Fake Data Could Help Solve Machine Learning's Bias Problem--if We Let It

Data is the lifeblood of artificial intelligence, and despite estimates that the world will generate more data over the next three years than it has in the previous 30, there still isn't enough of it to supply the booming A.I. industry. Amazon can predict your buying habits because its algorithms are trained on the data collected from its 112 million Prime subscribers in the U.S. and the tens of millions of other people around the world who visit the site and use its other products on a regular basis. Google's advertising business depends on predictive models fueled by the billions of internet searches it processes each day and data from the 2.5 billion devices running the Android operating system. The tech giants have carved out these massive data monopolies, and that gives them near-impenetrable advantages in the field of A.I. So how is a small A.I. startup to train its models to compete?