I’m torn by Evgeny’s work. I tend to agree with what I perceive is one of his basic ideas: our culture of deifying the application has a nasty side effect of reducing the perceived importance of political change: don’t bother actually risking anything to protest, just like the Facebook page about the protest. I really liked the concept about the rise of the choosing algorithm and its impact on creativity. I have a soft spot for a truly well written negative book review. And I think it’s vital that those of us who self-identify as “open” advocates engage with his work, because I think he’s onto something in more cases than I’d like to admit.
On a related note, I’ve been reading The Theory That Would Not Die recently. It’s a nice look at the waxing and waning of probability and inference over hundreds of years. When we’re in periods where we don’t know what we’re looking for - and it’s important to be as right as possible as fast as possible - then Bayes’ table becomes a vital tool in the kit. In World War II, that was cracking Enigma.
Unfortunately now, most of its usage is social, mobile, commercial. It offers me rehab in Napa Valley when I buy wine online.
But I worry that in burying the algorithm and the application and the game, to kill its overestimation in culture and in politics, he fails to appreciate the places where those tools are yet to be applied, but might bring real change. By real change, I mean epistemic change, a change in the way that we know we know something.
Science is one of those places. Science has a problem related to, but different than, solutionism. I’d call it “sensorism” perhaps - the belief that because we can make a machine that senses things more finely, more completely, and in massive parallel, we’ll somehow come to a greater understanding of the underlying thing being studied.
Sensorism is rife in the sciences. Pick a data generation task that used to be human centric and odds are someone is trying to automate and parallelize it (often via solutionism, oddly - there’s an app to generate that data). What’s missing is the epistemic transformation that makes the data emerging from sensors actually useful to make a scientific conclusion - or a policy decision supposedly based on a scientific consensus.
One of the reasons I do “open” work is that I think, in the sciences, it’s a philosophical approach that is more likely to lead to that epistemic transformation. If we have more data available about a scientific problem like climate change, or cancer, then the odds of the algorithms figuring something out that is “true” but incomprehensible to us humans go up. Sam Arbesman has written about this nicely both in his book the Half Life of Facts and in another recent Slate article.
I work for “open” not because “open” solves a specific scientific problem, but because it increases the overall probability of success in sensorism-driven science. Even if the odds of success themselves don’t change, increasing the sample size of attempts will increase the net number of successes. I have philosophical reasons for liking open as well, and those clearly cause me cognitive bias on the topic, but I deeply believe that the greatest value in open science is precisely the increased sample size of those looking.
I also tend to think there’s a truly, deeply political element to enabling access to knowledge and science. I don’t think it’s openwashing (and you should read this paper recommended by Morozov on the topic) to say that letting individuals read science can have a real political impact.
I look forward to reading Morozov’s new book this weekend at SXSW. It’ll be a bracing antidote to what I expect will be rampant solutionism. My panel is political - it’s about who owns the data these solutions create, and what rights and risks those solutions entail. It’ll get a lot less attendees than a product launch.
And I hope Morozov engages with sensorism one of these days. It’d be fun to see what he does with it.
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