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Romanian-born Anca Dragan’s research focuses on algorithms that will enable robots
to work with, around, and in support of people. She runs the InterACT Laboratory at
Berkeley, where her students work across different applications, from assistive robots to
manufacturing to autonomous cars, and draw from optimal control, planning, estimation,
learning, and cognitive science. Barely into her thirties herself, she has co-authored a
number of papers with her veteran Berkeley colleague and mentor Stuart Russell which
address various aspects of machine learning and the knotty problems of value alignment.
She shares Stuart’s preoccupation with AI safety: “An immediate risk is agents
producing unwanted, surprising behavior,” she told an interviewer from the Future of
Life Institute. “Even if we plan to use AI for good, things can go wrong, precisely
because we are bad at specifying objectives and constraints for AI agents. Their
solutions are often not what we had in mind.”
Her principal goal is therefore to help robots and programmers alike to overcome
the many conflicts that arise because of a lack of transparency about each other’s
intentions. Robots, she says, need to ask us questions. They should wonder about their
assignments, and they should pester their human programmers until everybody is on the
same page—so as to avoid what she has euphemistically called “unexpected side
effects.”

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