How to train artificial intelligence that won't destroy the environment

There's been a reckoning in recent years when it comes to measuring bias in machine learning. We now know that these "unbiased" automated tools are actually far from unprejudiced, and there's a growing demand that researchers think about how their products might screw over or endanger the lives of others before they unleash them on society. It's not just the final products we should be worried about, however, but also the consequences of building them. As the world burns in Facebook feeds and in backyards, the carbon footprints of even the most innocuous things are coming under scrutiny. It's sparked debates around AC units, straws, face scrubs, plastic bags, air travel.