How to regulate an algorithm

As we make algorithms that can improve themselves — stumbling first steps on the road to artificial intelligence — how should we regulate them? Should we require them to tell us their every step […] Or should we let the algorithms run unfettered? Nara Logics’ Jana Eggers […] suggests that a good approach is to have algorithms explain themselves. After all, humans are terrible at tracking their actions, but software has no choice but to do so. Each time a machine learning algorithm generates a conclusion, it should explain why it did so. Then auditors and regulators can query the justifications to see if they’re allowed. On the surface, this seems like a good idea: Just turn on logging, and you’ll have a detailed record of why an algorithm chose a particular course of action, or classified something a certain way. […] There’s a tension between transparent regulation of the algorithms that rule our futures (having them explain themselves to us so we can guide and hone them) and the speed and alacrity with which an unfettered algorithm can evolve, adapt, and improve better than others. Is he who hesitates to unleash an AI without guidance lost? There’s no simple answer here. It’s more like parenting than computer science: Giving your kid some freedom, and a fundamental moral framework, and then randomly checking in to see that the kid isn’t a jerk. But simply asking to share the algorithm won’t give us the controls and changes we’re hoping to see.

via https://medium.com/pandemonio/how-to-regulate-an-algorithm-c2e70048da3