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

[Michael Alexander]

 In my opinion, stand-alone efficiency is the wrong criterion; in most cases,  effectiveness would be closer to what’s desired.  Effectiveness, even though perhaps harder to quantify, relates to goals; efficiency doesn’t necessarily.
 Efficiency shouldn’t stand apart from the objective(s) one wants to achieve.  As Harry’s post illustrates, making efficiency into a primary goal can often lead people to irrelevant or perverse outcomes, while tricking people into thinking the “efficient” solution is the most desirable in its own right.
These are some of the truly pertinent questions:-  “Are these the right objectives?”  -  “How well do our methods/approaches lead to fulfilling those objectives?”  (And why?)-  “Do our methods produce undesirable side effects?”-  “Are other methods/approaches equally good, or better, at achieving the objectives?
Here’s a close business/management analog to efficiency (one might say it’s sometimes been confused with efficiency):  Milton Friedman’s (formerly?) widely embraced dictum that businesses should seek maximal profitability above all other considerations (resiliency, or market share, for example).. Profit basically became a proxy for  efficiency.  It benefitted many businesses in the short run; but as the example of General Electric demonstrated, it could destroy businesses.
    – Mike Alexander


    On Monday, July 10, 2023 at 05:13:20 PM EDT, SlateMD <slatemd at comcast.net> wrote:  
 
 I’ll bet that this has all sorts of applications. I wonder if the governors of the Federal Reserve with their “data driven” approach have this in mind. Probably not.Jerry 

Jerome Slate339 368 0075

On Jul 10, 2023, at 1:35 PM, 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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