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Human brains don't intuitively understand causality. They just associate things that have happened before with things that have happened after. Disentangling ca
by lern_too_spel 4y ago
Human brains don't intuitively understand causality. They just associate things that have happened before with things that have happened after. Disentangling causal graphs is a higher-level activity inferred from the associations made in statistics classes. You can absolutely get AGI using only associative models (and no causal models) as primitives.
- Jensson 4y ago> Human brains don't intuitively understand causality But human brains do understand causality, just not the part that does intuition, otherwise human brains wouldn't be able to invent statistics. Therefore you only get the stupid part of human brains when you try to make models like ChatGPT that only tries to replicate human intuition and not human reasoning.
- lern_too_spel 4y agoHuman brains can invent statistics just like they can invent numbers larger than collections of objects they can physically count. None of this needs causal models as a primitive to build on, just like large language models showed that we don't need specialized Chomskyan recursion structures as a primitive for language.
- pharrington 4y agoThere's plenty of evidence that brains do casual inference. https://pubmed.ncbi.nlm.nih.gov/31047778/ https://pubmed.ncbi.nlm.nih.gov/31047778/ is just one of many reputable and scholarly results that came up when I googled for "brain causal inference".
- lern_too_spel 4y agoAccording to the abstract, this paper doesn't describe causal inference à la Pearl but something akin to LASSO regularization on an associative model.