Blockchaining the Center

I begin by recalling (and revising) an old thought experiment of mine, somewhat derivative of Moldbug (but also Peirce, and maybe even Nietzsche), and which I can now speak of in terms of the demand-command circuit explored a couple of posts back. Consider what you would have the government do, what the government having done that in a way that you would affirm that it has, in fact, been done in such a way as to fulfill your demand would look like, which means without any unintended effects that would vitiate the intent of your demand; then, consider all the institutional realignments required for all that to be the case; then, consider the kind of government that could enact such a change and further consider that a government with that power would not only have so much more knowledge and understanding of the conditions enabling the meeting of your demand than could be informing the demand itself and, further, that the government capable of doing all this would have no need to care what you wanted even while it might find your demand to be useful input into its data banks—well, then what? Do you retract your demand? But wouldn’t that be only to issue a new one, since we can’t help wanting? Or, rather, like presumably Nietzsche encourages the one faced with his demon providing intelligence on “eternal return,” would you accept the demand-command circuit and seek agreement with your fellow citizens on a mode of governance that could detect and analyze all demands while being beholden to none; a government that you would therefore demand nothing more from than the provision of opportunities to donate most effectively to those data banks? If, in that moment of greatness and ecstasy you were to answer the demon affirmatively, then you are ready to receive your cryptographic key and participate in blockchain governance.

The centrality of data and data security to governance means not a “totalitarian” surveillance state or, more ridiculously, an exacerbation of “biases” that, coincidentally, DEI bureaucrats have been worried about for the past half century but, rather, the most heightened forms of responsibility imaginable. Take all the spheres of human life from which we would want data from: public safety, health, education, etc. Such data is only as good as the institutions charged with attending to those public functions and the institutions dependent upon the functioning of those institutions. We would expect schools, hospitals and police forces to provide us with data on education, health and crime, but we would also depend on institutions that depend upon people being able to read and do math, carry out strenuous tasks over long periods of time and storekeepers and people who go out in the evening to confirm the data provided by the primary institutions. If the police tell us crime is down but everyone is afraid to go out after dark what we have is data testifying to not only the inefficiency but dishonesty and corruption of the police and/or the courts. But that means that someone is gathering that other kind of data downstream of the primary function. We have our three destinations for the gathering of such data: the distributory center, arbiter of the nomos, holder of debts and dean of succession; the juridical; and the disciplines. The occupant of the center needs intelligence to make decisions on succession, and so the more questionable and arbitrary those decisions become the less valuable the intelligence; the juridical order needs data to make decisions that defer both the vendetta and antinomic prosecution of the order itself; and the disciplines need data so that their hypotheses are testable, their experiments replicable and their proofs scalable. They all know what kind of data they are looking for but they don’t know what kind of data they aren’t looking for but might need and so they all want institutions that continually refine their practices while also always recruiting initiators of anomalous and incommensurable practices. We’re always trying to make things fit, at every level, and can never know in advance perfectly what will do so. So, to think of yourself as a carrier of intelligence regarding learning, health and well-being, justice, and so on, is to think of yourself and make yourself something other than a drone slotted into pre-existing pigeonholes. A text is data; reading a text produces data; producing a text in response to a text is data pertinent to the primary text and the range of possible ways of reading it, its affiliation with a world and history of texts, etc. We will be increasing training ourselves on such things.

None of this broader human activity has been blockchained yet—the blockchain has really been limited to money and commerce. There is still far too much disagreement about what counts as learning, knowledge, health, justice, or, for that matter, character building, virtue, enjoyment, kinship, etc., to make it possible to establish protocols regarding what would count as publicly available, permanently stored, actionable data regarding all these forms of life. But that is what center study and, now, more precisely, the demand-command circuit is for. Technology, after all, is really just a way of binding ostensives, imperative, interrogatives and declaratives more tightly together. The problem with gathering data regarding education, health, public safety and so on is that all of these parts of life are connected to each other and the boundaries between them are institutional and historical, even if not arbitrary. Students will not learn if they grow up in crime-ridden neighborhoods and eat processed, sugary foods, and their failure to learn will therefore provide us with only limited intelligence about the schools. Indeed, attempts to single out and blame separate institutions corresponds to democratic politics, and hardly anyone ever does this kind of thing other than to score points. Imagine parent, community groups, employers, etc., suing the school—maybe they’d build a very good case in many instances, but, then, we’d have to acknowledge the school’s right to sue the police, the courts, the food and drug industries, (and maybe even the parents) etc. And that should be our framing, as the juridical is right in the middle of the demand to command circuit—the juridical is always already technological, a stack of scenes, but it also is our best representation, even better than ritual in many ways, of the scenic nature of the human. So, protocols and blockchains would turn the juridical into pedagogical platforms constructed so as to maximize the oscillation between the penetration of juridical categories into every nook and cranny of life and the abolition of the juridical through its perfection. Modern, i.e., desecratory, attempts to mechanize human life through, in particular, the regularity of markets and the distributed agency of divided government along with electoral feedback themselves all depend upon and feed back into the juridical. Without spaces of judgment it’s absurd to speak of markets, political decision making or even, as we are rapidly learning, the most basic institutions of electorally based governments.

Thirdness and Nomos/Class Action are both ways into blockchaining the center and we just have to go on creating other models, or prototypes, as Denisa Kera speaks of in her Algorithms and Automation. (To paraphrase William Carlos Williams, no ideas but in the companies themselves.) She wants a democratic model, based on rights, dialogue, participation, and so on, but we can treat all that as a series of demands to be input while sharing her interest in maximizing agency—not random agency of decentered, independent citizens, but duly appointed, anointed, assigned and delegated agencies positioned variously within the stack in accord with each’s need for data and ability to further shape that data for juridical and successionary purposes. We want to raise debt enforcement in proportion to proximity to the center, where the gifts, opportunities and therefore debt is highest. Let’s try converging health, public order and education in the “unit” of the “fit individual,” always keeping in mind that our future vocation will be training the AIs, or co-constituting with technology, or perfecting stacked presencing. “Fit” means “in shape,” well-conditioned, healthy; but to fit in means to be part of, to correspond to other parts, to be able to take on the characteristics of the whole, to fill some role that might otherwise go unfilled. For our purposes, we can define fitness in terms of exemplary data exchange: the fit individual is he (or she) who both makes best use of available data, including data generated by the activity of the fit individual and provides the best data, precisely by making use of all available means of fitness, physical and intellectual. Fitness is always an approximation to some ideal generated by the fitness activity itself—so, handicapped people or people with diseases and disorders can also be made to fit the fitness regime, which is also concerned with possible biological and technological transformations of the body. We are looking for social or communal fitness as well, so in this regime of regimens we include various learning projects, very much including operating textual transformations. I am to some extent influenced in this line of thinking by Curtis Yarvin’s insistence, recently reiterated in a Gray Mirror post, on maintaining useful, which is to say, challenging, socially important and character-building activities that would otherwise be lost to automation. I don’t agree with this specific proposal that something like shoemaking should be mandated, but there should be institutions conducting continuous inquiries into mind/body/community fits focused, I would say, on exemplary modes of activity that could be auto-telic, having only aesthetic and prototypical value. There is not a single member of any society who could not be made useful, and made to feel useful, within such an order.

What I am suggesting here would be a data exchange, first and foremost—partnering with “rogue” food producers, medical caregivers, pharmaceuticals, biomedical engineers, students of texts (especially those retrieving philological traditions), trainers, stunt men, and others, our company would recruit individuals interested in joining rigorous regimens for nothing more than free access to the goods and services provided by these partners, who provide such goods and services in exchange for nothing more than the data they provide. This would be a prototype of a broader total stacking of data exchange while in the present, of course, the participants would have other gigs, gigs for which the fitness company would make them more fit. The company would serve as a kind of employment and talent agency for its clients, and as marketing for its partners. The company would give out something like “degrees,” with something like “grades,” which, much like the degrees and grades handed out by universities, would serve as tokens providing access to other institutions. At the center of it all is, of course, center study and the originary hypothesis, for which this like any other proposed prototype is a kind of advertisement and proof of concept. And this would require continual increasing precision in the identification of practices, and the exercises that enable and refine them. There’s no real divide between the physical and the intellectual here: learning to read and write in increasingly sophisticated, powerful and nimble ways can be broken down into parts that can be articulated in various ways no less than gymnastics. And this is what would be put to test and put on the blockchain: specific interventions, exercises, applications, assignments, etc., identified with sufficient precision to receive increasingly useful information from (with that information defined as such, along with its degrees and varieties of usefulness, by other interventions, exercises, applications, assignments, etc.), so as to allow for predictions and betting which, in turn, would serve as a model for real world investing. The prototypes such a company would produce might include moot courts, trying out various ways of refining juridical scenes, film and theatrical productions, music, and so on, testing out ways of measuring the value or the “fit” of various talents (and their conditions of production) in actual or possible communities and institutions (and it’s easy to see the possible spin-offs of such enterprises). But it would also be a hub of scientific and technological innovation. We are again thinking of a kind of boundary between the capitalist, even ultra-capitalist, and the no longer quite capitalist order: betting, prediction markets, employment agencies, new currencies, investment inquiries; but, also, a space where well-being, learning and inquiry are ends in themselves—whether a new, qualitative enlargement of the nomos, not territorially but in terms of added layers of the stack, is possible along these lines would be one of the hypotheses placed on trial.