by Sebastian Benthall

Sometimes traffic on this blog draws attention to an old post from years ago. This can be a reminder that I’ve been repeating myself, encountering the same themes over and over again. This is not necessarily a bad thing, because I hope to one day compile the ideas from this blog into a book. It’s nice to see what points keep resurfacing.

One of these points is that liberalism assumes equality, but this challenged by society’s need for control structures, which creates inequality, which then undermines liberalism. This post calls in Charles Taylor (writing about Hegel!) to make the point. This post makes the point more succinctly. I’ve been drawing on Beniger for the ‘society needs control to manage its own integration’ thesis. I’ve pointed to the term managerialism as referring to an alternative to liberalism based on the acknowledgement of this need for control structures. Managerialism looks a lot like liberalism, it turns out, but it justifies things on different grounds and does not get so confused. As an alternative, more Bourdieusian view of the problem, I consider the relationship between capital, democracy, and oligarchy here. There are some useful names for what happens when managerialism goes wrong and people seem disconnected from each other–anomie–or from the control structures–alienation.

A related point I’ve made repeatedly is the tension between procedural legitimacy and getting people the substantive results that they want. That post about Hegel goes into this. But it comes up again in very recent work on antidiscrimination law and machine learning. What this amounts to is that attempts to come up with a fair, legitimate procedure are going to divide up the “pie” of resources, or be perceived to divide up the pie of resources, somehow, and people are going to be upset about it, however the pie is sliced.

A related theme that comes up frequently is mathematics. My contention is that effective control is a technical accomplishment that is mathematically optimized and constrained. There are mathematical results that reveal necessary trade-offs between values. Data science has been misunderstood as positivism when in fact it is a means of power. Technical knowledge and technology are forms of capital (Bourdieu again). Perhaps precisely because it is a rare form of capital, science is politically distrusted.

To put it succinctly: lack of mathematics education, due to lack of opportunity or mathophobia, lead to alienation and anomie in an economy of control. This is partly reflected in the chaotic disciplinarity of the social sciences, especially as they react to computational social science, at the intersection of social sciences, statistics, and computer science.

Lest this all seem like an argument for the mathematical certitude of totalitarianism, I have elsewhere considered and rejected this possibility of ‘instrumentality run amok‘. I’ve summarized these arguments here, though this appears to have left a number of people unconvinced. I’ve argued this further, and think there’s more to this story (a formalization of Scott’s arguments from Seeing Like a State, perhaps), but I must admit I don’t have a convincing solution to the “control problem” yet. However, it must be noted that the answer to the control problem is an empirical or scientific prediction, not a political inclination. Whether or not it is the most interesting or important question regarding technological control has been debated to a stalemate, as far as I can tell.

As I don’t believe singleton control is a likely or interesting scenario, I’m more interested in practical ways of offering legitimacy or resistance to control structures. I used to think the “right” political solution was a kind of “hacker class consciousness“; I don’t believe this any more. However, I still think there’s a lot to the idea of recursive publics as actually existing alternative power structures. Platform coops are interesting for the same reason.

All this leads me to admit my interest in the disruptive technology du jour, the blockchain.