Comment by lemonwaterlime
12 hours ago
The “Brenda” example is a lumped sum fallacy where there is an “average” person or phenomenon that we can benchmark against. Such a person doesn't exist, leading to these dissonant, contradictory dichotomies.
The fact of the matter is that there are some people who can hold lots of information in their head at once. Others are good at finding information. Others still are proficient at getting people to help them. Etc. Any of these people could be tasked with solving the same problem and they would leverage their actual, particular strengths rather than some nebulous “is good or bad at the task” metric.
As it happens, nearly all the discourse uses this lumped sum fallacy, leading to people simultaneously talking past one another while not fundamentally moving the discussion forward.
I see where you are coming from but in my head, Brenda isn't real.
She represents the typical domain-experts that use Excel imo. They have an understanding of some part of the business and express it while using Excel in a deterministic way: enter a value of X, multiply it by Y and it keeps producing Z forever!
You can train AI to be a better domain expert. That's not in question, however with AI, you introduce a dice roll: it may not miltiply X and Y to get Z... it might get something else. Sometimes. Maybe.
If your spreadsheet is a list of names going on the next annual accounts department outing then the risk is minimal.
If it's your annual accounts that the stock market needs to work out billion dollar investment portfolios, then you are asking for all the pain that it will likely bring.
> You can train AI to be a better domain expert. That's not in question.
I think that very much is in question.
I have to agree... I have no idea why I wrote that. Silly me. It's a bit of a global statement.
There are, however, definitely domains it can excel: things like entry-level call handlers... I think they're screwed in all honesty!
Edit: clarified some stuff...
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