This post is extremely reasonable, and I expect that if we look back on it 20-30 years from now, we’ll see two patterns:
1) Almost all the predictions will have been basically right.
2) Because of the few that were wrong, the list will have mostly failed to capture whatever happened that actually mattered.
New materials, new manufacturing methods, and new energy sources historically require whole communities and ecosystems to fail for generations, just to move the first few rungs along the tech development curve, before someone finds a niche application that makes real-world sense, which would move the world a few rungs further, and so on. Many never do. The ones that do, pay for all the rest and more, and get retconned into normality.
As an illustration, apply your method to the past instead of the future. At what point, before it actually happened, would it have successfully predicted the historical equivalents of these things? The transition of steam engines from curiosity to industrial revolution. The transition from wood and animal muscle to oil and gas. The transition of computers from rare commercial infrastructure to cheap and omnipresent consumer goods. The transition from oil and gas to renewables. All of these were both predicted in advance, and also dismissed as impossible. In many cases, these kinds of things get dismissed as impossible even after they’ve already started happening.
Agreed! I just think it’s worth calling out that ‘trying things’ and ‘taking risky shots on goal’ looks, for solar and again for lithium ion batteries, like something on the order of ~$1-2 trillion and ~5 million person-years over the course of five decades spent developing the tech to the point that it’s finally becoming clear enough that this is practical at scale to pass the test this post uses. Maybe PV would have passed in 2015 and Li-ion/EVs in 2020? Maybe the trajectory made each seem more likely than not by at most a decade before that, a time when in practice most people still dismissed straight-line-on-graph projections as doomed to being over-optimistic? And that all of that only happened because enough people were using much less stringent tests throughout that timespan as sufficient reason to make steadily larger bets on them anyway.