Forbes profiles Anca Dragan, one of CITRIS’s most prominent A.I. researchers, working in the Center for Human-compatible A.I. at CITRIS.
Forbes – Anca Dragan has a cool name, an impressive CV and an important job. While many roboticists focus on making AI better, faster and smarter, Dragan is also concerned about robot quality control. In anticipation of robots moving into every area of our lives, she wants to ensure our interactions with robots are positive ones. The computer scientist and robotics engineer is a principal investigator with UC Berkeley’s Center for Human-Compatible AI. “One particular area of interest is the problem of value alignment,” says Dragan. “How do you ensure that an artificially intelligent agent–be it a robot a few years from now or a much more capable agent in the future–how do you make sure that these agents optimize the right objectives? How do we teach them to optimize what we actually want optimized?”
Preventing undesirable robot behavior is becoming a priority as robots get more intelligent, more nimble and increasingly autonomous. It’s something a lot of people feel uneasy about, even if most of us don’t know enough about AI to put our concerns into quite the right words.
Finding the right words and dealing with communication breakdowns are at the very heart of a problem Dragan’s trying to tackle. She’s developing a new paradigm for machine learning to teach robots to do what we want–even if we can’t articulate what we really want.
That’s literally not what I want.
With traditional AI learning models, the robot designer programs a piece of code that specifies a utility function. The robot moves through the world automated by this code, its directive. But capturing desirable behavior in a piece of code leaves robots considerably error-prone. We humans skip over a lot of important information when we specify what we want. For instance, you may want a windfall of cash with zero effort. Lacking the moral framework encoded in our DNA and reinforced by our social norms, the robot could determine the best way to get you what you want is to kill your parents for the inheritance. Endless possible sci-fi horror movie scenarios play out without the benefit of context, guidance and real-time stopgaps to interrupt a baby robot’s perversion of logic.
Professor Dragan adds acknowledgment to her collaborators on this work: Dylan Hadfield Menell, Smitha Milli, Pieter Abbeel, and Stuart Russell.
Read the original article: https://www.forbes.com/sites/andreamorris/2018/02/07/keeping-robots-friendly-meet-the-woman-teaching-ai-about-human-values/#1392b1e060f9
Photo credit: Noah Berger