Digifesto

The Crevasse: a meditation on accountability of firms in the face of opacity as the complexity of scale

To recap:

(A1) Beneath corporate secrecy and user technical illiteracy, a fundamental source of opacity in “algorithms” and “machine learning” is the complexity of scale, especially scale of data inputs. (Burrell, 2016)

(A2) The opacity of the operation of companies using consumer data makes those consumers unable to engage with them as informed market actors. The consequence has been a “free fall” of market failure (Strandburg, 2013).

(A3) Ironically, this “free” fall has been “free” (zero price) for consumers; they appear to get something for nothing without knowing what has been given up or changed as a consequence (Hoofnagle and Whittington, 2013).

Comments:

(B1) The above line of argument conflates “algorithms”, “machine learning”, “data”, and “tech companies”, as is common in the broad discourse. That this conflation is possible speaks to the ignorance of the scholarly position on these topics, and ignorance that is implied by corporate secrecy, technical illiteracy, and complexity of scale simultaneously. We can, if we choose, distinguish between these factors analytically. But because, from the standpoint of the discourse, the internals are unknown, the general indication of a ‘black box’ organization is intuitively compelling.

(B1a) Giving in to the lazy conflation is an error because it prevents informed and effective praxis. If we do not distinguish between a corporate entity and its multiple internal human departments and technical subsystems, then we may confuse ourselves into thinking that a fair and interpretable algorithm can give us a fair and interpretable tech company. Nothing about the former guarantees the latter because tech companies operate in a larger operational field.

(B2) The opacity as the complexity of scale, a property of the functioning of machine learning algorithms, is also a property of the functioning of sociotechnical organizations more broadly. Universities, for example, are often opaque to themselves, because of their own internal complexity and scale. This is because the mathematics governing opacity as a function of complexity and scale are the same in both technical and sociotechnical systems (Benthall, 2016).

(B3) If we discuss the complexity of firms, as opposed the the complexity of algorithms, we should conclude that firms that are complex due to scale of operations and data inputs (including number of customers) will be opaque and therefore have strategic advantage in the market against less complex market actors (consumers) with stiffer bounds on rationality.

(B4) In other words, big, complex, data rich firms will be smarter than individual consumers and outmaneuver them in the market. That’s not just “tech companies”. It’s part of the MO of every firm to do this. Corporate entities are “artificial general intelligences” and they compete in a complex ecosystem in which consumers are a small and vulnerable part.

Twist:

(C1) Another source of opacity in data is that the meaning of data come from the causal context that generates it. (Benthall, 2018)

(C2) Learning causal structure from observational data is hard, both in terms of being data-intensive and being computationally complex (NP). (c.f. Friedman et al., 1998)

(C3) Internal complexity, for a firm, is not sufficient to be “all-knowing” about the data that is coming it; the firm has epistemic challenges of secrecy, illiteracy, and scale with respect to external complexity.

(C4) This is why many applications of machine learning are overrated and so many “AI” products kind of suck.

(C5) There is, in fact, an epistemic crevasse between all autonomous entities, each containing its own complexity and constituting a larger ecological field that is the external/being/environment for any other autonomy.

To do:

The most promising direction based on this analysis is a deeper read into transaction cost economics as a ‘theory of the firm’. This is where the formalization of the idea that what the Internet changed most are search costs (a kind of transaction cost) should be.

It would be nice if those insights could be expressed in the mathematics of “AI”.

There’s still a deep idea in here that I haven’t yet found the articulation for, something to do with autopoeisis.

References

Benthall, Sebastian. (2016) The Human is the Data Science. Workshop on Developing a Research Agenda for Human-Centered Data Science. Computer Supported Cooperative Work 2016. (link)

Sebastian Benthall. Context, Causality, and Information Flow: Implications for Privacy Engineering, Security, and Data Economics. Ph.D. dissertation. Advisors: John Chuang and Deirdre Mulligan. University of California, Berkeley. 2018.

Burrell, Jenna. “How the machine ‘thinks’: Understanding opacity in machine learning algorithms.” Big Data & Society 3.1 (2016): 2053951715622512.

Friedman, Nir, Kevin Murphy, and Stuart Russell. “Learning the structure of dynamic probabilistic networks.” Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence. Morgan Kaufmann Publishers Inc., 1998.

Hoofnagle, Chris Jay, and Jan Whittington. “Free: accounting for the costs of the internet’s most popular price.” UCLA L. Rev. 61 (2013): 606.

Strandburg, Katherine J. “Free fall: The online market’s consumer preference disconnect.” U. Chi. Legal F. (2013): 95.

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open source sustainability and autonomy, revisited

Some recent chats with Chris Holdgraf and colleagues at NYU interested in “critical digital infrastracture” have gotten me thinking again about the sustainability and autonomy of open source projects again.

I’ll admit to having had naive views about this topic in the past. Certainly, doing empirical data science work on open source software projects has given me a firmer perspective on things. Here are what I feel are the hardest earned insights on the matter:

  • There is tremendous heterogeneity in open source software projects. Almost all quantitative features of these projects fall in log-normal distributions. This suggests that the keys to open source software success are myriad and exogenous (how the technology fits in the larger ecosystem, how outside funding and recognition is accomplished, …) rather than endogenous factors (community policies, etc.) While many open source projects start as hobby and unpaid academic projects, those that go on to be successful find one or more funding sources. This funding is an exogenous factor.
  • The most significant exogenous factors to an open source software project’s success are the industrial organization of private tech companies. Developing an open technology is part of the strategic repertoire of these companies: for example, to undermine the position of a monopolist, developing an open source alternative decreases barriers to market entry and allows for a more competitive field in that sector. Another example: Google funded Mozilla for so long arguably to deflect antitrust action over Google Chrome.
  • There is some truth to Chris Kelty’s idea of open source communities as recursive publics, cultures that have autonomy that can assert political independence at the boundaries of other political forces. This autonomy comes from: the way developers of OSS get specific and valuable human capital in the process of working with the software and their communities; the way institutions begin to depend on OSS as part of their technical stack, creating an installed base; and how many different institutions may support the same project, creating competition for the scarce human capital of the developers. Essentially, at the point where the software and the skills needed to deploy it effectively and the community of people with those skills is self-organized, the OSS community has gained some economic and political autonomy. Often this autonomy will manifest itself in some kind of formal organization, whether a foundation, a non-profit, or a company like Redhat or Canonical or Enthought. If the community is large and diverse enough it may have multiple organizations supporting it. This is in principle good for the autonomy of the project but may also reflect political tensions that can lead to a schism or fork.
  • In general, since OSS development is internally most often very fluid, with the primary regulatory mechanism being the fork, the shape of OSS communities is more determined by exogenous factors than endogenous ones. When exogenous demand for the technology rises, the OSS community can find itself with a ‘surplus’, which can be channeled into autonomous operations.

What proportion of data protection violations are due to “dark data” flows?

“Data protection” refers to the aspect of privacy that is concerned with the use and misuse of personal data by those that process it. Though widely debated, scholars continue to converge (e.g.) on ideal data protection consisting of alignment between the purposes the data processor will use the data for and the expectations of the user, along with collection limitations that reduce exposure to misuse. Through its extraterritorial enforcement mechanism, the GDPR has threatened to make these standards global.

The implication of these trends is that there will be a global field of data flows regulated by these kinds of rules. Many of the large and important actors that process user data can be held accountable to the law. Privacy violations by these actors will be due to a failure to act within the bounds of the law that applies to them.

On the other hand, there is also cybercrime, an economy of data theft and information flows that exists “outside the law”.

I wonder what proportion of data protection violations are due to dark data flows–flows of personal data that are handled by organizations operating outside of any effective regulation.

I’m trying to draw an analogy to a global phenomenon that I know little about but which strikes me as perhaps more pressing than data protection: the interrelated problems of money laundering, off-shore finance, and dark money contributions to election campaigns. While surely oversimplifying the issue, my impression is that the network of financial flows can be divided into those that are more and less regulated by effective global law. Wealth seeks out these opportunities in the dark corners.

How much personal data flows in these dark networks? And how much is it responsible for privacy violations around the world? Versus how much is data protection effectively in the domain of accountable organizations (that may just make mistakes here and there)? Or is the dichotomy false, with truly no firm boundary between licit and illicit data flow networks?

the resilience of agonistic control centers of global trade

This post is merely notes; I’m fairly confident that I don’t know what I’m writing about. However, I want to learn more. Please recommend anything that could fill me in about this! I owe most of this to discussion with a colleague who I’m not sure would like to be acknowledged.

Following the logic of James Beniger, an increasingly integrated global economy requires more points of information integration and control.

Bourgeois (in the sense of ‘capitalist’) legal institutions exist precisely for the purpose of arbitrating between merchants.

Hence, on the one hand we would expect international trade law to be Habermasian. However, international trade need not rest on a foundation of German idealism (which increasingly strikes me as the core of European law). Rather, it is an evolved mechanism.

A key part of this mechanism, as I’ve heard, is that it is decentered. Multiple countries compete to be the sites of transnational arbitration, much like multiple nations compete to be tax havens. Sovereignty and discretion are factors of production in the economy of control.

This means, effectively, that one cannot defeat capitalism by chopping off its head. It is rather much more like a hydra: the “heads” are the creation of two-sided markets. These heads have no internalized sense of the public good. Rather, they are optimized to be attractive to the transnational corporations in bilateral negotiation. The plaintiffs and defendants in these cases are corporations and states–social forms and institutions of complexity far beyond that of any individual person. This is where, so to speak, the AI’s clash.

For a more ethical Silicon Valley, we need a wiser economics of data

Kara Swisher’s NYT op-ed about the dubious ethics of Silicon Valley and Nitasha Tiku’s WIRED article reviewing books with alternative (and perhaps more cynical than otherwise stated) stories about the rise of Silicon Valley has generated discussion and buzz among the tech commentariat.

One point of debate is whether the focus should be on “ethics” or on something more substantively defined, such as human rights. Another point is whether the emphasis should be on “ethics” or on something more substantively enforced, like laws which impose penalties between 1% and 4% of profits, referring of course to the GDPR.

While I’m sympathetic to the European approach (laws enforcing human rights with real teeth), I think there is something naive about it. We have not yet seen whether it’s ever really possible to comply with the GDPR could wind up being a kind of heavy tax on Big Tech companies operating in the EU, but one that doesn’t truly wind up changing how people’s data are used. In any case, the broad principles of European privacy are based on individual human dignity, and so they do not take into account the ways that corporations are social structures, i.e. sociotechnical organizations that transcend individual people. The European regulations address the problem of individual privacy while leaving mystified the question of why the current corporate organization of the world’s personal information is what it is. This sets up the fight over ‘technology ethics’ to be a political conflict between different kinds of actors whose positions are defined as much by their social habitus as by their intellectual reasons.

My own (unpopular!) view is that the solution to our problems of technology ethics are going to have to rely on a better adapted technology economics. We often forget today that economics was originally a branch of moral philosophy. Adam Smith wrote The Theory of Moral Sentiments (1759) before An Inquiry into the Nature and Causes of the Wealth of Nations (1776). Since then the main purpose of economics has been to intellectually grasp the major changes to society due to production, trade, markets, and so on in order to better steer policy and business strategy towards more fruitful equilibria. The discipline has a bad reputation among many “critical” scholars due to its role in supporting neoliberal ideology and policies, but it must be noted that this ideology and policy work is not entirely cynical; it was a successful centrist hegemony for some time. Now that it is under threat, partly due to the successes of the big tech companies that benefited under its regime, it’s worth considering what new lessons we have to learn to steer the economy in an improved direction.

The difference between an economic approach to the problems of the tech economy and either an ‘ethics’ or a ‘law’ based approach is that it inherently acknowledges that there are a wide variety of strategic actors co-creating social outcomes. Individual “ethics” will not be able to settle the outcomes of the economy because the outcomes depend on collective and uncoordinated actions. A fundamentally decent person may still do harm to others due to their own bounded rationality; “the road to hell is paved with good intentions”. Meanwhile, regulatory law is not the same as command; it is at best a way of setting the rules of a game that will be played, faithfully or not, by many others. Putting regulations in place without a good sense of how the game will play out differently because of them is just as irresponsible as implementing a sweeping business practice without thinking through the results, if not more so because the relationship between the state and citizens is coercive, not voluntary as the relationship between businesses and customers is.

Perhaps the biggest obstacle to shifting the debate about technology ethics to one about technology economics is that it requires a change in register. It drains the conversation of the pathos which is so instrumental in surfacing it as an important political topic. Sound analysis often ruins parties like this. Nevertheless, it must be done if we are to progress towards a more just solution to the crises technology gives us today.

Privacy of practicing high-level martial artists (BJJ, CI)

Continuing my somewhat lazy “ethnographic” study of Brazilian Jiu Jitsu, an interesting occurrence happened the other day that illustrates something interesting about BJJ that is reflective of privacy as contextual integrity.

Spencer (2016) has accounted for the changes in martial arts culture, and especially Brazilian Jiu Jitsu, due to the proliferation of video on-line. Social media is now a major vector for the skill acquisition in BJJ. It is also, in my gym, part of the social experience. A few dedicated accounts on social media platforms that share images and video from the practice. There is a group chat where gym members cheer each other on, share BJJ culture (memes, tips), and communicate with the instructors.

Several members have been taking pictures and videos of others in practice and sharing them to the group chat. These are generally met with enthusiastic acclaim and acceptance. The instructors have also been inviting in very experienced (black belt) players for one-off classes. These classes are opportunities for the less experienced folks to see another perspective on the game. Because it is a complex sport, there are a wide variety of styles and in general it is exciting and beneficial to see moves and attitudes of masters besides the ones we normally train with.

After some videos of a new guest instructor were posted to the group chat, one of the permanent instructors (“A”) asked not to do this:

A: “As a general rule of etiquette, you need permission from a black belt and esp if two black belts are rolling to record them training, be it drilling not [sic] rolling live.”

A: “Whether you post it somewhere or not, you need permission from both to record then [sic] training.”

B: “Heard”

C: “That’s totally fine by me, but im not really sure why…?

B: “I’m thinking it’s a respect thing.”

A: “Black belt may not want footage of him rolling or training. as a general rule if two black belts are training together it’s not to be recorded unless expressly asked. if they’re teaching, that’s how they pay their bills so you need permission to record them teaching. So either way, you need permission to record a black belt.”

A: “I’m just clarifying for everyone in class on etiquette, and for visiting other schools. Unless told by X, Y, [other gym staff], etc., or given permission at a school you’re visiting, you’re not to record black belts and visiting upper belts while rolling and potentially even just regular training or class. Some schools take it very seriously.”

C: “OK! Totally fine!”

D: “[thumbs up emoji] gots it :)”

D: “totally makes sense”

A few observations on this exchange.

First, there is the intriguing point that for martial arts black belts teaching, their instruction is part of their livelihood. The knowledge of the expert martial arts practitioner is hard-earned and valuable “intellectual property”, and it is exchanged through being observed. Training at a gym with high-rank players is a privilege that lower ranks pay for. The use of video recording has changed the economy of martial arts training. This has in many ways opened up the sport; it also opens up potential opportunities for the black belt in producing training videos.

Second, this is framed as etiquette, not as a legal obligation. I’m not sure what the law would say about recordings in this case. It’s interesting that as a point of etiquette, it applies only to videos of high belt players. Recording low belt players doesn’t seem to be a problem according to the agreement in the discussion. (I personally have asked not to be recorded at one point at the gym when an instructor explicitly asked to be recorded in order to create demo videos. This was out of embarrassment at my own poor skills; I was also feeling badly because I was injured at the time. This sort of consideration does not, it seem, currently operate as privacy etiquette within the BJJ community. Perhaps these norms are currently being negotiated or are otherwise in flux.)

Third, there is a sense in which high rank in BJJ comes with authority and privileges that do not require any justification. The “trainings are livelihood” argument does apply directly to general practice roles; the argument is not airtight. There is something else about the authority and gravitas of the black belt that is being preserved here. There is a sense of earned respect. Somehow this translates into a different form of privacy (information flow) norm.

References

Spencer, D. C. (2016). From many masters to many Students: YouTube, Brazilian Jiu Jitsu, and communities of practice. Jomec Journal, (5).

Brazilian Jiu Jitsu (BJJ) and the sociology of martial knowledge

Maybe 15 months ago, I started training in Brazilian Jiu Jitsu (BJJ), a martial art that focuses on grappling and ground-fighting. Matches are won through points based on position (e.g., “mount”, where you are sitting on somebody else) and through submission, when a player taps out due to hyperextension under a joint lock or asphyxiation by choking. I recommend it heartily to anybody as a fascinating, smart workout that also has a vibrant and supportive community around it.

One of the impressive aspects of BJJ, which differentiates it from many other martial arts, is its emphasis on live drilling and sparring (“rolling”), which can offer a third or more of a training session. In the context of sparring, there is opportunity for experimentation and rapid feedback about technique. In addition to being good fun and practice, regular sparring continually reaffirms the hierarchical ranking of skill. As in some other martial arts, rank is awarded as different colored “belts”–white, blue, purple, brown, black. Intermediary progress is given as “stripes” on the belt. White belts can spar with higher belts; more often than not, when they do so they get submitted.

BJJ also has tournaments, which allow players from different dojos to compete against each other. I attended my first tournament in August and thought it was a great experience. There is nothing like meeting a stranger for the first time and then engage them in single combat to kindle a profound respect for the value of sportsmanship. Off the mat, I’ve had some of the most courteous encounters with anybody I have ever met in New York City.

At tournaments, hundreds of contestants are divided into brackets. The brackets are determined by belt (white, blue, etc.), weight (up to 155 lbs, up to 170 lbs, etc.), sex (men and women), and age (kids age groups, adult, 30+ adult). There is an “absolute” bracket for those who would rise above the division of weight classes. There are “gi” and “no gi” variants of BJJ; the former requires wearing special uniform of jacket and pants, which are used in many techniques.

Overall, it is an efficient system for training a skill.


The few readers of this blog will recall that for some time I studied sociology of science and engineering, especially through the lens of Bourdieu’s Science of Science and Reflexivity. This was in turn a reaction to a somewhat startling exposure to sociology of science and education, and intellectual encounter that I never intended to have. I have been interested for a long time in the foundations of science. It was a rude shock, and one that I mostly regret, to have gone to grad school to become a better data scientist and find myself having to engage with the work of Bruno Latour. I did not know how to respond intellectually to the attack on scientific legitimacy on the basis that its self-understanding is insufficiently sociological until encountering Bourdieu, who refuted the Latourian critique and provides a clear-sighted view of how social structure under-girds scientific objectivity, when it works. Better was my encounter with Jean Lave, who introduced me to more phenomenological methods for understanding education through her class and works (Chaiklin and Lave, 1996). This made me more aware of the role of apprenticeship as well as the nuances of culture, framing, context, and purpose in education. Had I not encountered this work, I would likely never have found my way to Contextual Integrity, which draws more abstract themes about privacy from such subtle observations.

Now it’s impossible for me to do something as productive and enjoyable as BJJ without considering it through these kinds of lenses. One day I would like to do more formal work along these lines, but as has been my habit I have a few notes to jot down at the moment.

The first point, which is a minor one, is that there is something objectively known by experienced BJJ players, and that this knowledge is quintessentially grounded in intersubjective experience. The sparring encounter is the site at which technique is tested and knowledge is confirmed. Sparring simulates conditions of a fight for survival; indeed, if a choke is allowed to progress, a combatant can lose consciousness on the mat. This recalls Hegel’s observation that it is in single combat that a human being is forced to see the limits of their own solipsism. When the Other can kill you, that is an Other that you must see as, in some sense, equivalent in metaphysical status to oneself. This is a sadly forgotten truth in almost every formal academic environment I’ve found myself in, and that, I would argue, is why there is so much bullshit in academia. But now I digress.

The second point, which is perhaps more significant, is that BJJ has figured out how to be an inclusive field of knowledge despite the pervasive and ongoing politics of what I have called in another post body agonism. We are at a point where political conflict in the United States and elsewhere seems to be at root about the fact that people have different kinds of bodies, and these differences are upsetting for liberalism. How can we have functioning liberal society when, for example, some people have male bodies and other people have female bodies? It’s an absurd question, perhaps, but nevertheless it seems to be the question of the day. It is certainly a question that plagues academic politics.

BJJ provides a wealth of interesting case studies in how to deal productively with body agonism. BJJ is an unarmed martial art. The fact that there are different body types is an instrinsic aspect of the sport. Interestingly, in the dojo practices I’ve seen, trainings are co-ed and all body types (e.g., weight classes) train together. This leads to a dynamic and irregular practice environment that perhaps is better for teaching BJJ as a practical form of self-defense. Anecdotally, self-defense is an important motivation for why especially women are interested in BJJ, and in the context of a gym, sparring with men is a way to safely gain practical skill in defending against male assailants. On the other hand, as far as ranking progress is concerned, different bodies are considered in relation to other similar bodies through the tournament bracket system. While I know a badass 40-year old who submitted two college kids in the last tournament, that was extra. For the purposes of measuring my improvement in the discipline, I will be in the 30+ men’s bracket, compared with other guys approximately my weight. The general sense within the community is that progress in BJJ is a function of time spent practicing (something like the mantra that it takes 10,000 hours to master something), not any other intrinsic talent. Some people who are more dedicated to their training advance faster, and others advance slower.

Training in BJJ has been a positive experience for me, and I often wonder whether other social systems could be more like BJJ. There are important lessons to be learned from it, as it is a mental discipline, full of subtlety and intellectual play, in its own right.

References

Bourdieu, Pierre. Science of science and reflexivity. Polity, 2004.

Chaiklin, Seth, and Jean Lave, eds. Understanding practice: Perspectives on activity and context. Cambridge University Press, 1996.

On Hill’s work on ‘Greater Male Variability Hypothesis’ (GMVH)

I’m writing in response to Ted Hill’s recent piece describe the acceptance and subsequent removal of a paper about the ‘Greater Male Variability Hypothesis’, the controversial idea that there is more variability in male intelligence than female intelligence, i.e. “that there are more idiots and more geniuses among men than among women.”

I have no reason to doubt Hill’s account of events–his collaboration, his acceptance to a journal, and the mysterious political barriers to publication–and assume them for the purposes of this post. If these are refuted by future controversy somehow, I’ll stand corrected.

The few of you who have followed this blog for some time will know that I’ve devoted some energy to understanding the controversy around gender and STEM. One post, criticizing how Donna Haraway, widely used in Science and Technology Studies, can be read as implying that women should not become ‘hard scientists’ in the mathematical mode, has gotten a lot of hits (and some pushback). Hill’s piece makes me revisit the issue.

The paper itself is quite dry and the following quote is its main thesis:

SELECTIVITY-VARIABILITY PRINCIPLE. In a species with two sexes A and B, both of which are needed for reproduction, suppose that sex A is relatively selective, i.e., will mate only with a top tier (less than half ) of B candidates. Then from one generation to the next, among subpopulations of B with comparable average attributes, those with greater variability will tend to prevail over those with lesser variability. Conversely, if A is relatively non-selective, accepting all but a bottom fraction (less than half ) of the opposite sex, then subpopulations of B with lesser variability will tend to prevail over those with comparable means and greater variability.

This mathematical thesis is supported in the paper by computational simulations and mathematical proofs. From this, one can get the GMVH if one assumes that: (a) (human) males are less selective in their choice of (human) females when choosing to mate, and (b) traits that drive variability in intelligence are intergenerationally heritable, whether biologically or culturally. While not uncontroversial, neither of these are crazy ideas. In fact, if they weren’t both widely accepted, then we wouldn’t be having this conversation.

Is this the kind of result that should be published? This is the controversy. I am less interested in the truth or falsehood of broad implications of the mathematical work than I am in the arguments for why the mathematical work should not be published (in a mathematics journal).

As far as I can tell from Hill’s account and also from conversations and cultural osmosis on the matter, there are a number of reasons why research of this kind should not be published.

The first reason might be that there are errors in the mathematical or simulation work. In other words, the Selectivity-Variability Principle may be false, and falsely supported. If that is the case, then the reviewers should have rejected the paper on those grounds. However, the principle is intuitively plausible and the reviewers accepted it. Few of Hill’s critics (though some) attacked the piece on mathematical grounds. Rather, the objections were of a social and political nature. I want to focus on these latter objections, though if there is a mathematical refutation of the Selectivity-Variability Principle I’m not aware of, I’ll stand corrected.

The crux of the problem seems to be this: the two assumptions (a) and (b) are both so plausible that publishing a defense of (c) the Selectivity-Variability Principle would imply (d) the Greater Male Variability Hypothesis (GMVH). And if GMVH is true, then (e) there is a reason why more of the celebrated high-end of the STEM professions are male. It is because at the high-end, we’re looking at the thin tails of the human distribution, and the male tail is longer. (It is also longer at the low end, but nobody cares about the low end.)

The argument goes that if this claim (e) were widely known by aspiring females in STEM fields, then they will be discouraged from pursuing these promising careers, because “women have a lesser chance to succeed in mathematics at the very top end”, which would be a biased, sexist view. (e) could be used to defend the idea that (f) normatively, there’s nothing wrong with men having most success at the top end of mathematics, though there is a big is/ought distinction there.

My concern with this argument is that it assumes, at its heart, the idea that women aspiring to be STEM professionals are emotionally vulnerable to being dissuaded by this kind of mathematical argument, even when it is neither an empirical case (it is a mathematical model, not empirically confirmed within the paper) nor does it reflect on the capacity of any particular woman, and especially not after she has been selected for by the myriad social sorting mechanisms available. The argument that GMVH is professionally discouraging assumes many other hypotheses about human professional motivation, for example, the idea that it is only worth taking on a profession if one can expect to have a higher-than-average chance of achieving extremely high relative standing in that field. Given that extremely high relative standing in any field is going to be rare, it’s hard to say this is a good motivation for any profession, for men or for women, in the long run. In general, those that extrapolate from population level gender tendencies to individual cases are committing the ecological fallacy. It is ironic that under the assumption of the critics, potential female entrants into STEM might be screened out precisely because of their inability to understand a mathematical abstraction, along with its limitations and questionable applicability, through a cloud of political tension. Whereas if one were really interested in reaching mathematics in an equitable way, that would require teaching the capacity to see through political tension to the precise form of a mathematical abstraction. That is precisely what top performance in the STEM field should be about, and that it should be unflinchingly encouraged as part of the educational process for both men and women.

My point, really, is this: the argument that publishing and discussing GMVH is detrimental to the career aspirations of women, because of how individual women will internalize the result, depends on a host of sexist assumptions that are as if not more pernicious than GMVH. It is based on the idea that women as a whole need special protection from mathematical ideas in order to pursue careers in mathematics, which is self-defeating crazy talk if I’ve ever heard it. The whole point of academic publication is to enable a debate of defeasible positions on their intellectual merits. In the case of mathematics research, the standards of merit are especially clear. If there’s a problem with Hill’s model, that’s a great opportunity for another, better model, on a topic that is clearly politically and socially relevant. (If the reviewers ignored a lot prior work that settled the scientific relevance of the question, then that’s a different story. One gathers that is not what happened.)

As a caveat, there are other vectors through which GMVH could lead to bias against women pursuing STEM careers. For example, it could bias their less smart families or colleagues into believing less in their potential on the basis of their sex. But GMVH is about the variance, not the mean, of mathematical ability. So the only population that it’s relevant to is that in the very top tier of performers. That nuance is itself probably beyond the reach of most people who do not have at least some training in STEM, and indeed if somebody is reasoning from GMVH to an assumption about women’s competency in math then they are almost certainly conflating it with a dumber hypothesis about population means which is otherwise irrelevant.

This is perhaps the most baffling thing about this debate: that it boils down to a very rarefied form of elite conflict. “Should a respected mathematics journal publish a paper that implies that there is greater variance in mathematical ability between sexes based on their selectivity and therefore…” is a sentence that already selects for a very small segment of the population, a population that should know better than to censor a mathematical proof rather than to take the opportunity to engage it as an opportunity to educate people in STEM and why it is an interesting field. Nobody is objecting to the publication of support for GMVH on the grounds that it implies that more men are grossly incompetent and stupid than women, and it’s worth considering why that is. If our first reaction to GMVH is “but can no one woman never be the best off?”, we are showing that our concerns lie with who gets to be on top, not the welfare of those on bottom.

Note on Austin’s “Cyber Policy in China”: on the emphasis on ‘ethics’

I’ve had recommended to me Greg Austin’s “Cyber Policy in China” (2014) as a good, recent work. I am not sure what I was expecting–something about facts and numbers, how companies are being regulated, etc. Just looking at the preface, it looks like this book is about something else.

The preface frames the book in the discourse, beginning in the 20th century, about the “information society”. It explicitly mentions the UN’s World Summit on the Information Society (WSIS) as a touchstone of international consensus about what the information society is, as society “where everyone can create, access, utilise and share information and knowledge’ to ‘achieve their full potential’ in ‘improving their quality of life’. It is ‘people-centered’.

In Chinese, the word for information society is xinxi shehui (Please forgive me: I’ve got little to know understanding of the Chinese language and that includes not knowing how to put the appropriate diacritics into transliterations of Chinese terms.) It is related to a term “informatization” (xinxihua) that is compared to industrialization. It means the historical process by which information technology is fully used, information resources are developed and utilized, the exchange of information and knowledge sharing are promoted, the quality of economic growth is improved, and the transformation of economic and social development is promoted”. Austin’s interesting point is that this is “less people-centered than the UN vision and more in the mould of the materialist and technocratic traditions that Chinese Communists have preferred.”

This is an interesting statement on the difference between policy articulations by the United Nations and the CCP. It does not come as a surprise.

What did come as a surprise is how Austin chooses to orient his book.

On the assumption that outcomes in the information society are ethically determined, the analytical framework used in the book revolves around ideal policy values for achieving an advanced information society. This framework is derived from a study of ethics. Thus, the analysis is not presented as a work of social science (be that political science, industry policy or strategic studies). It is more an effort to situate the values of China’s leaders within an ethical framework implied by their acceptance of the ambition to become and advanced information society.

This comes as a surprise to me because what I was expected from a book titled “Cyber Policy in China” is really something more like industry policy or strategic studies. I was not ready for, and am frankly a bit disappointed by, the idea that this is really a work of applied philosophy.

Why? I do love philosophy as a discipline and have studied it carefully for many years. I’ve written and published about ethics and technological design. But my conclusion after so much study is that “the assumption that outcomes in the information society are ethically determined” is totally incorrect. I have been situated for some time in discussions of “technology ethics” and my main conclusion from them is that (a) “ethics” in this space are more often than not an attempt to universalize what are more narrow political and economic interests, and that (b) “ethics” are constantly getting compromised by economic motivations as well as the mundane difficulty of getting information technology to work as it is intended to in a narrow, functionally defined way. The real world is much bigger and more complex than any particular ethical lens can take in. Attempt to define technological change in terms of “ethics” are almost always a political maneuver, for good or for ill, of some kind that is reducing the real complexity of technological development into a soundbite. A true ethical analysis of cyber policy would need to address industrial policy and strategic aspects, as this is what drives the “cyber” part of it.

The irony is that there is something terribly un-emic about this approach. By Austin’s own admission, the CCP cyber policy is motivated by material concerns about the distribution of technology and economic growth. Austin could have approached China’s cyber policy in the technocratic terms they see themselves in. But instead Austin’s approach is “human-centered”, with a focus on leaders and their values. I already doubt the research on anthropological grounds because of the distance between the researcher and the subjects.

So I’m not sure what to do about this book. The preface makes it sound like it belongs to a genre of scholarship that reads well, and maybe does important ideological translation work, but does provide something like scientific knowledge of China’s cyber policy, which is what I’m most interested in. Perhaps I should move on, or take other recommendations for reading on this topic.

How trade protection can increase labor wages (the Stolper-Samuelson theorem)

I’m continuing a look into trade policy 8/08/30/trade-policy-and-income-distribution-effects/”>using Corden’s (1997) book on the topic.

Picking up where the last post left off, I’m operating on the assumption that any reader is familiar with the arguments for free trade that are an extension of those arguments of laissez-faire markets. I will assume that these arguments are true as far as they go: that the economy grows with free trade, that tariffs create a dead weight loss, that subsidies are expensive, but that both tariffs and subsidies do shift the market towards imports.

The question raised by Corden is why, despite its deleterious effects on the economy as a whole, protectionism enjoys political support by some sectors of the economy. He hints, earlier in Chapter 5, that this may be due to income distribution effects. He clarifies this with reference to an answer to this question that was given as early as 1941 by Stolper and Samuelson; their result is now celebrated as the Stolper-Samuelson theorem.

The mathematics of the theorem can be read in many places. Like any economic model, it depends on some assumptions that may or may not be the case. Its main advantage is that it articulates how it is possible for protectionism to benefit a class of the population, and not just in relative but in absolute terms. It does this by modeling the returns to different factors of production, which classically have been labor, land, and capital.

Roughly, the argument goes like this. Suppose and economy has two commodities, one for import and one for export. Suppose that the imported good is produced with a higher labor to land ratio than the export good. Suppose a protectionist policy increases the amount of the import good produced relative to the export good. Then the return on labor will increase (because more labor is used in supply), and the return on land will decrease (because less land is used in supply). Wages will increase and rent on land will decrease.

These breakdowns of the economy into “factors of production” feels very old school. You rarely read economists discuss the economy in these terms now, which is itself interesting. One reason why (and I am only speculating here) is that these models clarify how laborers, land-owners, and capital-owners have different political interests in economic intervention, and that can lead to the kind of thinking that was flushed out of the American academy during the McCarthy era. Another reason may be that “capital” has changed meaning from being about ownership of machine goods into being about having liquid funds available for financial investment.

I’m interested in these kinds of models today partly because I’m interested in the political interests in various policies, and also because I’m interested in particular in the economics of supply chain logistics. The “factors of production” approach is a crude way to model the ‘supply chain’ in a broad sense, but one that has proven to be an effective source of insights in the past.

References

Corden, W. Max. “Trade policy and economic welfare.” OUP Catalogue (1997).

Stolper, Wolfgang F., and Paul A. Samuelson. “Protection and real wages.” The Review of Economic Studies 9.1 (1941): 58-73.