Read The Happiness Industry Online

Authors: William Davies

The Happiness Industry (26 page)

In moving beyond survey techniques, researchers believe that they can now circumvent the quasi-democratic, political aspect of finding out what people value, but without simply depending on the market either. By analysing tweets, online behaviour or facial expressions in a largely clandestine fashion, a degree of detached objectivity becomes possible which is not available to the researcher who actually has to confront people in order to collect data. Watson's dream of freeing psychology from its reliance on the ‘verbal behaviour' of the subject looks to be nearly realized. The truth of our emotions will, allegedly, become plain, once researchers have decoded our brains, faces and unintentional sentiments.

As we move beyond the age of the survey, many of the same questions are being asked, but now with far more fine-grained answers. In place of opinion-polling, sentiment-tracking companies such as General Sentiment scrape data from 60 million sources every day, to produce interpretations of what the public thinks. In place of users' satisfaction surveys, public service providers and health-care providers are analysing social media sentiment for more conclusive evaluations.
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And in place of traditional market research, data analytics apparently reveals our deepest tastes and desires.
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One interesting element of this is that our quasi-private
conversations with each other (for instance via Facebook) are viewed as good hard data to be analysed, whereas the reports we make to interviews or surveys are considered less reliable. Our conscious statements of opinion or critique are untrustworthy, whereas our unwitting ‘verbal behaviour' is viewed as a source of inner psychological truth. This may make sense from the perspective of behavioural and emotional science, but it is disastrous from the point of view of democracy, which depends on the notion that people are capable of voicing their interests deliberately and consciously.

These developments have generated a new wave of optimism regarding what can be known about the individual mind, decisionmaking and happiness. Finally, the real facts of how to influence decision-making may come to light. At last, the truth of why people buy what they buy might come to light. Now, over two centuries after Bentham, we might be about to discover what actually causes a quantifiable increase in human happiness. And in the face of a depression epidemic, mass surveillance of mood and behaviour might unlock the secrets of this disease, so as to screen for it and offer tips and tools to avoid it.

The unspoken precondition of this utopian vision is that society becomes designed and governed as a vast laboratory, which we inhabit almost constantly in our day-to-day lives. This is a new type of power dynamic altogether, which is difficult to characterize purely in terms of surveillance and privacy. The accumulation of psychological data occurs unobtrusively in such a society, often thanks to the enthusiastic co-operation of individual consumers and social media users. Its rationale is typically to make life easier, healthier and happier for all. It offers environments, such as smart cities, which are constantly adapting around behaviour and real-time social trends, in ways that most people
are scarcely aware of. And in keeping with Bentham's fear of the ‘tyranny of sounds', it replaces dialogue with expert management. After all, not everybody can inhabit a laboratory, no matter how big. A powerful minority must play the role of the scientists.

We received a glimpse of this future in June 2014, when Facebook published a paper analysing ‘emotional contagion' in social networks.
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The public response was similar to that of JWT's survey subjects in Copenhagen and London in 1927: outrage. This one academic paper made headlines around the world, though not for the quality of its findings. Instead, the discovery that Facebook had deliberately manipulated the newsfeed of 700,000 users for one week in January 2012 seemed like an abuse of research ethics.
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It turned out that this platform, on which friendships and public campaigns depended, was also being used as a laboratory to probe and test behaviour.

Will this sort of activity still prompt outrage in another ten or twenty years, or will we have grown used to it? More to the point, will Facebook still bother to publish their findings, or will they simply run experiments for their own private benefit? What is troubling about the situation today is that the power inequalities on which such forms of knowledge depend have become largely invisible or taken for granted. The fact that they combine ‘benign' intentions (to improve our health and well-being) with those of profit and elite political strategy is central to how they function. The only way in which such blanket administration of our everyday lives can now be challenged is if we also challenge the automatic right of experts to deliver any form of emotion to us, be it positive or negative.

The truth of happiness?

How happy were you yesterday? How did you feel? Do you know? Can you remember? It's possible that, even if you don't, someone else could tell you. As the digital and neurological sciences of happiness progress, they are nearing the point where experts are more qualified to speak about your subjective state than you are. Or to put that another way, subjective states are no longer subjective matters.

Twitter is a case in point. Twitter's 250 million users produce 500 million tweets per day, producing a constant stream of data which can potentially be analysed for various purposes. This is one of the more dramatic examples of big data accumulation in recent years. Ten per cent of this stream is made freely available at no cost, opening up enticing opportunities for social researchers, both in business and universities. The rest of the stream, up to the complete fire-hose of every single tweet, is available for a range of fees.

The research challenge is how to make sense of so much data, which involves building algorithms capable of interpreting millions of tweets. At the University of Pittsburgh, a group of psychologists has built one such algorithm, aimed at capturing how much happiness is expressed in a single 140-character tweet. To do this, the researchers created a database of five thousand words, drawn from digital texts, and gave every word a ‘happiness value' on a scale of 1–9. A tweet can then be automatically scored in terms of its expression of happiness.

The Pittsburgh project is designed to spot trends in happiness at an aggregate level, analysing 50 million tweets every day. It is not in itself interested in the happiness levels of individual users. Instead, it can identify some clear patterns in how happiness
fluctuates across the population, both over time and over space. Happiness maps have been developed on the back of this data; the researchers now know that Tuesday is the least happy day of the week, and Saturday the most happy. This project might not actually report back on how happy you were last week. But a range of similar projects could, typically under the auspices that it would be for your own well-being, health or safety.

One such project is the ‘Durkheim Project', developed by researchers at Dartmouth College, named after Émile Durkheim. Durkheim is known as one of the founders of sociology, and author of
Suicide
, an analysis of variations in national suicide rates in the nineteenth century. Durkheim was drawing on the new statistical data on death rates that had recently accrued over a number of decades in Europe at the time. The Durkheim Project aimed to go one better: drawing on analysis of social media data and mobile phone conversations, suicide would be predicted.

The targets of this analysis are former US military veterans, who are known to have a higher risk of suicide than the rest of the population. The question is how to identify those who need help before it is too late. With support from the Department of Veterans Affairs, who are able to access medical records as an additional source of data, the Durkheim Project aims to provide an early warning system that a certain individual is showing higher risk of suicide. This requires sophisticated forms of data analytics capable of extracting meaning from large quantities of data, again through learning what specific words are likely to mean. Sentences and grammatical constructions of suicidal people are studied and taught to computers. Without any intrusion into the individual's life, their feelings are being tracked. A similar project, at University of Warwick, UK, has used real
suicide notes to teach computers how to spot suicidal thoughts within grammatical constructions.

If individuals can be co-opted into such psychological surveillance programmes, then the possibilities for measurement increase accordingly. The growth of mobile devices as tools for ‘Health 2.0' policies, aimed at capturing the well-being of individuals on a moment-by-moment basis, means that the medical gaze can penetrate much further into everyday life, beyond the boundaries of the surgery, hospital or laboratory. ‘Mood tracking' is now a particular wing of the larger quantified self movement, in which individuals seek to measure fluctuations in their own mood, either out of concern or just curiosity.
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Apps such as Moodscope (based on a well-known psychiatric affect scale, PANAS) have been built to facilitate and standardize the tracking of one's own mood.

Smartphone apps such as Track Your Happiness developed at Harvard or Mappiness at London School of Economics, which prod people every few hours for details of their present mood (reported as a number) and present activity, enable economists and well-being specialists to accumulate knowledge which was impossible to imagine only a decade ago. It turns out that people are happiest while having ‘intimate relations', though one wonders what reporting this via a phone does for the quality of that experience.
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When researchers first began trying to collect data on the happiness of entire societies during the 1960s, they encountered a problem. This is another of those technical problems which cut to the heart of utilitarianism: to what extent can you trust people's own reports of their happiness? The way people report happiness is likely to be skewed by a couple of things, though this of course assumes that there is something ‘objective' about
happiness to be reported in the first place. Firstly, they may forget how they actually experience their day-to-day lives and end up with a sunnier or gloomier overall take than is actually representative of their mood. We might consider this to be a form of delusion, although people are of course at liberty to narrate their lives however they see fit.

Secondly, they will be influenced by cultural norms regarding how to answer a survey question. If the question is, ‘Overall how happy do you feel with your life?' or ‘How happy were you yesterday?', some individuals may immediately react in certain ways, due to culture or upbringing, which lead them towards certain types of answer. They may feel that it is defeatist to complain and so exaggerate their happiness (a distinctly American problem), or conversely that it is vulgar to declare oneself happy and so under-report it (a more frequent phenomenon in France).

As happiness economics grew over the course of the 1990s, there emerged various strategies for getting around this problem. The goal was to access happiness as we actually experience it, rather than as we say we experience it. Obviously, this is as much a philosophical problem as a methodological one. What would it mean to access the ‘truth' of happiness, without going via the individual's own conscious reflections on it? Unperturbed, psychologists and economists have developed various ways of doing just this. One technique is the day reconstruction method, in which individuals participate in a happiness study by sitting down at the end of every day and producing a diary of how happy they felt at various times and what they were doing. This has some obvious flaws in terms of the possibility of misremembered experiences. But it takes one step towards cutting out the conscious, reporting mind in pursuit of some ethereal quantity of happiness that rises and falls within the mind.

The new surveillance and self-surveillance opportunities offered by data analytics and smartphones promise to eradicate this problem. People don't need to report their happiness via a survey if their words can be interpreted en masse without them even knowing, or if they can offer real-time numerical feedback on it via a smartphone app. For two hundred years, the ambition to measure the ebbs and flows of mental life was restricted to the limits of institutions – prisons, university labs, hospitals, workplaces. The power hierarchies which facilitated this measurement were therefore visible, even if they were not challengeable. Today, as those institutional limits evaporate, they are neither of those things.

Yet this is not even the most extravagant possibility for utilitarian surveillance. At the outer reaches of the science of human happiness are research projects which strip away the experience or consciousness of it altogether. Happiness, by this account, is not so much a state of mind or consciousness, but a biological and physical state of being that can be known objectively regardless of the carrier's own judgement or reports of it.

What has always been so seductive about the science of happiness is its promise to unlock the secrets of subjective mood. But as that science becomes ever more advanced, eventually the subjective element of it starts to drop out of the picture altogether. Bentham's presumption, that pleasure and pain are the only real dimensions of psychology, is now leading squarely towards the philosophical riddle whereby a neuroscientist or data scientist can tell me that I am objectively wrong about my own mood. We are reaching the point where our bodies are more trusted communicators than our words.

If one way of ‘seeing' happiness as a physiological event is via the face, the other way is to get even closer to its supposed locus:
the brain. Various types of mood and disorder are now considered visible, thanks to the affordances of EEG and fMRI scanners, including bipolar disorder and experiences of happiness.
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The exaggerated claims that have been made for neuroscience are already legion, and the plausibility of ever entirely reducing mind (as studied by psychology) to brain (as studied by neuroscience) depends on fundamentally misunderstanding what the word ‘mind' means in the first place. Nevertheless, it's possible that a new utilitarian epoch is opening up, the like of which Bentham could never have imagined, in which happiness science reaches the point where it can bypass not only traditional surveys and psychological tests, but all physical and verbal indicators of mood, to access the mood itself in its physical manifestation. The fundamental meaning of the word ‘mood' is being transformed.

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