In Amartya Sen’s recent reworking of the theory of justice, communication is the site where the lifeworld comparisons that ground claims for injustice get made. As Sen puts it at the end of The Idea of Justice, ‘it is bad enough that the world in which we live has so much deprivation of one kind or another . . . it would be even more terrible if we were not able to communicate, respond, and altercate’ (2009: 415). And yet through the myth of Big Data we are starting to give credence to a working model of social knowledge that operates as if the explanation of human action, and the processes of meaning-making on which such explanation has relied, don’t matter any more.

a polity based on an impoverished model of the human subject cannot expect much loyalty from, or legitimacy with, those it governs. The warning holds, whether it is governments or dense networks of corporations that are promoting the ‘construct of the intellect’ in question. The right response is not, of course, to walk away from the challenges and opportunities to which today’s new forms of social interconnection and information generation give rise, but instead to make sure that, in facing those challenges and thinking creatively about those opportunities, we take care to hold on to our richer accounts of human agency and knowledge, and to the sense of possible democratic agency and possible justice whose basic components they supply.

the alienation of the interpreter from the interpreted’ (2004 [1975]: 312)

here a vast power asymmetry is emerging that would not, I suspect, betolerated if it were exclusively state power that was benefiting

As US legal scholar Julie Cohen notes, we all increasingly operate in our daily lives in ‘networked space’ but ‘the configuration of networked space is . . . increasingly opaque to its users’ (2012: 202). Indeed, she argues, today’s web of protocols and passwords, data requirements and data monitoring, has created ‘a system of governance that is authoritarian’, in the sense that there seems little alternative but to comply with it.

All the myths I have discussed tonight rationalize massive concentrations of symbolic resource; all therefore involve injustice of a sort. Such injustices are difficult to name, precisely because they involve concentrations of power over the resources for naming.

I call this research ‘social analytics’: that is, the study of how social actors are themselves using analytics - data measures of all kinds, including those they have developed or customised – to meet their own ends, for example, by interpreting the world and their actions in new ways

First, agency, by which I mean not brute acts (of clicking on this button, pressing ‘like’ to this post) but (following Weber) the longer processes of action based on reflection, giving an account of what one has done, even more basically, making sense of the world so as to act within it.

As my colleague Robin Mansell argues in her book Imagining the Internet, we cannot move beyond such misalignments, unless we build new imaginaries - or at least, renew our hold on old ones. Challenging the myth of big data – a myth in which mass media and social media, the focus of my first two myths, are increasingly implicated and in which states and corporations are investing on a massive scale

Such analysis, by abandoning any language for interpreting what human subjects mean by their action, condemns us, like sleepwalkers, to submit to such changes.

when a vast attempt is under way to build a different account of how and why people matter, it is not enough just to say that people matter. We need an alternative account of why knowledge about people matters for understanding the social, and indeed why ‘the social’ matters, if understood as more than just a probability set for predicting repeat action.

we have become accustomed to giving accounts of ourselves in such data-saturated ways on social networking sites and elsewhere; as such habits become established, we may lose the sense that our collective life could lie anywhere else than in such ‘datafied’ forms

We risk building a social landscape peopled by what the 19th century Russian novelist Nikolai Gogol called ‘dead souls’: human entities that have financial value (in his novel, if you remember, as mortgageable assets; in our new world, as unwitting data producers), but that are not alive, not at least in the sense we know human beings to be alive.

Its new form of ‘social knowledge’ splits up discourse populations: the groups that could once be talked about aspopulations for various purposes. It fractures the space of discourse, depicting its data subjects in ways that don’t connect any more with the space of action and thought in which actual individuals think they live; and it stretches the time of discourse, aggregating action-fragments from any moment in the stream of a person’s recorded acts into patterns that bear little relationship to how those people themselves understand the sequence and meaning of their actions.

But if the big data model works by equatingouronly forms of social knowledgewith such probabilities, then we have already started organising things so that the single story – your story, my story - really doesn’t matter.

Judith Butler provides a clue to this when in her book Precarious Life, discussing how a media of excessive spectacle (too much showing) narrows our grasp of the human, she writes that ‘there is less a dehumanizing discourse at work here than a refusal of discourse’ (2004: 36). It is the gaps and breaks in our languages of social interpretation, authorised by the myth of big data, on which we must focus.

we too are involved in its reproduction, supplying information (to government and countless other collectors, including social media platforms) about what we do, as we do it, allowing that information to supplant other possible types of information about ourselves, what we say, and how we reflect on our situation.

predictive strings that tell those who care what, say a man in his 50s with a certain educational background will do on a Thursday evening in November

of human behaviour, from linguistics to sociology. Forget taxonomy, ontology and psychology’. Why? Because the proxies that big data generate are good enough; or as Google’s research director put it, ‘you can succeed without them’. But success for who? For what purpose? In the service of whose or what notion of knowledge?

he moral consequences of acting on the basis of ‘big data’ arises - for example, arresting people for offences they are predicted to commit but haven’t yet - they back off and say that big data only provide probabilities, not actualities, and worry about ‘fetishizing the output of our [data] analysis’ (151).

Myth works, as I’ve often argued following Maurice Bloch and Roland Barthes, through ambiguity: through sometimes claiming to offer ‘truth’ and at other times to be merely playful, providing what, in the George W. Bush era, was called ‘plausible deniability’, but here at the level of claims aboutknowledge claims!

his lack of sense doesn’t matter, they argue, because a really good proxy, once discovered, will help us see regularity across vast numbers of variables that would otherwise be invisible. The result is to undercut the rationale of not just qualitative methods of analysis, but also of the interpretative models – the hermeneutics, if you like - that for decades have driven large-scale survey research. And, if we reject the very possibility of such a hermeneutic, then we appear to disarm hermeneutic critique also, making the myth of Big Data armour-plated against criticism

as in the controversial case where US retailer Target started communicating with a young woman on the basis she was pregnant, just because she had started buying a basket of consumer products that their predictive model associated with women who would shortly start buying pregnancy products.

analysts are giving up on specific hypotheses and instead focussing on generating, through countless parallel calculations, ‘a really good proxy’

Big data’s new ‘politics of measurement’ (in anthropologist James Scott’s phrase: 1998: 29) is changing the terrain on which all large institutions (including governments) can claim to tell us the way things are.

the claims now being made about what big data can achieve for understanding our world.

The ‘social’ at which media processes are targeted is being reconstructed all around us.

We all know that the tracking of our activity on social media sites is the basis of the value Facebook sells to advertisers and, indirectly, to the new data-mining industry that has emerged to create additional value out of that data.

he myth of ‘us’, like all myth, disguises the other knowledges it helps us lose along the way. So we need to dis-enchant such rhetorical claims about the new social world that platform-based networks make possible.

rhetoric about the social does the work of analysis: what do these writers mean by ‘social’? does it relate to what we have meant by that word in the past?

tracking us as we perform the act of ‘being us’, on platforms that propose we do just tha

Remember there is no collectivity, no ‘us’, of the sort we have come to talk about around social media, until those platforms attract ‘us’ (whoever we are) to use them, and link to them.

why talk of ‘myth’, why disenchant what so often is good fun? Because we must be wary when our most important moments of ‘coming together’ seem to be captured in what people happen to do on platforms whose economic value is based on generating just such an idea of natural collectivity. It would not be enough for Facebook, for example, to say that lots of small groups, unknown to each other, do roughly similar things behind virtual closed doors. It is vital to the value claims on which Facebook depends for it to open as many of those interconnecting doors as possible and claim that Facebook is what ‘we’ are now doing together. ‘We’, the collectivity of everyday people, everywhere. Vague as it is, this claim grounds any number of specific rhetorics and judgements about what’s happening, what’s trending, and so (by a self-accumulating logic) what matters: for government, society, business, and for us.

We see the myth’s effects in accounts of political protests across the world in the past 3 years as Twitter or Facebook revolutions, orin the Guardian’s recent listing of ‘us’ as media personality of 2013.

when Facebook offers to ‘tell the story of our lives’, we have: ‘us now’. Of course, this myth is not yet fully established: if the myth of the mediated centre took decades to become so, the myth of ‘us’ too will only fully stabilise over time.

A new myth about the collectivities we form when we use platforms such as Facebook. An emerging myth of natural collectivity that is particularly seductive, because here traditional media institutions seem to drop out altogether from the picture: the story is focussed entirely on what ‘we’ do naturally, when we have the chance to keep in touch with each other, as of course we want to do.

Indeed, social media platforms, far from being an authentic social response to large media, represent an entirely new business model for media and communications infrastructures. And, as this new way of organizing business and our lives around digital platforms becomes normalized, a new myth is emerging to make sense of this.

Social media are of fundamental importance to the myth of the mediated centre, because they offer a new form of centrality, a new social ‘liveness’, mediated apparently by us rather than by content-producing media institutions.

Media have evolved elaborate categories of thought to express the myth of their centrality: for example, the language of ‘liveness’ and celebrity, the greater value given to what’s “in” the media over what isn’t. But, as I have argued for a decade or so, we need to disenchant that language, not because it is necessarily bad for us, but in order to grasp all the work done that keeps it in place, and sustains the particular perspective onsocialknowledge that it involves.

This myth is what we might call a ‘reserve rationalization’ that makes sense of our organizing our lives around the content flows of media organizations; it tells us that society has a ‘centre’ of value, knowledge and meaning, and that particular institutions, those we call ‘media’, have a privileged role in giving us access to that supposed ‘centre’.

the exchanges of signs that enable acts of communications to make sense, to accumulate over time as meaning, as knowledge.

we run’, he said, ‘the risk that the whole humanities enterprise of trying to understand ourselves is coming to seem peculiar’.

the myth of Big Data emerges, because it challenges the very idea that the social is something we can interpret at all

rationalizing a certain perspective on how we come to know the social, obscures our possibilities for imagining, describing and enacting the social otherwise.

rethinking government as a version of total data access

The ‘myth of us’ has, as its domain, our activities of social interaction as registered by social media platforms; its effect is to underwrite the belief on which those platforms rely that this is where we now come together: the ‘us’ here is not necessarily national, it is just as easily transnational. This myth’s immediate beneficiaries are the platform owners, while the ultimate benefit passes to the institutions from government to marketers that want to remain in touch with us this way.

collectivities:

Calling these different processes ‘myths’ enables us to see an underlying pattern in how, as societies, we make sense of organizing things around assumptions that certain types of information, expertise and knowledge are more valuable than others, and offer us a privileged view on the reality of social life. I say ‘we’ because these myths are not merely an elite production: we are all, potentially, involved in producing these myths through our everyday actions (making ‘myth’ a more useful term, incidentally, than ‘ideology’). Each myth I have mentioned has a distinctive domain, a distinctive effect and a distinctive set of beneficiaries.

entangled with the building and sustaining of platforms for social interaction (such as Facebook, Twitter, Weibo) and with the continuous gathering of data about us whose value fuels those platforms and increasingly the whole of the media and cultural industries.

three ‘myths’ by which the relations between media and social knowledge have been framed and disguised.

1 A NECESSARY DISENCHANTMENT:

I am interested in how certain institutions with concentrated power over the production and circulation of symbols (we’ve usually called them ‘media’) have for at least two centuries been bound up with our possibilities of knowing the social.

representing shared reality, reality that becomes recognised as ‘ours’, in part, through what media do