Power Asymmetries in the Medium of Data

In general, the data form reveals itself in various interrelated ways, all of which are worth analyzing: its quantitative essence, reducing subjectivities into objectivities; its connection to profit and the capitalist system; its alleged neutrality regarding the contents different data represent (Zuboff, 2015, p. 79); and so forth. What interests me here, though, are the power relations inherent to data. For I hold that the latter is not the neutral medium its proponents would have us believe. When it comes to issues of privacy, it is not unusual for data giants like Google, Facebook, Microsoft, Amazon, and others to grandly announce that they are unconcerned with the contents of user’s internet behaviour, such as their emails or messages (Burlacu, 2018). Or, in a more recent instance, Facebook’s Chief Privacy Officer Erin Egan claimed that the company does not “watch or listen to your audio or video calls” (Biddle, 2020). The occasional internal document leak and subsequent scandal notwithstanding, this is probably largely true (Price, 2019). The unfortunate fact is: They do not need to. As long as Google and co. have access to their user’s metadata, they have more than enough information to profitably sustain their business. Indeed, we are talking high profitability, with data having become the world’s most valuable resource to date (Selz, 2017; Tarnoff, 2018; The Economist, 2017). It is predominantly metadata, or what Zuboff (2015, p. 79) calls ‘data exhaust’, that underlies this fountain of wealth. To Big Data it is not necessarily what you write that matters but how you write it, for example – Google knows how to turn even the most trivial sets of data trash into money. As the documentary Nothing to Hide (Meillassoux, 2017) vividly displays, with nothing but superficial data can sophisticated technology map out a personality and behaviour profile which is more accurate than a self-description of one’s conscious self. Significantly, “Google knows far more about its populations than they know about themselves” (Zuboff, 2015, p. 83).

The foregoing ‘problem statement’ points to crucial injustices and inequalities related to data, which go beyond the mere knowledge of another’s secrets. These inequalities are best evaluated under the header of power. In this regard, I contend that asymmetries of power become prevalent when scrutinizing data, both by virtue of its nature and its current utilization. I shall treat both these aspects under what I term ‘the inaccessibility problem’.

As data qua data, a disbalance is already exposed in its two most common definitions. According to Merriam-Webster (“Data,” n.d.), data refers to either “factual information (such as measurements or statistics) used as a basis for reasoning, discussion, or calculation” or “information in digital form that can be transmitted or processed”. We thus have: Data as information and data as bits and bytes. 

As for the former, let us remember that we humans are the original computers: Humans have a very refined capacity for processing, storing and retrieving information. This ability is existent in every human to some degree, in some fashion. Nonetheless, issues come with numbers. The sheer mass of information available is restricted by the individual capacity to cope: There is only so much information one person can effectively manage. More so, the bulk of information permits one entity to possess more than another. As scientia potentia est, it is here that power inequalities attach. While possibly insignificant at the micro-level of individuals, information lends itself to be accumulated, conglomerated, by meso and macro groups, such as, interest groups, companies and states. Masses of information are hardly handled by one person alone, but increasingly more accessible the larger the handler becomes.

There are limits to the amount of information that humans can naturally deal with, even if converged in larger entities. In this field, machines have long outraced humans, and will continue to do so exponentially according to Moore’s law. Enter data as bits and bytes. But here the inaccessibility problem is even more apparent, since humans simply cannot understand data in this form. Bits, ones and zeros, digital abstractions, are not within the repertoire of human language or cognition. They are, in this sense, unintelligible to humans. Certainly, individual pieces of data can be translated – binary can be translated into decimal, no doubt. However, strings of data, ever-growing and convoluted vastness of digital information, are not available for penetration by the human mind.

One might therefore suspect, in the data form, a propensity for power asymmetries. To sum up my endeavours to this point: Thus far I have described the inaccessibility problem, which is evident both in data as information, where mass opens up the possibilities for power, and in data as bits, where direct unintelligibility renders humans secondary interpreters at best. The medium of data is, so it appears, not altogether neutral. By contrast, it appears that data in itself is a potent carrier of power relations.