Machine learning and artificial intelligence (AI) are exploding in popularity in fields ranging from art to science and everything in between—bioengineering included. While these tools have the potential to bring about significant improvements in healthcare, the systems aren’t perfect. How can we identify when machine learning and artificial intelligence are suggesting solutions that aren’t effective in the real world?
