and Canada, Facebook users are registered with Facebook Ireland Ltd. and Irish law provides for the right to access your own personal information that any online business has been collecting on you. In 2011 an Austrian student named Max Schrems submitted such a request and, after a lengthy bureaucratic process, received a document 1200 pages long. 1200!

Whether or not the 1200 pages on Max Schrems’s Facebook activity were all strictly necessary, and whether or not Facebook should have been keeping all those supposedly deleted messages and lists of de-friended people, I strongly doubt that a cumbersome 100Mb PDF was in a form that Schrems could easily process into useful information. On the contrary, this sounds like a data deluge: a wall of pure, near-raw data whose volume makes it all but impenetrable.

Part of the reason for the relentless detail is legal in nature: it could not then be accused of under-complying. But if the unwieldy format is specified by law, the laws need to keep up with what’s in the public interest. The usability of data is a huge issue here, and is getting more important the more data sets grow.

The basic problem with Freedom of Information requests is as follows:

1. Citizen files Freedom of Information request with organisation (public or private) possibly with a specific query, but relating to large dataset.
2. If at all possible, organisation hides information relevant to request inside massive data set. Organisation therefore complies with the letter of the law.
3. Citizen cannot process data set and likely gives up; information remains useless.

Drowning in data?

To me it seems like it should be in many companies’ interests to be as open and transparent as it can be when dealing with requests for personal data. I don’t care what Google does with the data I continually feed it, as a rule, but that’s partly because I trust it to be honest and tell me what it’s using it all for. I also trust it (perhaps in error) to lay off using my data if I ask it to.

Facebook, on the other hand, has followed a different path, but maybe this difference is in the fragility of the customer base: you can’t leave unless all your friends leave too, but stopping using Google is a relatively easy individual choice – on the face of it, anyway. Regardless, Google hasn’t made a habit of pissing off its users like Facebook can.

So in some cases it is in the interests of the data user (eg. Google) to be transparent with how they use data. Those cases will no doubt take care of themselves – though they may need some extra encouragement to be accountable to the public interest, alongside what is essentially also a branding exercise.

What about the cases where transparency is in the public interest, but not in the interest of those keeping and using the data? The resistance to transparency could be nefarious or it could just be lazy. In those cases, there is an increasing temptation – and ability – to use the realities of Big Data to obscure useful information.

For example, as Fred Pearce asks, should scientists always disclose their raw data along with their findings? Arguably yes, especially if they’re publicly funded – but how far should those scientists go to help requesters actually deal with it? Is a 5 terabyte data set of climate records worth anything without knowing how to interpret it? There is much about the processing methodology that scientists would prefer to keep confidential, at least until publication. Having released the data, these scientists will no doubt be hassled with hundreds of requests for help interpreting their monster data sets. How much time and effort is all this really worth?

There really is a problem here. Big Data means that organisations have the ability and the incentive to collect and use vast amounts of data on people. They can use this, with a sprinkling of multivariate statistical inference, to work out what sort of cheese you might buy next time you go to Tesco, whether you’re likely to click on an ad about breast enlargements, and how likely you are to contract lung cancer before you’re 50. Yet when you ask what they have on you, they only have to tell you about the data, which may run to 1200 pages or more and be completely indigestible. The actual information is still proprietary and you’re none the wiser.

What can someone without a degree in statistics and computer science do?

Direct democracy at the edge of chaos

Everybody’s heard of chaos theory but few people really know what it is. Normally we use ‘chaos’ interchangeably with ‘disorder’: this is misleading. Chaos is not about randomness. It’s much more to do with the unpredictability of order, and how transitions between ‘ordered’ states happen.

The precise definition of a chaotic system requires degree-level mathematics to really understand, but this will do for now: it’s a dynamical (changing) system whose behaviour is highly sensitive to initial conditions (the ‘butterfly effect’). These systems only need to satisfy a few mathematical conditions – beyond this, they can be as simple or as complex as you like. Suffice to say that a huge number of real systems fall into this category.

Chaos theory has been successfully and usefully applied to explain the development of leopards’ spots to Jupiter’s big red spot, crime statistics, lines of desire, the weather and more.

Emergence is a fancy word for self-organisation. If we change the starting variables of a chaotic system, we see a variety of behaviours. For some values, the system is entirely random and disordered. For others, it settles into an uncanny regularity. By changing the system’s variables to the point just on the edge of chaos, the system achieves maximum complexity.

This kind of emergent complexity is dependent on the rules of the system and the starting conditions, but otherwise is entirely self-assembled. It happens from the bottom up.

Think of a flock of birds. Consider the way the whole flock can move as one, and compare it to the way an orchestra follows its conductor. Both are groups of individuals that perform stunning feats of synchronised agility, but the way they achieve their coordination is quite different. The flock coordinates its movements from the bottom up – each bird acts individually, instinctively flying in the right direction and distance from the others so that the entire flock moves as one, without its members getting left behind or crashing into one another.

An orchestra does the opposite: the conductor is coordinating the group’s behaviour from the top down. The self-organisation of the flock is a matter of mutual coordination and cooperation. The orchestra in this case is a matter of control. (Arguably, a good orchestra or team is more than the sum of its parts, and becomes so when its members start working together and predicting each other’s movements instinctively much like the flock of birds.)

Part of a cellular metobolic network. The blobs represent molecules; the lines are interactions. The circle at the bottom is the Krebs cycle. This kind of complexity took millions of years to emerge, and sustains itself using the energy from the sun.

Emergence is everywhere, from the spontaneous alignment of iron atoms in a magnet, to the generation of consciousness by the cells in your brain, to birds in a flock, to the coalescence of stars to form a galaxy. Life itself is a form of spontaneous complexity, that started when a group of relatively simple molecules started making copies of themselves. Emergence is the formation of a complex and often regular pattern out of a collection of simple components governed by no more than a few simple rules.

Those ‘simple rules’ come down to thermodynamics, and specifically the tendency of the energy in the universe to become more disordered over time. The second law of thermodynamics states that ‘the entropy of a closed system always increases’. The universe is the biggest closed system there is, so on average the energy in the universe must always become more dissipated and diffuse.

So on the one hand the universe is always becoming more disordered, its energy dissipated and spread more thinly, on average. On the other hand, matter – the stuff of the universe – finds itself being arranged into ever more chaotic and complex shapes and systems. The processes of life exist because they are good at dissipating energy – and the fact of evolution means that they are continually being tested against circumstances and iteratively improved.

Where does human agency and ‘free will’ fit into this?

Unlike most of nature, humans are creative, tool-using, self-aware beings that can communicate complex ideas and create strategies to influence the future. As a species, humans’ wit is our main means of adaptation, but while we are a resourceful and highly adaptable species the fact remains that we are part of natural processes.

Greed: to be taken in moderation.

One prevailing view that collective needs are best served by individual self-interest. In the words of Gordon Gekko: “greed is good”. By this dogma, the only really efficient form of resource allocation is a world where each person pursues their own needs and wants first and foremost. Nobody can know a person’s needs better than they themselves, and any distribution of resources by someone else on their behalf is wasteful by that very fact.

This philosophy is easy to grasp and easy to follow, which explains its popularity. What is often overlooked – and what research is increasingly finding ways to demonstrate – is that empathy, sympathy, compassion and cooperation are very often in our longer-term self-interest.

But compassionate behaviours are emergent in society already. Murder could in many ways be a selfish act, but most humans just know it’s wrong without thinking because it’s a deeply ingrained social rule. Even if they do think about it they’d realise any society that revelled in the supposed joys of fratricide would quickly erase itself from the human gene pool.

It’s easy to see the direct benefit to yourself of being selfish, but for selfless acts the benefit is less clear. We have maxims like the Golden Rule and ‘what goes around comes around’ to remind us that selflessness is sometimes in our best interests. But we humans are bad at working out the wider consequences of our actions.

Many issues – particularly those with global consequences – cannot be resolved by pursuing individual or national self-interest, but only with mutual cooperation. This cooperation can only happen if people realise why they need to do it for themselves, which in turn relies heavily on encouraging principles of transparency, free speech and feedback.

A British consumer boycott on slave-grown sugar - an important Imperial cash-cow - was part of the campaign that succeeded in banning the slave trade in 1807

The passing of the Slave Trade Act in 1807 was, you could say, a geopolitically selfless and counterproductive thing for Britain to do. France and the USA still had slave plantations and Britain was denying itself a major source of revenue when it still had wars to fight. I’m simplifying all this hugely for the sake of argument, but in passing the bill, information feedback and consumer action did play an important part.

Anti-slavery campaigners drew a line of consequence – and therefore responsibility – between consumers’ actions and their effects. An appreciation of the immorality and cruelty of slavery led many in England to choose not to buy Jamaican sugar, rum and coffee. Hey presto: consumer action campaigns, like today’s Fairtrade movement.

Information feedback is the linking of actions to effects back to actions, and has for a long time been a missing ingredient in globalisation. Over the twentieth century it became more and more common for actions to be dissociated from consequences geographically. Future climate change caused by present carbon emissions is an example of a similar dissociation in time. This dissociative trend – a kind of cultural denial – is being broken thanks to mass media and the Internet.

Unilever is one of many companies now using direct consumer feedback, a technique that has taken off thanks to social media. Might this be adapted by governments?

One of the Internet’s key functions, now and in the future, is as one big information feedback system. Corporations are already interacting with their customers on matters both trivial and consequential – from details of product design to corporate social responsibility. Governments are not far behind. The strategic reasons these two types of organisation have for interacting with their stakeholders are vastly different, but it is interesting to see the feedback loop closing.

Direct democracy anyone?

Projection, from Art to Advertising

-the consumer’s way in-

Part of the reason art from about 1400 onwards can be so impressive and fun to experience is because it developed many of the techniques used in modern advertising. The point of the work is often to communicate a specific feeling, idea or lesson (usually religious in nature, but definitely not always). To do this, the artist tries to make the viewer empathise with the characters. To do this, you can try to make them look realistic, but it may be even more effective to make the characters look like the same sort of people as the viewers. This is why Caravaggio depicted his biblical stories acted out by southern European people in 1600s clothing – this is the equivalent of having Jesus and his gang of apostles in hoodies. This is also why Jesus is white: because the audiences of the paintings were too. They were far more likely to empathise with a white man dying for you, a white Italian/French person, when in reality Jesus would have looked to them quite terrifying, more like one of the Sultan’s Mosalmen camped outside the walls of Byzantium.

Today, advertisers use the same trick. There’s a character who you empathise with. They’re in your situation. They buy a product, it makes them happy and complete – it would do the same for you too.

It’s also a bit like that pivotal moment in Roald Dahl’s BFG, or to take a less obscure example, Inception. Once you realise that part of the artificial dream is true (the person in the advert is like you / there is a girl called Sophie sitting on your windowsill / your father is an emotionally distant businessman on his deathbed) then you will be prepared to believe that it’s all true (that you need to buy the product / send the army to attack the bad giants / dissolve your father’s business).

In order to get the advert over and done with in today’s vanishingly small attention spans, while maximising its persuasive power, advertisers need to deploy the full range of clever details and hooks to help you ‘identify with’ their character.

By targeting the ‘majority’ 80% or so of its potential market, advertisers and politicians can overlook, or at worst exclude, the ‘dissimilar’, hard-to-define, diverse 20%. This means that if you’re not included in the narrative of the advertising or the nation, you have a problem. You might follow your natural human inclination to be a part of the ‘in’ group, and conform to the narrative, fitting yourself in somehow – if you’re a gay man in a homophobic society you might marry a woman and suppress your other sexual desires, for example. You choose to trade the advantages of being ‘you’ for the advantages of being accepted and supported by society.

Instead of attempting to conform with the majority you may disengage, or resist. When this happens to enough people, and when they can talk to each other and organise, a new minority group will crystallise. This minority ‘community’ has its own norms and will probably be just as exclusionary to its own ‘minority-minorities’.

My point here is that there will always be minorities as long as there are social narratives, because (even though the most successful narratives are the ones that the most people can relate to), no single narrative can include everybody. The only difference to society is in whether the majority’s narrative can accommodate diversity or not. Unless diversity is actively tolerated, respected and cherished to some degree, the whole ‘majority’ society can go stale and rigid for want of new ideas.

Branding is always targeted at someone. Very few campaigns do not appeal to, and therefore push, one set of values more than others.

I fully acknowledge the benefits of advertising in promoting products, but brands have become symbiotic with our identities. We give money to the brand by buying the product, and in return we ‘buy into’ the brand – we identify ourselves with it, implying ‘I am Mr. Muscle, and I love the jobs you hate’, ‘I drink PepsiMax so I am cool like David Beckham’ or maybe ‘my Omega watch is just like James Bond’s so I’m a dysfunctional womaniser’.

Individual personalities are becoming things that are imposed as a set of choices: you compose your public identity partly from the global brands you affiliate with. Your friends get told that you ‘like’ Diet Coke and Batman on Facebook. Your newsfeed is filtered to be more relevant to your ‘preferences’ as surmised from the statistics of your behaviour online. What are the implications of this? Will people be motivated to actually find out about themselves and each other, or will they just wear brands on their cyber-lapel like political badges and leave it at that? The filter bubble phenomenon has been well-documented both in theory and practise.

What if the only people you ever encountered were people you could be fairly sure were just like you? Nobody you ever met would need much effort for you to understand, because you can reasonably assume they’re thinking the same things as you. They vote the same way, and they can’t understand why anybody wouldn’t. You don’t have any friends outside your group – why would you? They’re all idiots. Republicans. Democrats. French. Chinese. Fat Americans. Terrorist infidels.

Welcome to the Web 2.0, where the Social Network is the new class system.

Personally, I predict a counter-trend here. Less will really change than you might think. Those of us with a hankering for argument and alternative viewpoints will always hunger for a bit of randomness in social encounters. This randomness will probably come with strings attached, but whyever would you want dangerous wilderness when you can live all your life in a well-managed Walled Garden?