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Too much efficiency makes everything worse (2022)

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Re: Too much efficiency makes everything worse (2022)

#92

I don't think it's unintuitive at all. 100% optimized means 100% without slack. No slack means any hitch at all will destroy you.

That would assume your only target measure is efficiency, which would be a silly think to target in exclusivity of everything else.

Re: Too much efficiency makes everything worse (2022)

#93
I was listening to an episode of the "inControl" podcast [1], in which Ben Recht suggested that overfitting is not always well understood.

Perhaps it is interesting to read his blogpost "Machine Learning has a validity problem" alongside this article.

[1] https://www.incontrolpodcast.com/

[2] https://archives.argmin.net/2022/03/15/external-validity/

Re: Too much efficiency makes everything worse (2022)

#94
If a citizen recognizes or intuits this to be a deep-seated problem of the political process, and if the only concrete influence this citizen can exert on the political process is choosing one of several proposed representatives, it seems rational to choose the most irrational, volatile, chaotic and unpredictable candidate.

The ideal choice would be a random number generator, but lacking that, he would want to inject the greatest dose of entropy available into the system.

Re: Too much efficiency makes everything worse (2022)

#95
The author identifies problems with a system measuring targets, but then all the proposals are about increasing the power and control of the system.

Perhaps the answer—as hippy sounding as it is—is to reduce the control of the system outright. Instead of adding more measures, more controls, which are susceptible to the prejudices of control, we let the system fall where it may.

This, to me, is a classic post of an academic understanding the failures of a system (and people like themselves in control of said system) but then not allowing the mitigation mechanisms of alternate systems to take its place.

This is one of the reasons I come to HN: to view the prime instigators of big-M Modern failure and their inability to recognize their contributions to that problem.

Re: Too much efficiency makes everything worse (2022)

#96

I recognize the author Jascha as an incredibly brilliant ML researcher, formerly at Google Brain and now at Anthropic. Among his notable accomplishments, he and coauthors mathematically characterized the propagation of signals through deep neural networks via techniques from physics and statistics (mean field and free probability theory). Leading to arguably some of the most profound yet under-appreciated theoretical…

The exciting thing about this idea is if you can correlate, say, economics with the works of ML, that means a computer program which you can run, revise and alter can directly give you measurable data about these complex system interactions that mostly have existed as a platonic idea since reality is too nuanced and multiple to validate concepts formally. With the idea that there is some subset of logic that sits bel…

This idea has been pursued several times in the past, and it always ends up producing lots of interesting academic results and no practical conclusions.

It's certainly an interesting perspective on the development of complex systems. The idea that an economy can be somehow overfitted to its own incentives and constraints I don't think is entirely new, cf the Beer Game. But as a general concept, it's certainly not something that usually finds its way into policy discussion, beyond some very specific talk about reshoring of certain critical industries.

However, I think the most important benefit of this perspective is going to be providing yet another counterargument against the Austrian economics death cult.

Re: Too much efficiency makes everything worse (2022)

#98

I recognize the author Jascha as an incredibly brilliant ML researcher, formerly at Google Brain and now at Anthropic. Among his notable accomplishments, he and coauthors mathematically characterized the propagation of signals through deep neural networks via techniques from physics and statistics (mean field and free probability theory). Leading to arguably some of the most profound yet under-appreciated theoretical…

Interesting timing for me! Just a couple of days ago I discovered the work of biologist Olivier Hamant who has been raising exactly this issue. His main thesis is that very high performance (which he defines as efficacy towards a known goal plus efficiency) and very high robustness (the ability to withstand large fluctuations in the system) are physically incompatible. Examples abound in nature. Contrary to common perception evolution does not optimise for high performance but high robustness. Giving priority to performance may have made sense in a world of abundant resources, but we are now facing a very different period where instability is the norm. We must (and will be forced to) backtrack on performance in order to become robust. It’s the freshest and most interesting take on the poly-crisis that I’ve seen in a long time.

https://books.google.co.uk/books/about/Tracts_N_50_Antidote_...

Re: Too much efficiency makes everything worse (2022)

#99
post #24

Those are great points! Another related law is from queuing theory: waiting time goes to infinity when utilization approaches 100%. You need your processes/machines/engineers to have some slack otherwise some tasks will wait forever.

I feel that a 100% efficient system is not resilient. Even minor disruptions in subsystems lead to major breakdowns. There’s no room to absorb shocks. We saw a drastic version of this during COVID-19 induced supply chain collapse. Car manufacturers had built near 100% just in time manufacturing that they couldn’t absorb chip shortages and it took them years to get back up. It also leaves no room for experimentation.…

This is coincides with my headcannon cause of the business cycle.

1. Firms compete

2. Firms either increase their efficiency or die

3. Efficient firms are more susceptible to shocks

4. Firm shutdown and closures are themselves shocks

5. Eventually the system reaches a critical point where the aggregate susceptibility is higher than the aggregate of shocks that will be generated by shutdowns and closures

6. Any external shock will cause a cascade

There's essentially a "commons" where firms trade susceptibility for efficiency. Or in other words, susceptibility is pooled while the rewards for efficiency are separate.

Re: Too much efficiency makes everything worse (2022)

#100
post #85

Earlier quoted context omitted.

I’m remembering reading once that cities are incredibly efficient in how they use resources (compared to the suburbs and rural areas, I guess), and, in light of your comment about waiting time, I’m realizing why now why they’re so unpleasant: constant resource contention.

The efficiency results in abundance not possible in less dense areas, you are waiting for things that are simply not available elsewhere.

Sort of. Compare doing laundry at the laundromat to doing laundry in your basement.
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