Digifesto

“the privatization of public functions”

An emerging theme from the conference on Trade Secrets and Algorithmic Systems was that legal scholars have become concerned about the privatization of public functions. For example, the use of proprietary risk assessment tools instead of the discretion of judges who are supposed to be publicly accountable is a problem. More generally, use of “trade secrecy” in court settings to prevent inquiry into software systems is bogus and moves more societal control into the realm of private ordering.

Many remedies were proposed. Most involved some kind of disclosure and audit to experts. The most extreme form of disclosure is making the software and, where it’s a matter of public record, training data publicly available.

It is striking to me to be encountering the call for government use of open source systems because…this is not a new issue. The conversation about federal use of open source software was alive and well over five years ago. Then, the arguments were about vendor lock-in; now, they are about accountability of AI. But the essential problem of whether core governing logic should be available to public scrutiny, and the effects of its privatization, have been the same.

If we are concerned with the reliability of a closed and large-scale decision-making process of any kind, we are dealing with problems of credibility, opacity, and complexity. The prospects of an efficient market for these kinds of systems are dim. These market conditions are the conditions of sustainability of open source infrastructure. Failures in sustainability are manifest as software vulnerabilities, which are one of the key reasons why governments are warned against OSS now, though the process of measurement and evaluation of OSS software vulnerability versus proprietary vulnerabilities is methodologically highly fraught.

Trade secrecy, “an FDA for algorithms”, a software bills of materials (SBOM) #SecretAlgos

At the Conference on Trade Secrets and Algorithmic Systems at NYU today, the target of most critiques is the use of trade secrecy by proprietary technology providers to prevent courts and the public from seeing the inner workings of algorithms that determine people’s credit scores, health care, criminal sentencing, and so on. The overarching theme is that sometimes companies will use trade secrecy to hide the ways that their software is bad, and that that is a problem.

In one panel, the question of whether an “FDA for Algorithms” is on the table–referring the Food and Drug Administration’s approval of pharmaceuticals. It was not dealt with in too much depth, which is too bad, because it is a nice example of how government oversight of potentially dangerous technology is managed in a way that respects trade secrecy.

According to this article, when filing for FDA approval, a company can declare some of their ingredients to be trade secrets. The upshot of that is that those trade secrets are not subject to FOIA requests. However, these ingredients are still considered when approval is granted by the FDA.

It so happens that in the cybersecurity policy conversation (more so than in privacy) the question of openness of “ingredients” to inspection has been coming up in a serious way. NTIA has been hosting multistakeholder meetings about standards and policy around Software Component Transparency. In particular they are encouraging standardizations of Software Bills of Materials (SBOM) like the Linux Foundation’s Software Package Data Exchange (SPDX). SPDX (and SBOM’s more generally) describe the “ingredients” in a software package at a higher level of resolution than exposing the full source code, but at a level specific enough useful for security audits.

It’s possible that a similar method could be used for algorithmic audits with fairness (i.e., nondiscrimination compliance) and privacy (i.e., information sharing to third-parties) in mind. Particular components could be audited (perhaps in a way that protects trade secrecy), and then those components could be listed as “ingredients” by other vendors.

The paradox of ‘data markets’

We often hear that companies are “selling out data”, or that we are “paying for services” with our data. Data brokers literally buy and sell data about people. There are other forms of expensive data sources or data sets. There is, undoubtedly, one or more data markets.

We know that classically, perfect competition in markets depends on perfect information. Buyers and sellers on the market need to have equal and instantaneous access to information about utility curves and prices in order for the market to price things efficiently.

Since the bread and butter of the data market is information asymmetry, we know that data markets can never be perfectly competitive. If it was, the data market would cease to exist, because the perfect information condition would entail that there is nothing to buy and sell.

Data markets therefore have to be imperfectly competitive. But since these are the markets that perfect information in other markets might depend on, this imperfection is viral. The vicissitudes of the data market are the vicissitudes of the economy in general.

The upshot is that the challenges of information economics are not only those that appear in special sectors like insurance markets. They are at the heart of all economic activity, and there are no equilibrium guarantees.

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.

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.