“Though this pheonomenon is often discussed, it doesn't seem to be named. Let's call it the strong version of Goodhart's law“ I wonder why the author called it that way when this seems to me clearly derived from Ross Ashby‘s law of Requisite Variet[1], predating Goodhard by 20 years. As I see it, it is not even necessary to put more meaning it Goodhard as there actually is. Requisite Variety is sufficient. Going by h…
Too much efficiency makes everything worse (2022)
141–150 of 377 posts
Re: Too much efficiency makes everything worse (2022)
#142Those 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.
Re: Too much efficiency makes everything worse (2022)
#143Upon reading the title at first glance, I thought this was going to be how "effecient" computers nowadays. Such as MacBooks and such, who started this efficient computers thing in the recent times. And they are, but as a result computers are all worse off for it. I mean soldered RAMs and everything is a system on a chip.
Re: Too much efficiency makes everything worse (2022)
#144The argument rides on the well-known Goodhart's law ( when a measure becomes a target, it ceases to be a good measure ). However, it only puts it down to measurement problems, as in, we can't measure the things we really care about, so we optimize some proxies. That, in my view, is a far too reductionist view of the problem. The problem isn't just about measurement, it's about human behavior. Unlike particles, humans…
This is true, these "laws" are approximations and imperfect reductions. Which one is useful or descriptive will depend on the specific example. Optimizing ML VS Optimizing a social media algorithm VS using standardized testing to optimize education systems. There is no perfect abstraction that applies to these different scenarios precisely. We don't need that precision. We just need the subsequent intuition about whe…
Re: Too much efficiency makes everything worse (2022)
#145Earlier quoted context omitted.
Yep, I used to work in a factory. Target utilization at planning time was 80%. If you over-predict your utilization, you waste money. If you under-predict, a giant queue of “not important” stuff starts to develop
For some scenarios that's fine, and you can slash the queue whenever necessary. Eg at Google (this was ten years ago or so), we could always spend leftover networking capacity on syncing a tiny bit faster and more often between our data centres. And that would improve users' experience slightly, but it also not something that builds up a backlog. At a factory, you could always have some idle workers swipe the floor a…
Re: Too much efficiency makes everything worse (2022)
#146Re: Too much efficiency makes everything worse (2022)
#147Earlier quoted context omitted.
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 pe…
We've seen this during the COVID pandemic supply chain disruptions as well, where just in time supply chain management doesn't work as expected when operating in an abnormal environment.
Highly optimized systems take full advantage of their environment and rely on a high degree of predictability in order to avoid redundant operations.
These systems minimize the free energy in the system, and so very little free energy is available to counteract new forces introduced to the environment which act on the system.
You'll find parallels in countless domains, since the very basis for learning and stabilization of a system revolves around becoming more or less sensitive to a given stimulus. Examples could be attention, supply chain economics, institutions, etc.
Re: Too much efficiency makes everything worse (2022)
#148I would claim in a completely informal way that the optimal degree of utilization is ln(2)=0.693, around 70%. This stems from the optimal load of self-balancing trees. A little bit of slack is always useful to deal with the unforeseen. And even a lot of slack is useful (though not always as it is costly) as it enables to do things that a dedicated resource cannot do. On the other hand, no slack at all (so running at…
I would put it at 1 - e^(-1) ~= 0.6321 As e^x is a commonly occurring curve and at that point its derivative goes below 1, meaning from that point on it's diminishing returns.
Re: Too much efficiency makes everything worse (2022)
#149Earlier quoted context omitted.
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 extern…