I found this nice call for a talk held in Cambridge. I have to chase the organizers to see if the recorded the talk:

Most recent work on giving computers such “common sense” has focused on the use of formal logic and manual knowledge engineering. Instead, can we try a wider range of approaches? Can we build commonsense models using graphical models learned from sensory data or the web? Can we adopt a Wikipedia-like divide-and-conquer strategy? Can we use case-based reasoning, genetic programming, or reinforcement learning? The jury is still out about what methods people themselves use, but in building “human aware” systems we can look to a broader array of strategies that, together, could far exceed our own capabilities at commonsense thinking — leading, perhaps, to systems that understand people better than people understand themselves.