Melanie Mitchell

idea model simple mathematics computers fundamental complex

"idea models—models that are simple enough to study via mathematics or computers but that nonetheless capture fundamental properties of natural complex systems."

—Melanie Mitchell

humans overestimate AI underestimate complexity intelligence

“…we humans tend to overestimate AI advances and underestimate the complexity of our own intelligence.”

—Melanie Mitchell

pile narrow intelligence general number ability integration

“A pile of narrow intelligences will never add up to a general intelligence. General intelligence isn’t about the number of abilities, but about the integration between those abilities.”

—Melanie Mitchell

afraid intelligence machine decision stupidity tail risk specifi

“We should be afraid. Not of intelligent machines. But of machines making decisions that they do not have the intelligence to make. I am far more afraid of machine stupidity than of machine intelligence. Machine stupidity creates a tail risk. Machines can make many many good decisions and then one day fail spectacularly on a tail event that did not appear in their training data. This is the difference between specific and general intelligence.”

—Melanie Mitchell

poor mathematical intuitive understanding coincidence

“We have a poor mathematical, as well as a poor intuitive understanding of the nature of coincidence.”

—Melanie Mitchell

linearity reductionist dream nonlinearity nightmare

“Linearity is a reductionist’s dream, and nonlinearity can sometimes be a reductionist’s nightmare. Understanding the distinction between linearity and nonlinearity is very important and worthwhile."

—Melanie Mitchell

complex system network component simple rule complex collective

“complex system: a system in which large networks of components with no central control and simple rules of operation give rise to complex collective behavior, sophisticated information processing, and adaptation via learning or evolution.”

—Melanie Mitchell

This statement is not provable

“ 'This statement is not provable.' Think about it for a minute. It’s a strange statement, since it talks about itself—in fact, it asserts that it is not provable. Let’s call this statement 'Statement A'. Now, suppose Statement A could indeed be proved. But then it would be false (since it states that it cannot be proved). That would mean a false statement could be proved—arithmetic would be inconsistent. Okay, let’s assume the opposite, that Statement A cannot be proved. That would mean that Statement A is true (because it asserts that it cannot be proved), but then there is a true statement that cannot be proved—arithmetic would be incomplete. Ergo, arithmetic is either inconsistent or incomplete.”

—Melanie Mitchell