I agree that raising general predictive ability would also tend to increase wisdom. I think my main point, which I probably didn't sufficiently highlight, is that wisdom is bottlenecked on data (and also maybe seems to require more abstraction and abduction than other learning) moreso than other knowledge we tend to collect due to the underlying complexity of the thing we are trying to predict (human behavior)

I think that's right and it's a bit of a strawman. I don't think pomo originally threw out epistemology but it provides tools that, while useful for general societal critique, are also easy to shoot your foot off with. So, pomo allows for some good things but also seems to have enabled identity politics as well as right wing fake news hysteria.

To me, this felt more like speculation which was certainly informed by many things I've read in the past but nothing particular came to mind with the exception of the obvious reference to Deleuze. A kind of applied Deleuzian psychiatry, although I'm not sure he would agree with this sort of application. (https://en.wikipedia.org/wiki/Anti-Oedipus#Desiring_machines_and_social_production)

Good point regarding Focusing, and I do agree that it is closely related. I've only listened to the audiobook, is there a work by Gendlin you would recommend? Upon reflection, it seems one of the main insights I was trying to point at here is the lack of logical connection between the qualia of desire and the object it seeks (the machine it seeks to connect to, in D&G's terminology). The mental act of seeking out levers to pull would be equivalent to Focusing here, I think?

Yes that Cleese piece is great, thanks for sharing.

+1 for the suggestions made by others. I will ping the blog writer about this post to see if he's interested in reaching out.

You may also want to look at Daniel Ingram and his MCTB community

That's also just the tip of the iceberg. This book is a good guide to identifying and predicting complex time series behavior: https://www.amazon.com/gp/product/0521529026/ref=oh_aui_search_detailpage?ie=UTF8&psc=1

So I guess this is along the lines of: try prediction techniques that are designed to work on complex systems and see how it goes.

This doesn't work when you don't have enough data to do so, of course.

On the topic of financial markets and aggregation of signals, there is actually a lot of ML-based signal aggregation going on within trading companies. A common structure is having specialized individuals or teams develop predictive signals (for publicly traded securities) and then have them aggregated into a single meta-prediction (typically a "microprice", or theoretical price) which is then used for order placement.

A couple anecdotes:

1. There is some publicly available story about a high frequency KOSPI options desk that made a substantial improvement in P/L after adding a Random Forest in their signal aggregation logic. Eventually, this became the difference between making and losing money
2. Accurate up until about a year or two ago, I believe one of the top 10 worldwide trading firms was using a simple average as their aggregation mechanism for most of their trading. This would include averaging effectively redundant signals which could be easily identified as such.

Nice. Just curious, how much did you do, and why'd you stop (if you did)?

This is derivative of meditative insight practice. You may be interested in looking into Vipassana practice. With some time spent building concentration skills this kind of sensation noticing practice is far more powerful (think, LSD-like power) and can be extended to get you a lot more than just joy

Sorry for the slow reply, want to do this over email? im gbasin at gmail