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AI and ML are just as smart as the training data, which for large sets of data usually gives biased or outright results

Posted by jpluimers on 2022/06/15

Kris phrases a thought that has been lingering in my head for decades: [] Kristian Köhntopp on Twitter: “”AI” ist nicht intelligent, sondern reproduziert das Trainingsmaterial und die Vorurteile darin. Es handelt sich um automatisierten Aberglauben und Verschwörungsquatsch. Je größer das Netzwerk, um so wirrer.” / Twitter

Basically there are two kinds of AI:

  • a bunch of if/then/else statements
  • a model based engine that is as bad as it’s training data; the larger the set of training data, the worse it gets.

A few of the images in the excellent thread that Kris quoted (more in the [Wayback/] PDF): [] Owain Evans on Twitter: “Paper: New benchmark testing if models like GPT3 are truthful (= avoid generating false answers). We find that models fail and they imitate human misconceptions. Larger models (with more params) do worse! PDF: with S.Lin (Oxford) + J.Hilton (OpenAI)… “




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