If you don’t know me well, here are two things to know: I am conservative, and yet I like reading the New Yorker.
One of the joys of a Sunday morning home after travel is perusing the stack of magazines that arrived during the week. I’m a digital guy and I read on my Kindle all the time, but I’ve tried reading magazines on my iPad and it just doesn’t have the same … something. I like the paper versions. Maybe it’s because the wind on my balcony flutters the pages and my cat attacks them. Anyway.
My favorite part of the New Yorker (well, next to the cartoons) is the reviews. The reviewers are smart, entertaining, thought-provoking, and occasionally even point the way to an interesting book, movie, or band. Adam Gopnik is a feature writer but often takes his turn on book reviews, and so it was this week, in a review entitled “The Illiberal Imagination”. (The online version is titled “Are Liberals on the Wrong Side of History?”, a more accurate but less imaginative recasting.)
In this review – it takes several table-setting paragraphs to discover – three books are reviewed; Pankaj Mishra, “Age of Anger”, Joel Mokyr, “A Culture of Growth”, and Yuval Noah Harari, “Homo Dues”. And while the books are indeed reviewed, and well, they merely provide three views of a common theme, Gopnik’s true aim: an introspection into why different cultures make progress at different rates.
Is liberalism the best approach? (In the classic sense of fostering and enabling changes, not in the current political sense of government-funded pseudo-socialism.) Or is conservatism, in the classic sense of resisting changes and doing things a prescribed way. Or – and this is Gopnik’s thesis, with which I agree – is the best approach a mixture, in which the change of liberalism exposes new things, and conservatism then “locks in” the ones that work. Philosophical Darwinism.
What makes science so successful – in the sense of this article, the sense of “progress” – is that scientific progress monotonically increases, with new theories being propounded, new ways to validate them, and new ways to build on what has come before, but always moving society forward. The side note to the discussion of all these books is that the scientific method works best for cultures too, even if they don’t explicitly acknowledge it. Quoting Mokyr in “Culture of Growth”: “the true elite of modern societies is composed of engineers, mechanics, and artisans – masters of reality, not big thinkers.” That seems exactly right.
This jibes nicely with some recent reflections on venture capital and startup culture, triggered by a recent trip. Startup culture is inherently liberal, always looking for change, better ways, different things, and new opportunities, somewhat regardless of risk. Venture capital is inherently conservative, locking in the best changes, the ratchet which monetizes progress and makes it possible – and in fact provides the motivation for those taking on the risk. It’s a circle of life – today’s LPs investing in VC funds are yesterday’s successful entrepreneurs. The job of culture is to make this productive dance possible.
This applies in all areas, for example, when considering how best to improve the practice of medicine and the economics of healthcare, it seems best to try fostering this type of progress – the interplay of liberal change and conservative locking in of improvements – rather than forming a panel of thinkers to dictate improvements. Throughout the world governments have locked in suboptimal systems, and the solutions to the sub-optimality are often prescribed rather than evolved. Taking a step back and letting many things happen seems better.
A recent Forbes story, about doctor burnout, is a classic example, and illustrates the light at the end of the tunnel: in it, a beleaguered "Dr X" and his partners were able to innovate by starting their own direct-pay clinic. In fact, having read them more or less consecutively on the same morning, the Forbes story and the New York Times book review seem to be about the same thing: Which cultural models are best for enabling people to work cooperatively and make progress.
These models work for computers too. Two weeks ago my company InTouch hosted Jeff Dean of Google, who subsequently gave an inspiring talk at UCSB about the progress being made in machine intelligence. The approaches which work best are neural networks, which are not rules-based or prescriptive; instead, they “discover” solutions iteratively, by processing lots of data which feed back into the network. At first the a neural network is open – liberal – but as data flow through it becomes more closed – conservative – as it “locks in” the best inference paths. This model works, and it even works on a meta level; neural nets are now being used to optimize themselves as well as to accomplish specific tasks.
This is a long musing – even for me, you are thinking – but one more data point to note. Last week my Engineering team held a hackathon; it broke itself into ten five-person teams, each of which had a little over one working day to create a “hack” with the theme “Expanding the Network”. I was blown away by the cool ideas which surfaced; the liberalism of engineering! Hopefully we can “lock in” some of those ideas and convert them to products; the conservatism of business :)
That’s how we make progress.