[Lex Computer & Tech Group/LCTG] Too much efficiency makes everything worse

[Robert Primak]

A few examples I don't think I saw in the article are measuring executive performance by measuring quarterly financials or measuring software engineers by lines of code.

Good examples! 
I would just ad that just because you can measure something in a certain way, this does not mean that the thing being measured or the metric used to measure it is important to an optimal outcome. This is how bureaucracies and regulatory frameworks grow and grow, but don't always seem to solve the underlying or the immediate problems. 
-- Bob Primak 

    On Monday, July 10, 2023 at 01:34:51 PM EDT, Jon Dreyer <jon at jondreyer.org> wrote:  
 
  
By the time I got through the first few paragraphs, I remembered that, over a decade ago, I saw the danger of what he calls "overfitting" in education and coined what I called "the implicit motto of education reform":
 
 
If you can't measure what you value, value what you can measure.
 
 
So I was not surprised to see education as the first on the list of examples of the the danger of overfitting in section 3.
 
I'd not read of Goodhart's Law, either the weak or strong forms, but I had discovered the idea. It seems increasingly important to keep in mind as technology makes it ever easier to measure things. A few examples I don't think I saw in the article are measuring executive performance by measuring quarterly financials or measuring software engineers by lines of code.
 
 
-- 
 
 
 Jon "Measure Twice, Gut Once" Dreyer
 Math Tutor/Computer Science Tutor
 Jon Dreyer Music 
 On 7/10/23 8:40 AM, Harry Forsdick wrote:
  
  Interesting use of ML/AI:  
  
  Too much efficiency makes everything worse: overfitting and the strong version of Goodhart's law  
      
   - https://sohl-dickstein.github.io/2022/11/06/strong-Goodhart.html
  -- Harry  
 
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