Earlier quoted context omitted.
Love myself some cybernetics! All engineers are doing themselves a disservice by sitting here writing smooth-brained rants about “dumb MBAs making my job hard” instead of reading up on this field and understanding the true complexities that are inherent in people working together.
Agreed. I wonder if this is still the aftermath of the chasm which resulted when ‘Marvin Minsky et al‚ disowned Cybernetics, took some parts out of it and gave it a shiny new name. Especially Systems Theory in its second manifestation (Maturana, Luhmann, von Förster, Glasersfeld - and Ackoff) is extremely powerful, deep and, reasons beyond me, totally overlooked. Have to say tho, most MBA‘s I encountered sadly never…
Too much efficiency makes everything worse (2022)
221–230 of 377 posts
Re: Too much efficiency makes everything worse (2022)
#222This is why I don’t like focusing on GDP. I think a quarterly poll on life satisfaction and optimism would be a better measure. If you’re curious about GDP. I my car breaks and I get it fixed, that adds to GDP. If a parent stays home to raise kids, that lowers GDP. If I clean my own house that lowers GDP. Etc. Unemployment is another crude metric. Are these jobs people want or do they feel forced to work bad jobs.
Re: Too much efficiency makes everything worse (2022)
#223This is why I don’t like focusing on GDP. I think a quarterly poll on life satisfaction and optimism would be a better measure. If you’re curious about GDP. I my car breaks and I get it fixed, that adds to GDP. If a parent stays home to raise kids, that lowers GDP. If I clean my own house that lowers GDP. Etc. Unemployment is another crude metric. Are these jobs people want or do they feel forced to work bad jobs.
Re: Too much efficiency makes everything worse (2022)
#224Earlier quoted context omitted.
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…
I missed the citation on his education point. Has someone proved that “teaching to the test” leads to lower educational outcomes than not having tests?
There do happen to be citations for this question but I doubt any really clears an "indisputable evidence" standard. That's the nature of the field. Even if the whole discussion was evidence based and dotted with citations, we'd still be working with a lot of intuition and speculation.
Re: Too much efficiency makes everything worse (2022)
#225I 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 pe…
Re: Too much efficiency makes everything worse (2022)
#226The 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…
> Unlike particles, humans will actively seek to exploit any control system you've set up. But that’s only possible because the control system doesn’t exactly (and only) control what we want it to control. The control system is only an imperfect proxy for what we really want, in a very similar way as the measure in Goodhart’s law. Another variation of that is the law of unintended consequences [0]. There is probably…
Re: Too much efficiency makes everything worse (2022)
#227Re: Too much efficiency makes everything worse (2022)
#228I 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 pe…
I know I'd tolerate a digital experience of far lower fidelity (fewer pixels, for instance, or even giving up GUIs altogether) if I could get it in a way that doesn't break every time some far away person farts near a cloud console: A trade of performance for robustness.
Re: Too much efficiency makes everything worse (2022)
#229Re: Too much efficiency makes everything worse (2022)
#230The 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…
> Unlike particles, humans will actively seek to exploit any control system you've set up. But that’s only possible because the control system doesn’t exactly (and only) control what we want it to control. The control system is only an imperfect proxy for what we really want, in a very similar way as the measure in Goodhart’s law. Another variation of that is the law of unintended consequences [0]. There is probably…
Start working with a nice, clean, fully relevant system, end up modelling that plus the whole range of adversarial perturbations from agents of pretty high complexity.