“Transactions that are too complex…to be allowed to exist.” cf @FrankPasquale

by Sebastian Benthall

I stand corrected; my interpretation of Pasquale in my last post was too narrow. Having completed Chapter One of The Black Box Society (TBBS), Pasquale does not take the naive view that all organizational secrecy should be abolished, as I might have once. Rather, his is a more nuanced perspective.

First, Pasquale distinguishes between three “critical strategies for keeping black boxes closed”, or opacity, “[Pasquale’s] blanket term for remediable incomprehensibility”:

  • Real secrecy establishes a barrier between hidden content and unauthorized access to it.”
  • Legal secrecy obliges those privy to certain information to keep it secret”
  • Obfuscation involves deliberate attempts at concealment when secrecy has been compromised.”

Cutting to the chase by looking at the Pasquale and Bracha “Federal Search Commission” (2008) paper that a number of people have recommended to me, it appears (in my limited reading so far) that Pasquale’s position is not that opacity in general is a problem (because there are of course important uses of opacity that serve the public interest, such as confidentiality). Rather, despite these legitimate uses of opacity there is also the need for public oversight, perhaps through federal regulation. The Federal Government serves the public interest better than the imperfect market for search can provide on its own.

There is perhaps a tension between this 2008 position and what is expressed in Chapter 1 of TBBS in the section “The One-Way Mirror,” which gets I dare say a little conspiratorial about The Powers That Be. “We are increasingly ruled by what former political insider Jeff Connaughton called ‘The Blob,’ a shadowy network of actors who mobilize money and media for private gain, whether acting officially on behalf of business or of government.” Here, Pasquale appears to espouse a strong theory of regulatory capture from which, we we to insist on consistency, a Federal Search Commission would presumably not be exempt. Hence perhaps the role of TBBS in stirring popular sentiment to put political pressure on the elites of The Blob.

Though it is a digression I will note, since it is a pet peeve of mine, Pasquale’s objection to mathematized governance:

“Technocrats and managers cloak contestable value judgments in the garb of ‘science’: thus the insatiable demand for mathematical models that reframe the subtle and subjective conclusions (such as the worth of a worker, service, article, or product) as the inevitable dictate of salient, measurable data. Big data driven decisions may lead to unprecedented profits. But once we use computation not merely to exercise power over things, but also over people, we need to develop a much more robust ethical framework than ‘the Blob’ is now willing to entertain.”

That this sentiment that scientists should not be making political decisions has been articulated since at least as early as Hannah Arendt’s 1958 The Human Condition is an indication that there is nothing particular to Big Data about this anxiety. And indeed, if we think about ‘computation’ as broadly as mathematized, algorithmic thought, then its use for control over people-not-just-things has an even longer history. Lukacs’ 1923 “Reification and the Consciousness of the Proletariat” is a profound critique of Tayloristic scientific factory management that is getting close to being a hundred years old.

Perhaps a robust ethics of quantification has been in the works for some time as well.

Moving past this, by the end of Chapter 1 of TBBS Pasquale gives us the outline of the book and the true crux of his critique, which is the problem of complexity. Whether or not regulators are successful in opening the black boxes of Silicon Valley or Wall Street (or the branches of government that are complicit with Silicon Valley and Wall Street), their efforts will be in vain if what they get back from the organizations they are trying to regulate is too complex for them to understand.

Following the thrust of Pasquale’s argument, we can see that for him, complexity is the result of obfuscation. It is therefore a source of opacity, which as we have noted he has defined as “remediable incomprehensibility”. Pasquale promises to, by the end of the book, give us a game plan for creating, legally, the Intelligible Society. “Transactions that are too complex to explain to outsiders may well be too complex to be allowed to exist.”

This gets us back to the question we started with, which is whether this complexity and incomprehensibility is avoidable. Suppose we were to legislate against institutional complexity: what would that cost us?

Mathematical modeling gives us the tools we need to analyze these kinds of question. Information theory, theory of computational, and complexity theory are all foundational to the technology of telecommunications and data science. People with expertise in understanding complexity and the limitations we have of controlling it are precisely the people who make the ubiquitous algorithms which society depends on today. But this kind of theory rarely makes it into “critical” literature such as TBBS.

I’m drawn to the example of The Social Media Collective’s Critical Algorithm Studies Reading List, which lists Pasquale’s TBBS among many other works, because it opens with precisely the disciplinary gatekeeping that creates what I fear is the blind spot I’m pointing to:

This list is an attempt to collect and categorize a growing critical literature on algorithms as social concerns. The work included spans sociology, anthropology, science and technology studies, geography, communication, media studies, and legal studies, among others. Our interest in assembling this list was to catalog the emergence of “algorithms” as objects of interest for disciplines beyond mathematics, computer science, and software engineering.

As a result, our list does not contain much writing by computer scientists, nor does it cover potentially relevant work on topics such as quantification, rationalization, automation, software more generally, or big data, although these interests are well-represented in these works’ reference sections of the essays themselves.

This area is growing in size and popularity so quickly that many contributions are popping up without reference to work from disciplinary neighbors. One goal for this list is to help nascent scholars of algorithms to identify broader conversations across disciplines and to avoid reinventing the wheel or falling into analytic traps that other scholars have already identified.

This reading list is framed as a tool for scholars, which it no doubt is. But if contributors to this field of scholarship aspire, as Pasquale does, for “critical algorithms studies” to have real policy ramifications, then this disciplinary wall must fall (as I’ve argued this elsewhere).

Advertisements