Artificial intelligence researchers discuss bias in algorithms at Northeastern University for New England Machine Learning Day

Machine learning, which trains computers to accomplish specific tasks without receiving explicit instructions from humans, has become an increasingly valuable tool for a variety of industries. But the rapid incorporation of machine learning into marketing, finance, healthcare, and other fields has raised a range of ethical concerns that must be addressed. That was the message embraced by five artificial intelligence experts from academia and industry who convened at Northeastern on Friday to discuss the challenges of integrating machine learning into the workplace in order to improve processes and productivity. Researchers, they said, need to work to eliminate bias in algorithms, more accurately communicate to the public the limitations of machine learning, and build systems that prioritize the health and wellness of humans. "Machine learning has come to a point now where it is very central to essentially every branch of science and technology," said D. Sculley, a software engineer at Google.