IDGNS: What's the thing that most excites you about the field of AI at the moment that you think will have the biggest effect on your life?
MC: I hope by the time I'm retired the aging in place system has been worked out in great detail and I can take advantage of it.
As AI advances, some of the systems that exist right now in a limited form are going to become much more useful in the real world.
One of the big problems I see with the whole deep-learning explosion is, they tend to be focused on problems that you could say are more perceptual: You get an image or an audio clip or something and you classify the image or you produce the text that comes from that audio clip.
But real multi-step reasoning and planning and strategic thinking aren't currently a great strength of these AI systems, and that's where people come in. I was saying before how AI systems can help focus people on what matters:; I think people can focus AI systems on looking at problems or looking in directions where there's an intuition that there is something useful there.
That's where I see these systems developing in the next decade, humans bringing their skills to the mix, the machines bringing their skills and working together. I see that happening in practically every field, health care, education, aging in place, you name it.
IDGNS: You're building AI system at work, but do you use AI systems to help you in your work?
MC: As a researcher, I use tools, obviously; I use web searches and I have tools that help me look at the technical papers that come out and try and identify the ones that I should be focusing on. But when it comes to asking the interesting questions, what should I be working on, and identifying the most profitable or most likely directions that I should be doing research, I haven't seen a tool yet that can really help me. Obviously, that would be a great project that might make me as a researcher much more efficient if I could develop the AI tools that would help me do my job better.
IDGNS: Perhaps that will be the next big challenge?
That's certainly one of them, perhaps not the one that everybody out there thinks of because there are so many real-world problems that affect millions or even billions of people every day. But for the community that works in AI, we're inundated just like everybody else with information. The number of technical papers coming out every day is quite amazing even compared to five years ago, and we need help like everybody else.
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