A to I without the E: artificial intelligence just isn’t that clever
While machine learning has shown itself useful for many things, it starts to flounder when the stakes go higher
What do Facebook co-founder Mark Zuckerberg and Tesla CEO Elon Musk have in common? Both are grappling with big problems that stem, at least in part, from putting faith in artificial intelligence systems that have underdelivered. Zuckerberg is dealing with algorithms that are failing to stop the spread of harmful content, Musk with software that has yet to drive a car in the ways he has frequently promised.
There is one lesson to be gleaned from their experiences: AI is not yet ready for prime time. Furthermore, it is hard to know when it will be. Companies should consider focusing on cultivating high-quality data — lots of it — and hiring people to do the work that AI is not ready to do.
Designed to loosely emulate the human brain, deep-learning AI systems can spot tumours, drive cars and write text, showing spectacular results in a lab setting. But therein lies the catch. When it comes to using the technology in the unpredictable real world, AI sometimes falls short. That’s worrying when it is touted for use in high-stakes applications such as healthcare...