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Artificial Intuition: When Algorithms have Hunches
The current generation of Artificial Intelligence (AI) and Machine Learning (ML) algorithms are focused on sifting through massive amounts of data to identify patterns that enable forecasts and predictions.
But AI hasn’t done well with general problem solving. The human ability of having a hunch or gut feel when making decisions is something that’s been difficult to quantify and translate to an algorithm.
Researchers though are trying to incorporate an element of human-like intuition into algorithms. To do that, for example, MIT researchers are studying problem solving methods used intuitively by very smart people. The strategies used by those people are then implemented in software.
Julie Shah, assistant professor at MIT, explained the goal of their research: “can we take the insights and the high-level strategies from the few people who are truly excellent at it and allow a machine to make use of that to be better at problem-solving than the vast majority of the population?”
Sankalp Shangari, technology investor, wrote that “the world will witness a huge network of artificial intelligence that’ll showcase intuitive and reasoning capabilities due to the abundance of data gathered from all corners of the world. But, the question that we need to ask ourselves is ‘Can we trust the intuition of artificial intelligence?'”
