An AI expert explains why it’s hard to give computers something you take for granted: Common sense
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Recent ambitious efforts have recognized machine common sense as a moonshot AI problem of our times, one requiring concerted collaborations across institutions over many years. A notable example is the four-year Machine Common Sense program launched in 2019 by the US. One reason to be optimistic about finally cracking machine common sense is the recent development of a type of advanced deep learning AI called transformers. Transformers are able to model natural language in a powerful way and, with some adjustments, are able to answer simple commonsense questions. Commonsense question answering is an essential first step for building chatbots that can converse in a human-like way. Defense Advanced Research Projects Agency to accelerate research in the field after the agency released a paper outlining the problem and the state of research in the field.
Even if you accept that some overlap and ambiguity in theories of common sense is inevitable, can researchers ever really be sure that an AI has common sense? We often ask machines questions to evaluate their common sense, but humans navigate daily life in far more interesting ways. People employ a range of skills, honed by evolution, including the ability to recognize basic cause and effect, creative problem solving, estimations, planning and essential social skills, such as conversation and negotiation. As long and incomplete as this list might be, an AI should achieve no less before its creators can declare victory in machine commonsense research.
It’s already becoming painfully clear that even research in transformers is yielding diminishing returns. Transformers are getting larger and more power hungry. A recent transformer developed by Chinese search engine giant Baidu has several billion parameters. It takes an enormous amount of data to effectively train. Yet, it has so far proved unable to grasp the nuances of human common sense.
The Machine Common Sense program funds many current research efforts in machine common sense, including our own, Multi-modal Open World Grounded Learning and Inference (MOWGLI). MOWGLI is a collaboration between our research group at the University of Southern California and AI researchers from the Massachusetts Institute of Technology, University of California at Irvine, Stanford University and Rensselaer Polytechnic Institute. The project aims to build a computer system that can answer a wide range of commonsense questions.
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August 20, 2021 at 1:33 PM #441203GZeusHParticipant
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They need to understand where the phrase comes from. Common, meaning belonging to all humans, and a sense, meaning a way of perceiving stimuli the world gives us. One common sense is “avoid getting bitten by an animal”. This comes fairly early, and while a toddler may not know how to avoid being bitten by a menacing animal, most people over 4 display those cautions. Until an AI program understands the pain of being bitten, and why you would want to avoid it, it’s not going to develop a human’s common sense on the topic.
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August 20, 2021 at 2:06 PM #441208djean111Participant
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The danger is in thinking it will not be error prone precisely because it is not human intelligence with human experience and human frames of reference. What seems right and correct to, say, Elon Musk will probably not be the same for you or me. Too many variables.
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Everything I post is just my opinion, and, honestly, I would love to be wrong.
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