Digifesto

Category: academia

Eclipse of Reason

I’m starting to read Max Horkheimer’s Eclipse of Reason. I have had high hopes for it and have not been disappointed.

The distinction Horkheimer draws in the first section, “Means and Ends”, is between subjective reason and objective reason.

Subjective reason is the kind of reasoning that is used to most efficiently achieve ones goals, whatever they are. Writing even as early as 1947, Horkheimer notes that subjective reason has become formalized and reduced to the computation of technical probabilities. He is referring to the formalization of logic in the Anglophone tradition by Russell and Whitehead and its use in early computer science, most likely. (See Imre Lakatos and programming as dialectic for more background on this, as well as resonant material on where this is going)

Objective reason is, within a simple “means/ends” binary, most simply described as the reasoning of ends. I am not very far through the book and Horkheimer is so far unspecific about what this entails in practice but instead articulates it as an idea that has fallen out of use. He associates it with Platonic forms. With logos–a word that becomes especially charged for me around Christmas and whose religious connotations are certainly intertwined with the idea of objectivity. Since it is objective and not bound to a particular subject, the rationality of correct ends is the rationality of the whole world or universe, it’s proper ordering or harmony. Humanity’s understanding of it is not a technical accomplishment so much an achievement of revelation or wisdom achieved–and I think this is Horkheimer’s Hegelian/Marxist twist–dialectically.

Horkheimer in 1947 believes that subjective reason, and specifically its formalization, have undermined objective reason by exposing its mythological origins. While we have countless traditions still based in old ideologies that give us shared values and norms simply out of habit, they have been exposed as superstition. And so while our ability to achieve our goals has been amplified, our ability to have goals with intellectual integrity has hollowed out. This is a crisis.

One reason this is a crisis is because (to paraphrase) the functions once performed by objectivity or authoritarian religion or metaphysics are now taken on by the reifying apparatus of the market. This is a Marxist critique that is apropos today.

It is not hard to see that Horkheimer’s critique of “formalized subjective reason” extends to the wide use of computational statistics or “data science” in the vast ways it is now. Moreover, it’s easy to see how the “Internet of Things” and everything else instrumented–the Facebook user interface, this blog post, everything else–participates in this reifying market apparatus. Every critique of the Internet and the data economy from the past five years has just been a reiteration of Horkheimer, whose warning came loud and clear in the 40’s.

Moreover, the anxieties of the “apocalyptic libertarians” of Sam Franks article, the Less Wrong theorists of friendly and unfriendly Artificial intelligence, are straight out of the old books of the Frankfurt School. Ironically, todays “rationalists” have no awareness of the broader history of rationality. Rather, their version of rationality begins with Von Neummann, and ends with two kinds of rationality, “epistemic rationality”, about determining correct beliefs, and “instrumental rationality”, about correctly reaching ones ends. Both are formal and subjective, in Horkheimer’s analysis; they don’t even have a word for ‘objective reason’, it has so far fallen away from their awareness of what is intellectually possible.

But the consequence is that this same community lives in fear of the unfriendly AI–a superintelligence driven by a “utility function” so inhuman that it creates a dystopia. Unarmed with the tools of Marxist criticism, they are unable to see the present economic system as precisely that inhuman superintelligence, a monster bricolage of formally reasoning market apparati.

For Horkheimer (and I’m talking out of my butt a little here because I haven’t read enough of the book to really know; I’m going on some context I’ve read up on early) the formalization and automation of reason is part of the problem. Having a computer think for you is very different from actually thinking. The latter is psychologically transformative in ways that the former is not. It is hard for me to tell whether Horkheimer would prefer things to go back the way they were, or if he thinks that we must resign ourselves to a bleak inhuman future, or what.

My own view, which I am worried is deeply quixotic, is that a formalization of objective reason would allow us to achieve its conditions faster. You could say I’m a logos-accelerationist. However, if the way to achieve objective reason is dialectically, then this requires a mathematical formalization of dialectic. That’s shooting the moon.

This is not entirely unlike the goals and position of MIRI in a number of ways except that I think I’ve got some deep intellectual disagreements about their formulation of the problem.

Reflecting on “Technoscience and Expressionism” by @FractalOntology

I’ve come across Joseph Weissman’s (@FractalOntology) “Technoscience and Expressionism” and am grateful for it, as its filled me in on a philosophical position that I missed the first time around, accelerationism. I’m not a Deleuzian and prefer my analytic texts to plod, so I can’t say I understood all of the essay. On the other hand, I gather the angle of this kind of philosophizing is intentionally psychotherapeutic and hence serves and artistic/literary function rather than one that explicitly guides praxis.

I am curious about the essay because I would like to see a thorough analysis of the political possibilities for the 21st century that gets past 20th century tropes. The passions of journalistic and intellectual debate have an atavistic tendency due to a lack of imagination that I would like to avoid in my own life and work.

Accelerationism looks new. It was pronounced in a manifesto, which is a good start.

Here is a quote from it:

Democracy cannot be defined simply by its means — not via voting, discussion, or general assemblies. Real democracy must be defined by its goal — collective self-​mastery. This is a project which must align politics with the legacy of the Enlightenment, to the extent that it is only through harnessing our ability to understand ourselves and our world better (our social, technical, economic, psychological world) that we can come to rule ourselves. We need to posit a collectively controlled legitimate vertical authority in addition to distributed horizontal forms of sociality, to avoid becoming the slaves of either a tyrannical totalitarian centralism or a capricious emergent order beyond our control. The command of The Plan must be married to the improvised order of The Network.

Hell yeah, the Enlightenment! Sign me up!

The manifesto calls for an end to the left’s emphasis on local action, transparency, and direct democracy. Rather, it calls for a muscular hegemonic left that fully employs and deploys “technoscience”.

It is good to be able to name this political tendency and distinguish it from other left tendencies. It is also good to distinguish it from “right accelerationism”, which Weissman identifies with billionaires who want to create exurb communities.

A left-accelerationist impulse is today playing out dramatically against a right-accelerationist one. And the right-accelerationists are about as dangerous as you may imagine. With silicon valley VCs, and libertarian technologists more generally reading Nick Land on geopolitical fragmentation, the reception or at least receptivity to hard-right accelerants seems problematically open (and the recent $2M campaign proposing the segmentation of California into six microstates seems to provide some evidence for this.) Billionaires consuming hard-right accelerationist materials arguing for hyper-secessionism undoubtedly amounts to a critically dangerous situation. I suspect that the right-accelerationist materials, perspectives, affect, energy expresses a similar shadow, if it is not partly what is catalyzing the resurgence of micro-fascisms elsewhere (and macro ones as well — perhaps most significant to my mind here is the overlap of right-acceleration with white nationalism, and more generally what is deplorably and disingenuously called “race realism” — and is of course simply racism; consider Marine le Pen’s fascist front, which recently won 25% of the seats in the French parliament, UKIP’s resurgence in Great Britain; while we may not hear accelerationist allegiances and watchwords explicitly, the political implications and continuity is at the very least somewhat unsettling…)

There is an unfortunate conflation of several different points of view here. It is too easy to associate racism, wealth, and libertarianism as these are the nightmares of the left’s political imagination. If ideological writing is therapeutic, a way of articulating ones dreams, then this is entirely appropriate with a caveat. The caveat being that every nightmare is a creation of ones own psychology more so than a reflection of the real world.

The same elisions are made by Sam Frank in his recent article thematizing Silicon Valley libertarianism, friendly artificial intelligence research, and contemporary rationalism as a self-help technique. There are interesting organizational ties between these institutions that are validly worth investigating but it would be lazy to collapse vast swathes of the intellectual spectrum into binaries.

In March 2013 I wrote about the Bay Area Rationalists:

There is a good story here, somewhere. If I were a journalist, I would get in on this and publish something about it, just because there is such a great opportunity for sensationalist exploitation.

I would like to say “I called it”–Sam Frank has recently written just such a sensationalist, exploitative piece in Harper’s Magazine. It is thoroughly enjoyable and I wouldn’t say it’s inaccurate. But I don’t think this is the best way to get to know these people. A better one is to attend a CFAR workshop. It used to be that you could avoid the fee with a promise to volunteer, but that there was a money-back guarantee which extended to ones promise to volunteer. If that’s still the case, then one can essentially attend for free.

Another way to engage this community intellectually, which I would encourage the left accelerationists to do because it’s interesting, is to start participating on LessWrong. For some reason this community is not subject to ideological raids like so many other community platforms. I think it could stand for an influx of Deleuze.

Ultimately the left/right divide comes down to a question of distribution of resources and/or surplus. Left accelerationist tactics appear from here to be a more viable way of seizing resources than direct democracy. However, the question is whether accelerationist tactics inevitably result in inequalities that create control structures of the kind originally objected to. In other words, this may simply be politics as usual and nothing radical at all.

So there’s an intersection between these considerations (accelerationist vs. … decelerationism? Capital accumulation vs. capital redistribution?) and the question of decentralization of decision-making process (is that the managerialism vs. multistakeholderism divide?) whose logic is unclear to me. I want to know which affinities are necessary and which are merely contingent.

Discourse theory of law from Habermas

There has been at least one major gap in my understanding of Habermas’s social theory which I’m just filling now. The position Habermas reaches towards the end of Theory of Communicative Action vol 2 and develops further in later work in Between Facts and Norms (1992) is the discourse theory of law.

What I think went on is that Habermas eventually gave up on deliberative democracy in its purest form. After a career of scholarship about the public sphere, the ideal speech situation, and communicative action–fully developing the lifeworld as the ground for legitimate norms–but eventually had to make a concession to “the steering media” of money and power as necessary for the organization of society at scale. But at the intersection between lifeworld and system is law. Lawserves as a transmission belt between legitimate norms established by civil society and “system”; at it’s best it is both efficacious and legitimate.

Law is ambiguous; it can serve both legitimate citizen interests united in communicative solidarity. It can also serve strong powerful interests. But it’s where the action is, because it’s where Habermas sees the ability for lifeworld to counter-steer the whole political apparatus towards legitimacy, including shifting the balance of power between lifeworld and system.

This is interesting because:

  • Habermas is like the last living heir of the Frankfurt School mission and this is a mature and actionable view nevertheless founded in the Critical Theory tradition.
  • If you pair it with Lessig’s Code is Law thesis, you get a framework for thinking about how technical mediation of civil society can be legitimate but also efficacious. I.e., code can be legitimized discoursively through communicative action. Arguably, this is how a lot of open source communities work, as well as standards bodies.
  • Thinking about managerialism as a system of centralized power that provides a framework of freedoms within it, Habermas seems to be presenting an alternative model where law or code evolves with the direct input of civil stakeholders. I’m fascinated by where Nick Doty’s work on multistakeholderism in the W3C is going and think there’s an alternative model in there somewhere. There’s a deep consistency in this, noted a while ago (2003) by Froomkin but largely unacknowledged as far as I can tell in the Data and Society or Berkman worlds.

I don’t see in Habermas anything about funding the state. That would mean acknowledging military force and the power to tax. But this is progress for me.

References

Zurn, Christopher. “Discourse theory of law”, in Jurgen Habermas: Key Concepts, edited by Barbara Fultner

Some research questions

Last week was so interesting. Some weeks you just get exposed to so many different ideas that it’s trouble to integrate them. I tried to articulate what’s been coming up as a result. It’s several difficult questions.

  • Assuming trust is necessary for effective context management, how does one organize sociotechnical systems to provide social equity in a sustainable way?
  • Assuming an ecology of scientific practices, what are appropriate selection mechanisms (or criteria)? Are they transcendent or immanent?
  • Given the contradictory character of emotional reality, how can psychic integration occur without rendering one dead or at least very boring?
  • Are there limitations of the computational paradigm imposed by data science as an emerging pan-constructivist practice coextensive with the limits of cognitive or phenomenological primitives?

Some notes:

  • I think that two or three of these questions above may be in essence the same question. In that they can be formalized into the same mathematical problem, and the solution is the same in each case.
  • I really do have to read Isabelle Stengers and Nancy Nersessian. Based on the signals I’m getting, they seem to be the people most on top of their game in terms of understanding how science happens.
  • I’ve been assuming that trust relations are interpersonal but I suppose they can be interorganizational as well, or between a person and an organization. This gets back to a problem I struggle with in a recurring way: how do you account for causal relationships between a macro-organism (like an organization or company) and a micro-organism? I think it’s when there are entanglements between these kinds of entities that we are inclined to call something an “ecosystem”, though I learned recently that this use of the term bothers actual ecologists (no surprise there). The only things I know about ecology are from reading Ulanowicz papers, but those have been so on point and beautiful that I feel I can proceed with confidence anyway.
  • I don’t think there’s any way to get around having at least a psychological model to work with when looking at these sorts of things. A recurring an promising angle is that of psychic integration. Carl Jung, who has inspired clinical practices that I can personally vouch for, and Gregory Bateson both understood the goal of personal growth to be integration of disparate elements. I’ve learned recently from Turner’s The Democratic Surround that Bateson was a more significant historical figure than I thought, unless Turner’s account of history is a glorification of intellectuals that appeal to him, which is entirely possible. Perhaps more importantly to me, Bateson inspired Ulanowicz, and so these theories are compatible; Bateson was also a cyberneticist following Wiener, who was prescient and either foundational to contemporary data science or a good articulator of its roots. But there is also a tie-in to constructivist epistemology. DiSessa’s epistemology, building on Piaget but embracing what he calls the computational metaphor, understands the learning of math and physics as the integration of phenomenological primitives.
  • The purpose of all this is ultimately protocol design.
  • This does not pertain directly to my dissertation, though I think it’s useful orienting context.

objectivity is powerful

Like “neoliberal”, “objectivity” in contemporary academic discourse is only used as a term of disparagement. It has fallen out of fashion to speak about “objectivity” in scientific language. It remains in fashion to be critical of objectivity in those disciplines that have been criticizing objectivity since at least the 70’s.

This is too bad because objectivity is great.

The criticism goes like this: scientists and journalists both used to say that they were being objective. There was a lot to this term. It could mean ‘disinterested’ or it could mean so rigorous as to be perfectly inter-subjective. It sounded good. But actually, all the scientists and journalists who claimed to be objective were sexist, racist, and lapdogs of the bourgeoisie. They used ‘objectivity’ as a way to exclude those who were interested in promoting social justice. Hence, anyone who claims to be objective is suspicious.

There are some more sophisticated arguments than this but their sophistication only weakens the main emotional thrust of the original criticism. The only reason for this sophistication is to be academically impressive, which is fundamentally useless, or to respond in good faith to criticisms, which is politically unnecessary and probably unwise.

Why is it unwise to respond in good faith to criticisms of a critique of objectivity? Because to concede that good faith response to criticism is epistemically virtuous would be to concede something to the defender of objectivity. Once you start negotiating with the enemy in terms of reasons, you become accountable to some kind of shared logic which transcends your personal subjectivity, or the collective subjectivity of those whose perspectives are channeled in your discourse.

In a world in which power is enacted and exerted through discourse, and in which cultural logics are just rules in a language game provisionally accepted by players, this rejection of objectivity is true resistance. The act of will that resists logical engagement with those in power will stymie that power. It’s what sticks it to the Man.

The problem is that however well-intentioned this strategy may be, it is dumb.

It is dumb because as everybody knows, power isn’t exerted mainly through discourse. Power is exerted through violence. And while it may be fun to talk about “cultural logics” if you are a particular kind of academic, and even fun to talk about how cultural logics can be violent, that is vague metaphorical poetry compared to something else that they could be talking about. Words don’t kill people. Guns kill people.

Put yourself in the position of somebody designing and manufacturing guns. What do you talk about with your friends and collaborators? If you think that power is about discourse, then you might think that these people talk about their racist political agenda, wherein they reproduce the power dynamics that they will wield to continue their military dominance.

They don’t though.

Instead what they talk about is the mechanics of how guns work and the technicalities of supply chain management. Where are they importing their gunpowder from and how much does it cost? How much will it go boom?

These conversations aren’t governed by “cultural logics.” They are governed by logic. Because logic is what preserves the intersubjective validity of their claims. That’s important because to successful build and market guns, the gun has to go boom the same amount whether or not the person being aimed at shares your cultural logic.

This is all quite grim. “Of course, that’s the point: objectivity is the language of violence and power! Boo objectivity!”

But that misses the point. The point is that it’s not that objectivity is what powerful people dupe people into believing in order to stay powerful. The point is that objectivity is what powerful people strive for in order to stay powerful. Objectivity is powerful in ways that more subjectively justified forms of knowledge are not.

This is not a popular perspective. There a number of reasons for this. One is that attain objective understanding is a lot of hard work and most people are just not up for it. Another is that there are a lot of people who have made their careers arguing for a much more popular perspective, which is that “objectivity” is associated with evil people and therefor we should reject it as an epistemic principal. There will always be an audience for this view, who will be rendered powerless by it and become the self-fulfilling prophecy of the demagogues who encourage their ignorance.

frustrations with machine ethics

It’s perhaps because of the contemporary two cultures problem of tech and the humanities that machine ethics is in such a frustrating state.

Today I read danah boyd’s piece in The Message about technology as an arbiter of fairness. It’s more baffling conflation of data science with neoliberalism. This time, the assertion was that the ideology of the tech industry is neoliberalism hence their idea of ‘fairness’ is individualist and against social fabric. It’s not clear what backs up these kinds of assertions. They are more or less refuted by the fact that industrial data science is obsessed with our network of ties for marketing reasons. If anybody understands the failure of the myth of the atomistic individual, it’s “tech folks,” a category boyd uses to capture, I guess, everyone from marketing people at Google to venture capitalists to startup engineers to IBM researchers. You know, the homogenous category that is “tech folks.”

This kind of criticism makes the mistake of thinking that a historic past is the right way to understand a rapidly changing present that is often more technically sophisticated than the critics understand. But critical academics have fallen into the trap of critiquing neoliberalism over and over again. One problem is that tech folks don’t spend a ton of time articulating their ideology in ways that are convenient for pop culture critique. Often their business models require rather sophisticated understandings of the market, etc. that don’t fit readily into that kind of mold.

What’s needed is substantive progress in computational ethics. Ok, so algorithms are ethically and politically important. What politics would you like to see enacted, and how do you go about implementing that? How do you do it in a way that attracts new users and is competitively funded so that it can keep up with the changing technology with which we use to access the web? These are the real questions. There is so little effort spent trying to answer them. Instead there’s just an endless series of op-ed bemoaning the way things continue to be bad because it’s easier than having agency about making things better.

more on algorithms, judgment, polarization

I’m still pondering the most recent Tufekci piece about algorithms and human judgment on Twitter. It prompted some grumbling among data scientists. Sweeping statements about ‘algorithms’ do that, since to a computer scientist ‘algorithm’ is about as general a term as ‘math’.

In later conversation, Tufekci clarified that when she was calling out the potential problems of algorithmic filtering of the Twitter newsfeed, she was speaking to the problems of a newsfeed curated algorithmically for the sake of maximizing ‘engagement’. Or ads. Or, it is apparent on a re-reading of the piece, new members. She thinks an anti-homophily algorithm would maybe be a good idea, but that this is so unlikely according to the commercial logic of Twitter to be a marginal point. And, meanwhile, she defends ‘human prioritizatin’ over algorithmic curation, despite the fact that homophily (not to mention preferential attachment) are arguable negative consequences of social system driven by human judgment.

I think inquiry into this question is important, but bound to be confusing to those who aren’t familiar in a deep way with network science, machine learning, and related fields. It’s also, I believe, helpful to have a background in cognitive science, because that’s a field which maintains that human judgment and computational systems are doing fundamentally commensurable kinds of work. When we think in sophisticated way about crowdsourced labor, we use this sort of thinking. We acknowledge, for example, that human brains are better at the computational task of image recognition, so then we employ Turkers to look at and label images. But those human judgments are then inputs to statistical proceses that verify and check those judgments against each other. Later, those determinations that result from a combination of human judgment and algorithmic processing could be used in a search engine–which returns answers to questions based on human input. Search engines, then, are also a way of combining human and purely algorithmic judgment.

What it comes down to is that virtually all of our interactions with the internet are built around algorithmic affordances. And these systems can be understood systematically if we reject the quantitative/qualitative divide at the ontological level. Reductive physicalism entails this rejection, but–and this is not to be underestated–pisses or alienates people who do qualitative or humanities research.

This is old news. C.P. Snow’s The Two Cultures. The Science Wars. We’ve been through this before. Ironically, the polarization is algorithmically visible in the contemporary discussion about algorithms.*

The Two Cultures on Twitter?

It’s I guess not surprising that STS and cultural studies academics are still around and in opposition to the hard scientists. What’s maybe new is how much computer science now affects the public, and how the popular press appears to have allied itself with the STS and cultural studies view. I guess this must be because cultural anthropologists and media studies people are more likely to become journalists and writers, whereas harder science is pretty abstruse.

There’s an interesting conflation now from the soft side of the culture wars of science with power/privilege/capitalism that plays out again and again. I bump into it in the university context. I read about it all the time. Tufekci’s pessimism that the only algorihtmic filtering Twitter would adopt would be one that essentially obeys the logic “of Wall Street” is, well, sad. It’s sad that an unfortunate pairing that is analytically contingent is historically determined to be so.

But there is also something deeply wrong about this view. Of course there are humanitarian scientists. Of course there is a nuanced center to the science wars “debate”. It’s just that the tedious framing of the science wars has been so pervasive and compelling, like a commercial jingle, that it’s hard to feel like there’s an audience for anything more subtle. How would you even talk about it?

* I need to confess: I think there was some sloppiness in that Medium piece. If I had had more time, I would have done something to check which conversations were actually about the Tufekci article, and which were just about whatever. I feel I may have misrepresented this in the post. For the sake of accessibility or to make the point, I guess. Also, I’m retrospectively skittish about exactly how distinct a cluster the data scientists were, and whether its insularity might have been an artifact of the data collection method. I’ve been building out poll.emic in fits mainly as a hobby. I built it originally because I wanted to at last understand Weird Twitter’s internal structure. The results were interesting but I never got to writing them up. Now I’m afraid that the culture has changed so much that I wouldn’t recognize it any more. But I digress. Is it even notable that social scientists from different disciplines would have very different social circles around them? Is the generalization too much? And are there enough nodes in this graph to make it a significant thing to say about anything, really? There could be thousands of academic tiffs I haven’t heard about that are just as important but which defy my expectations and assumptions. Or is the fact that Medium appears to have endorsed a particular small set of public intellectuals significant? How many Medium readers are there? Not as many as there are Twitter users, by several orders of magnitude, I expect. Who matters? Do academics matter? Why am I even studying these people as opposed to people who do more real things? What about all the presumabely sane and happy people who are not pathologically on the Internet? Etc.

a response to “Big Data and the ‘Physics’ of Social Harmony” by @doctaj; also Notes towards ‘Criticality as ideology';

I’ve been thinking over Robin James’ “Big Data & the ‘Physics’ of Social Harmony“, an essay in three sections. The first discusses Singapore’s use of data science to detect terrorists and public health threats for the sake of “social harmony,” as reported by Harris in Foreign Policy. The second ties together Plato, Pentland’s “social physics”, and neoliberalism. The last discusses the limits to individual liberty proposed by J.S. Mill. The author admits it’s “all over the place.” I get the sense that it is a draft towards a greater argument. It is very thought-provoking and informative.

I take issue with a number of points in the essay. Underlying my disagreement is what I think is a political difference about the framing of “data science” and its impact on society. Since I am a data science practitioner who takes my work seriously, I would like this framing to be nuanced, recognizing both the harm and help that data science can do. I would like the debate about data science to be more concrete and pragmatic so that practitioners can use this discussion as a guide to do the right thing. I believe this will require discussion of data science in society to be informed by a technical understanding of what data science is up to. However, I think it’s also very important that these discussions rigorously take up the normative questions surrounding data sciences’ use. It’s with this agenda that I’m interested in James’ piece.

James is a professor of Philosophy and Women’s/Gender Studies and the essay bears the hallmarks of these disciplines. Situated in a Western and primarily anglophone intellectual tradition, it draws on Plato and Mill for its understanding of social harmony and liberalism. At the same time, it has the political orientation common to Gender Studies, alluding to the gendered division of economic labor, at times adopting Marxist terminology, and holding suspicion for authoritarian power. Plato is read as being the intellectual root of a “particular neoliberal kind of social harmony” that is “the ideal that informs data science.” James contrasts this ideal with the ideal of individual liberty, as espoused and then limited by Mill.

Where I take issue with James is that I think this line of argument is biased by its disciplinary formation. (Since this is more or less a truism for all academics, I suppose this is less a rebuttal than a critique.) Where I believe this is most visible is in her casting of Singapore’s ideal of social harmony as an upgrade of Plato, via the ideology of neoliberalism. She does not not consider in the essay that Singapore’s ideal of social harmony might be rooted in Eastern philosophy, not Western philosophy. Though I have no special access or insight into the political philosophy of Singapore, this seems to me to be an important omission given that Singapore is ethnically 74.2% Chinese and with Buddhist plurality.

Social harmony is a central concept in Eastern, especially Chinese, philosophy with deep roots in Confucianism and Daoism. A great introduction for those with background in Western philosophy who are interested in the philosophical contributions of Confucius is Fingarette’s Confucius: The Secular as Sacred. Fingarette discusses how Confucian thought is a reaction to the social upheaval and war of Anciant China’s Warring States Period, roughly 475 – 221 BC. Out of these troubling social conditions, Confucian thought attempts to establish conditions for peace. These include ritualized forms of social interaction at whose center is a benevolent Emperor.

There are many parallels with Plato’s political philosophy, but Fingarette makes a point of highlighting where Confucianism is different. In particular, the role of social ritual and ceremony as the basis of society is at odds with Western individualism. Political power is not a matter of contest of wills but the proper enactment of communal rites. It is like a dance. Frequently, the word “harmony” is used in the translation of Confucian texts to refer to the ideal of this functional, peaceful ceremonial society and, especially, its relationship with nature.

A thorough analysis of use of data science for social control in light of Eastern philosophy would be an important and interesting work. I certainly haven’t done it. My point is simply that when we consider the use of data science for social control as a global phenomenon, it is dubious to see it narrowly in light of Western intellectual history and ideology. That includes rooting it in Plato, contrasting it with Mill, and characterizing it primarily as an expression of white neoliberalism. Expansive use of these Western tropes is a projection, a fallacy of “I think this way, therefore the world must.” This I submit is an occupational hazard of anyone who sees their work primarily as an analysis of critique of ideology.

In a lecture in 1965 printed in Knowledge and Human Interests, Habermas states:

The concept of knowledge-constitutive human interests already conjoins the two elements whose relation still has to be explained: knowledge and interest. From everyday experience we know that ideas serve often enough to furnish our actions with justifying motives in place of the real ones. What is called rationalization at this level is called ideology at the level of collective action. In both cases the manifest content of statements is falsified by consciousness’ unreflected tie to interests, despite its illusion of autonomy. The discipline of trained thought thus correctly aims at excluding such interests. In all the sciences routines have been developed that guard against the subjectivity of opinion, and a new discipline, the sociology of knowledge, has emerged to counter the uncontrolled influence of interests on a deeper level, which derive less from the individual than from the objective situation of social groups.

Habermas goes on to reflect on the interests driving scientific inquiry–“scientific” in the broadest sense of having to do with knowledge. He delineates:

  • Technical inquiry motivated by the drive for manipulation and control, or power
  • Historical-hermeneutic inquiry motivated by the drive to guide collective action
  • Critical, reflexive inquiry into how the objective situation of social groups controls ideology, motivated by the drive to be free or liberated

This was written in 1965. Habermas was positioning himself as a critical thinker; however, unlike some of the earlier Frankfurt School thinkers he drew on, he did maintained that technical power was an objective human interest. (see Bohman and Rehg) In the United States especially, criticality as a mode of inquiry took aim at the ideologies that aimed at white, bourgeois, and male power. Contemporary academic critique has since solidified as an academic discipline and wields political power. In particular, is frequently enlisted as an expression of the interests of marginalized groups. In so doing, academic criticality has (in my view regrettably) becomes mere ideology. No longer interested in being scientifically disinterested, it has become a tool of rationalization. It’s project is the articulation of changing historical conditions in certain institutionally recognized tropes. One of these tropes is the critique of capitalism, modernism, neoliberalism, etc. and their white male bourgeois heritage. Another is the feminist emphasis on domesticity as a dismissed form on economic production. This trope features in James’ analysis of Singapore’s ideal of social harmony:

Harris emphasizes that Singaporeans generally think that finely-tuned social harmony is the one thing that keeps the tiny city-state from tumbling into chaos. [1] In a context where resources are extremely scarce–there’s very little land, and little to no domestic water, food, or energy sources, harmony is crucial. It’s what makes society sufficiently productive so that it can generate enough commercial and tax revenue to buy and import the things it can’t cultivate domestically (and by domestically, I really mean domestically, as in, by ‘housework’ or the un/low-waged labor traditionally done by women and slaves/servants.) Harmony is what makes commercial processes efficient enough to make up for what’s lost when you don’t have a ‘domestic’ supply chain. (emphasis mine)

To me, this parenthetical is quite odd. There are other uses of the word “domestic” that do not specifically carry the connotation of women and slave/servants. For example, the economic idea of gross domestic product just means “an aggregate measure of production equal to the sum of the gross values added of all resident institutional units engaged in production (plus any taxes, and minus any subsidies, on products not included in the value of their outputs).” Included in that production is work done by men and high-wage laborers. To suggest that natural resources are primarily exploited by “domestic” labor in the ‘housework’ sense is bizarre given, say, agribusiness, industrial mining, etc.

There is perhaps an interesting etymological relationship here; does our use of ‘domestic’ in ‘domestic product’ have its roots in household production? I wouldn’t know. Does that same etymological root apply in Singapore? Was agriculture in East Asia traditionally the province of household servants in China and Southeast Asia (as opposed to independent farmers and their sons?)? Regardless, domestic economic production agricultural production is not housework now. So it’s mysterious that this detail should play a role in explaining Singapore’s emphasis on social harmony today.

So I think it’s safe to say that this parenthetical remark by James is due to her disciplinary orientation and academic focus. Perhaps it is a contortion to satisfy the audience of Cyborgology, which has a critical left-leaning politics. A Harris’s original article does not appear to support this interpretation. Rather, it only uses the word ‘harmony’ twice, and maintains a cultural sensitivity that James’ piece lacks, noting that Singapore’s use of data science may be motivated by a cultural fear of loss or risk.

The colloquial word kiasu, which stems from a vernacular Chinese word that means “fear of losing,” is a shorthand by which natives concisely convey the sense of vulnerability that seems coded into their social DNA (as well as their anxiety about missing out — on the best schools, the best jobs, the best new consumer products). Singaporeans’ boundless ambition is matched only by their extreme aversion to risk.

If we think that Harris is closer to the source here, then we do not need the projections of Western philosophy and neoliberal theory to explain what is really meant by Singapore’s use of data science. Rather, we can look to Singapore’s culture and perhaps its ideological origins in East Asian thinking. Confucius, not Plato.

* * *

If there it is a disciplinary bias to American philosophy departments, it is that they exist to reproduce anglophone philosophy. This is point that James has recently expressed herself…in fact while I have been in the process of writing this response.

Though I don’t share James’ political project, generally speaking I agree that effort spent of the reproduction of disciplinary terminology is not helpful to the philosophical and scientific projects. Terminology should be deployed for pragmatic reasons in service to objective interests like power, understanding, and freedom. On the other hand, language requires consistency to be effective, and education requires language. My own personal conclusion on is that the scientific project can only be sustained now through disciplinary collapse.

When James suggests that old terms like metaphysics and epistemology prevent the de-centering of the “white supremacist/patriarchal/capitalist heart of philosophy”, she perhaps alludes to her recent coinage of “epistemontology” as a combination of epistemology and ontology, as a way of designating what neoliberalism is. She notes that she is trying to understand neoliberalism as an ideology, not as a historical period, and finds useful the definition that “neoliberals think everything in the universe works like a deregulated, competitive, financialized capitalist market.”

However helpful a philosophical understanding of neoliberalism as market epistemontology might be, I wonder whether James sees the tension between her statements about rejecting traditional terminology that reproduces the philosophical discipline and her interest in preserving the idea of “neoliberalism” in a way that can be be taught in an introduction to philosophy class, a point she makes in a blog comment later. It is, perhaps, in the act of teaching that a discipline is reproduced.

The use of neoliberalism as a target of leftist academic critique has been challenged relatively recently. Craig Hickman, in a blog post about Luis Suarez-Villa, writes:

In fact Williams and Srinicek see this already in their first statement in the interview where they remind us that “what is interesting is that the neoliberal hegemony remains relatively impervious to critique from the standpoint of the latter, whilst it appears fundamentally unable to counter a politics which would be able to combat it on the terrain of modernity, technology, creativity, and innovation.” That’s because the ball has moved and the neoliberalist target has shifted in the past few years. The Left is stuck in waging a war it cannot win. What I mean by that is that it is at war with a target (neoliberalism) that no longer exists except in the facades of spectacle and illusion promoted in the vast Industrial-Media-Complex. What is going on in the world is now shifting toward the East and in new visions of technocapitalism of which such initiatives as Smart Cities by both CISCO (see here) and IBM and a conglomerate of other subsidiary firms and networking partners to build new 21st Century infrastructures and architectures to promote creativity, innovation, ultra-modernity, and technocapitalism.

Let’s face it capitalism is once again reinventing itself in a new guise and all the Foundations, Think-Tanks, academic, and media blitz hype artists are slowly pushing toward a different order than the older market economy of neoliberalism. So it’s time the Left begin addressing the new target and its ideological shift rather than attacking the boogeyman of capitalism’s past. Oh, true, the façade of neoliberalism will remain in the EU and U.S.A. and much of the rest of the world for a long while yet, so there is a need to continue our watchdog efforts on that score. But what I’m getting at is that we need to move forward and overtake this new agenda that is slowly creeping into the mix before it suddenly displaces any forms of resistance. So far I’m not sure if this new technocapitalistic ideology has even registered on the major leftist critiques beyond a few individuals like Luis Suarez-Villa. Mark Bergfield has a good critique of Suarez-Villa’s first book on Marx & Philosophy site: here.

In other words, the continuation of capitalist domination is due to its evolution relative to the stagnation of intellectual critiques of it. Or to put it another way, privilege is the capacity to evolve and not merely reproduce. Indeed, the language game of academic criticality is won by those who develop and disseminate new tropes through which to represent the interests of the marginalized. These privileged academics accomplish what Lyotard describes as “legitimation through paralogy.”

* * * * *

If James were working merely within academic criticality, I would be less interested in the work. But her aspirations appear to be higher, in a new political philosophy that can provide normative guidance in a world where data science is a technical reality. She writes:

Mill has already made–in 1859 no less–the argument that rationalizes the sacrifice of individual liberty for social harmony: as long as such harmony is enforced as a matter of opinion rather than a matter of law, then nobody’s violating anybody’s individual rights or liberties. This is, however, a crap argument, one designed to limit the possibly revolutionary effects of actually granting individual liberty as more than a merely formal, procedural thing (emancipating people really, not just politically, to use Marx’s distinction). For example, a careful, critical reading of On Liberty shows that Mill’s argument only works if large groups of people–mainly Asians–don’t get individual liberty in the first place. [2] So, critiquing Mill’s argument may help us show why updated data-science versions of it are crap, too. (And, I don’t think the solution is to shore up individual liberty–cause remember, individual liberty is exclusionary to begin with–but to think of something that’s both better than the old ideas, and more suited to new material/technical realities.)

It’s because of these more universalist ambitions that I think it’s fair to point out the limits of her argument. If a government’s idea of “social harmony” is not in fact white capitalist but premodern Chinese, if “neoliberalism” is no longer the dominant ideology but rather an idea of an ideology reproduced by a stagnating academic discipline, then these ideas will not help us understand what is going on in the contemporary world in which ‘data science’ is allegedly of such importance.

What would be better than this?

There is an empirical reality to the practices of data science. Perhaps it should be studied on its own terms, without disciplinary baggage.

picking a data backend for representing email in #python

I’m at a difficult crossroads with BigBang where I need to pick an appropriate data storage backend for my preprocessed mailing list data.

There are a lot of different aspects to this problem.

The first and most important consideration is speed. If you know anything about computer science, you know that it exists to quickly execute complex tasks that would take too long to do by hand. It’s odd writing that sentence since computational complexity considerations are so fundamental to algorithm design that this can go unspoken in most technical contexts. But since coming to grad school I’ve found myself writing for a more diverse audience, so…

The problem I’m facing is that in doing exploratory data analysis, I do not know all the questions I am going to ask yet. But any particular question will be impractical to ask unless I tune the underlying infrastructure to answer it. This chicken-and-egg problem means that the process of inquiry is necessarily constrained by the engineering options that are available.

This is not new in scientific practice. Notoriously, the field of economics in the 20th century was shaped by what was analytically tractable as formal, mathematical results. The nuance of contemporary modeling of complex systems is due largely to the fact that we now have computers to do this work for us. That means we can still have the intersubjectively verified rigor that comes with mathematization without trying to fit square pegs into round holes. (Side note: something mathematicians acknowledge that others tend to miss is that mathematics is based on dialectic proof and intersubjective agreement. This makes it much closer epistemologically to something like history as a discipline than it is to technical fields dedicated to prediction and control, like chemistry or structural engineering. Computer science is in many ways an extension of mathematics. Obviously, these formalizations are then applied to great effect. Their power comes from their deep intersubjective validity–in other words, their truth. Disciplines that have dispensed with intersubjective validity as a grounds for truth claims in favor of a more nebulous sense of diverse truths in a manifold of interpretation have difficulty understanding this and so are likely to see the institutional gains of computer scientists to be a result of political manipulation, as opposed to something more basic: mastery of nature, or more provacatively, use of force. This disciplinary disfunction is one reason why these groups see their influence erode.)

For example, I have determined that in order to implement a certain query on the data efficiently, it would be best if another query were constant time. One way to do this is to use a database with an index.

However, setting up a database is something that requires extra work on the part of the programmer and so makes it harder to reproduce results. So far I have been keeping my processed email data “in memory” after it is pulled from files on the file system. This means that I have access to the data within the programming environment I’m most comfortable with, without depending on an external or parallel process. Fewer moving parts means that it is simpler to do my work.

So there is a tradeoff between the computational time of the software as it executes and the time and attention is takes me (and others that want to reproduce my results) to set up the environment in which the software runs. Since I am running this as an open source project and hope others will build on my work, I have every reason to be lazy, in a certain sense. Every inconvenience I suffer is one that will be suffered by everyone that follows me. There is a Kantian categorical imperative to keep things as simple as possible for people, to take any complex procedure and replace it with a script, so that others can do original creative thinking, solve the next problem. This is the imperative that those of us embedded in this culture have internalized. (G. Coleman notes that there are many cultures of hacking; I don’t know how prevalent these norms are, to be honest; I’m speaking from my experience) It is what makes this social process of developing our software infrastructure a social one with a modernist sense of progress. We are part of something that is being built out.

There are also social and political considerations. I am building this project intentionally in a way that is embedded within the Scientific Python ecosystem, as they are also my object of study. Certain projects are trendy right now, and for good reason. At the Python Worker’s Party at Berkeley last Friday, I saw a great presentation of Blaze. Blaze is a project that allows programmers experienced with older idioms of scientific Python programming to transfer their skills to systems that can handle more data, like Spark. This is exciting for the Python community. In such a fast moving field with multiple interoperating ecosystems, there is always the anxiety that ones skills are no longer the best skills to have. Has your expertise been made obsolete? So there is a huge demand for tools that adapt one way of thinking to a new system. As more data has become available, people have engineered new sophisticated processing backends. Often these are not done in Python, which has a reputation for being very usable and accessible but slow to run in operation. Getting the usable programming interface to interoperate with the carefully engineered data backends is hard work, work that Matt Rocklin is doing while being paid by Continuum Analytics. That is sweet.

I’m eager to try out Blaze. But as I think through the questions I am trying to ask about open source projects, I’m realizing that they don’t fit easily into the kind of data processing that Blaze currently supports. Perhaps this is dense on my part. If I knew better what I was asking, I could maybe figure out how to make it fit. But probably, what I’m looking at is data that is not “big”, that does not need the kind of power that these new tools provide. Currently my data fits on my laptop. It even fits in memory! Shouldn’t I build something that works well for what I need it for, and not worry about scaling at this point?

But I’m also trying to think long-term. What happens if an when it does scale up? What if I want to analyze ALL the mailing list data? Is that “big” data?

“Premature optimization is the root of all evil.” – Donald Knuth

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