Yeah it is interesting how much the LW space recreates these sorts of ideas from first principles, the combination of overfocus on math, disdain for non-lw experts, disdain for softer sciences, insider hero worship, and contrarianism creates a perfect cult incubator.

That’s the simplest way that this is wrong. But it’s also wrong in a much more interesting way that even a bunch of scientists I interact with don’t quite get sometimes.

You can talk about the current complex system that has built up a bunch of internal dependencies over time, and wrongly talk about the odds of the specific sequence with all that embedded history appearing all at once.

But you can also talk about canalization, and the metaphors from erosion are very apt and very intentional. If you have a hillside where it rains, there are a huge number of drainage networks that can transfer water down the hill, and any one of them is only a tiny subset of the huge of possibilities. But also, if you take a hillside and bulldoze it, you WILL get one of those valid networks back again, and it does not have to happen all at once. Instead, small changes to the inert starting point will be driven into existence by the pressures of the flowing water, causing the flow to slightly increase. Those highly contingent starting points will then drive an accelerating process of secondary changes that pushes the hillside towards an efficient drainage network, regardless of the starting point. The system is driven very predictably into a tiny corner of parameter space, from a huge number of initial starting points.

There are very persuasive arguments that abiogenesis and evolution are very similar. That instead of talking about the random convergence of rare events, you should think of the process as a runaway, tiny initial changes making future ones more likely in a chain reaction that drives you towards function. Initially inert chemistry subject to disequilibrium being driven into becoming an efficient metabolic channel, and an efficient information channel, pushing you towards the living state in an initial environment that has enough disequlibrium and chemistry that can support structure. In this school of thought, the forces that drive life into existence are basically the same forces that sustain it once it exists.

EDIT This is even relevant to machine learning! You literally initialize synthetic neural network with random numbers, and apply the training process, trying to push it towards having the output given an input match the ground truth. Regardless of the random inert starting point, you reliably drive the network into a state that produces something like the ground truth output from the training input, provided there is sufficient information in the input in the first place. You don’t have to initialize it with the perfect starting weights, almost every starting point is canalized towards some state that produces the relevant type of outputs.

I recommend looking for the work of one particular guy, Dr. Eric Smith. There’s an old talk of his somewhere on youtube, where to roughly paraphrase, he says that you shouldn’t be wondering about the very specific chemical events at the origin of life, but instead, you should “ask what was so wrong with the dead Earth that it had to spontaneously break down into the living Earth” which is the stable state, the resting point that it is canalized towards.