Complexity and Silicon Valley

The path towards understanding and appreciating conservatism in Silicon Valley is through complexity. Here, let's start at the beginning. Complexity as it is understood here starts with MIT Professor Edward Lorenz and his discovery of the error amplification effects of feedback-based systems. While attending complexity conferences, one hears the team "complexity" repeated too frequently, almost like a mantra. For Lorenz though, the complex combination of nonlinearity, stock-flow (integrative), and feedback effects in his 1960s-era different equation-based models led to unexpected amplification of small initial differences.

 At approximately the same time, in 1965, Friedrich Hayek applied new notions of complexity to politics and economics. Those who have been paying attention know Hayek from two career highlights: (1) The Road to Serfdom; and (2) his becoming a Nobel laureate in Economics in 1974. Rather than running though this work, let us instead focus on the matter at hand, how does complexity impact and inform conservatism? Complexity generally, and the complexity of socio-economic systems specifically, provides hard limits to what is knowable about these systems. So as political entrepreneurs and purported innovators make claims in the  marketplace of ideas, complexity places limits on what can be said.

The problem comes in that these same entrepreneurs and innovators don't want to be constrained by what they can say. Hayek explains at length how such claims, especially as they relate to and regard socialism, have demonstrated themselves to be false. Your correspondent agrees with Hayek's conclusion but will leave that argument for a later time.

What is especially informative is how these political entrepreneurs respond to complexities  limitations: in the words of Tom Wolfe, they scream like weenies roasting over a fire. The best example I've found is Herman Finer's The Road to Reaction. It's a remarkable example of what I call an "affect storm," or what others call "argument by outrage." While purporting to be logical and rational, Finer's book is a collection of half-thought-through accusations, what Hayek called, ""a specimen of abuse and invective which is probably unique in contemporary academic discussion." It's instructive to consider the incentives behind Finer's comments, and here we need to distinguish between good reasons and real reasons. Finer, being a Fabian socialist, portrays a concern for society's poorest. Here your correspondent draws insight from Tom Wolfe who credits his prescience to a focus on status. So in your correspondent's opinion, Finer's affect-laden response to Hayek is driven by the implications and consequences of complexity: that is, he can no longer claim special insight into socio-economic systems, which would limits his status and power. This in Finer's view, is clearly unacceptable.

 But much of the politics since the 1940s has been driven by just this tension between what is knowable and what is not as limited by complexity, which is a conservative concept. And that is what we see amplified in 21st century politics: this analytic tension between what can be known, and what is not knowable. The computer revolution, and represented by Silicon Valley, has something useful and important to say about this complexity by pushing the boundaries of what is knowable. However, this can only happen if senior policy makers and those interested in policy acknowledge these limitations, which is controversial and problematic.

What's more conservative, EE or CS?

As a Silicon Valley (SV) conservative, I was thinking to myself, “Which is more conservative, electrical engineering (EE) or computer science (CS)?” Let me allow the reader – whoever that might be – to consider the question briefly before continuing. (Jeopardy theme)

Before diving into the answer, let’s first establish the conceptual context. The foundation of conservatism -- and through inverse causality, liberalism as well – is the fact-value distinction, with conservatism associated with the fact side and liberalism with values.

So how do EE and CS compare in the fact-value distinction. The answer should be pretty obvious to anybody who’s studied both, EE is more fact oriented because it is a branch of and grounded in physics, while CS is more virtual, conceptual, and abstract. With EE, if you’re unsure about the ohms (units of resistance), farads (capacitance), or henrys (inductance) of a device, one can measure it. With CS, if you need more of whatever it is – memory, objects, or agents – one just defines more. Now there are limits to this argument, but CS is related more to math than physics – and then it doesn’t even need to be that related to math.

These observation might explain why SV is so overwhelming liberal, which is to say Democrat. EE is a discipline of design within constraint, which CS and the products associated with it, are comparatively less constrained by physics, or reality for that matter.

What does it mean to be an SV conservative?

One of the questions I cannot quite shake is this: Why is Silicon Valley so gosh-darned liberal? I grew up there and became a conservative of sorts. I grew up reading the San Francisco Chronicle and wondered at the insane decisions of so-called liberal adults whose politics and policies were ever so easy to criticize. But increasingly, instead of merely criticizing liberals, I increasingly wonder what it means to be a conservative?

There are a couple of insights that illuminate for me what being a conservative is. The first comes from the Gospels according to Matthew and Luke in which Jesus says that, "a tree is known by its fruits." My interpretation, in the "here" and "now", that names and reputations are based on the long-term consequences of a person, policy, or population. Note that this is very different from our modern-day media-driven democratic world of reputation based on short-term group opinion.

Second, Tom Wolfe's "The Great Relearning," provides multiple examples of the progressive ideas of intellectuals being implemented only to end in disaster. Wolfe's primary example is the sexual revolution, which was implemented with such fanfare but generated a of unanticipated, and sometimes anticipated, consequences.

Third, this focus on consequences leads, in turn, to a focus on complexity generally and causal complexity specifically. That is, what makes consequences "unintended" is that human cognition is not very good at anticipating the consequences of large policy changes because of the complexity of the social systems involved. However, power computers, the kinds created and used by Silicon Valley engineers, can be used to address and account for that complexity.

However, there is a division in Silicon Valley between analysis used for accurate prediction, such as that used for engineering design and corporate operations, and that used for sales and marketing. That is, sales and marketing rely more on affect and emotion rather than cognition and accurate analysis. And here is the key division between standard liberal and much rarer conservative beliefs in Silicon Valley: the former generates sales and votes based on affect, while the latter generates more accurate analysis based on accurate cognition and accounting for complexity.

As the costs of affect and profit-driven policy analysis mount and become ever more apparent, the need to engage in accurate, engineering design-like policy analysis will increase, but given the tenor of America's 2016 presidential election, that time is still some ways off.