Guys, let’s all appreciate King Kong while being respectful of himself and his family at his advanced age. Kong suffered a stroke several years ago and has had difficulty swallowing buildings ever since. He lives in an assisted care facility and has periodic dementia. He doesn’t remember which cities he has terrorized, and doesn’t sign autographs anymore. He was asked to leave his prior nursing home after the staff complained about dozens of calls for autographs every hour. Kong was unable to attend People’s villains of the century gala last year, and asked Bigfoot to attend in his place. He asks that donations be made to the Kong facility for underprivileged super villains.
This problem isn't particularly unique to AI research. In any optimization problem, if you do not encode all constraints or if your cost function does not always reflect the real world cost, then you will get incorrect or even nonsensical results. Describing this as an AI problem is just clickbait.
The article doesn't mention it but the researchers are using agent-based-modelling. It was nice to see the gif of what appears to be either NetLogo or Repast. I did research in that area for about 8 years and know a bit about the subject.
What they are showing is one of the main issues with agent-based-models (and I think every model, but it happens particularly with models trying to capture the behaviour of complex open systems): Garbage in -> Garbage Out.
Most likely the representation of the sheep/wolf system was not correct (so the modeling was not correct). Here "correct" means good enough to demonstrate whatever emerging behaviour they are studying. ABM is a powerful tool, but you must know how to use it.
I would argue that Bayes Theorem is taught in high school basically conditional probabilities and inferences. The issue is that applied Bayes Theorem is not taught. What do you do with information given with the data at hand?
Bayesian updates should be taught in schools, at least at the most coarse-grained level. Not to let people calculate anything; almost nobody is going to need that in life anyway. But so that some authority (which a school is) tells people they're allowed and supposed to update their beliefs on evidence. That evidence drags belief more in one direction than the other. That 0 and 1 are not probabilities in real life. That being certain of something is a rare thing, that they should embrace being more or less sure. That this is not someone's random worldview, but there is a proper (and rather fundamental) mathematical formalism behind it, it's just impossible to apply it fully in real life, so we have to approximate it.
