I have a history of science anecdote to answer that. In the 80s, most AI research was concentrated in symbolic AI and expert systems. Only a handful of researchers were working on neural networks. Geoffrey Hinton (@geoffreyhinton), now a Nobel Prize winner, was one of them. When expert systems failed to deliver tangible results, funding for AI research dried up in the US. This became known as the AI Winter. Geoffrey moved from the US to the University of Toronto because of this funding cut and, according to @CadeMetz in the brilliant book Genius Makers, his wife's desire to leave the US. In 2012, he co-authored the AlexNet paper, showing that neural networks vastly outperformed every other method in image classification. Shortly after, he sold his startup to Google for $44 million. AlexNet and breakthroughs happening elsewhere, led to the AI boom, creating strong demand for AI scientists and people with hands-on experience in neural networks. With so much of this happening in Toronto, the city developed a startup and research culture around neural networks. Keep in mind: for many years, only a select few universities were doing serious AI research. I imagine all of this got "in the air" (@joshgans) and spilled over into economics. I don't know how much of this anecdote is true. But it is nice to think that ideas diffuse beautifully like that. It is also interesting to think that a flap of a butterfly's wings, or someone's wife wanting to leave the US, can spark such cascade of events.