Statistical machine learning is at the core of modern-day advances in artificial intelligence, but a Rochester Institute of Technology professor argues that applying it correctly requires equal parts science and art.
Ernest Fokoué of RIT’s School of Mathematical Sciences emphasized the human element of statistical machine learning in his primer on the field that graced the cover of “Notices of the American Mathematical Society.”
“One of the most important commodities in your life is common sense,” Fokoué said. “Mathematics is beautiful, but mathematics is your servant. When you sit down and design a model, data can be very stubborn. We design models with assumptions of what the data will show or look like, but the data never looks exactly like what you expect. You may have a nice central tenet, but there’s always something that’s going to require your human intervention. That’s where the art comes in. After you run all these statistical techniques, when it comes down to drawing the final conclusion, you need your common sense.”
Statistical machine learning is a field that combines mathematics, probability, statistics, computer science, cognitive neuroscience and psychology to create models that learn from data and make predictions about the world. One of its earliest applications was when the U.S. Postal Service used it to learn and recognize handwritten letters and digits to autonomously sort letters. Now, it is applied in various settings from facial recognition technology on smartphones to self-driving cars.
Researchers developed different learning machines and statistical models that can be applied to a given problem, but there is no one-size-fits-all method that works well for all situations. Fokoué said selecting the appropriate method requires mathematical and statistical rigor, along with practical knowledge. His paper explains the central concepts and approaches, which he hopes will get more people involved in the field and harvesting its potential.
“Statistical machine learning is the main tool behind artificial intelligence,” Fokoué said. “It’s allowing us to construct extensions of the human being so our lives, transportation, agriculture, medicine and education can all be better. Thanks to statistical machine learning, you can understand the processes by which people learn and slowly and steadily help humanity access a higher level.”