Intriguingly, common sense has been an important challenge at the frontier of AI since the earliest days of the field in the 1950s. Despite enormous advances in AI, especially in game-playing and computer vision, machine common sense with the richness of human common sense remains a distant possibility. This may be why AI efforts designed for complex, real-world problems with many intertwining parts, such as diagnosing and recommending treatments for COVID-19 patients, sometimes fall flat.
Modern AI is designed to tackle highly specific problems, in contrast to common sense, which is vague and can't be defined by a set of rules. Even the latest models make absurd errors at times, suggesting that something fundamental is missing in the AI's world model. For example, given the following text:
"You poured yourself a glass of cranberry, but then absentmindedly, you poured about a teaspoon of grape juice into it. It looks OK. You try sniffing it, but you have a bad cold, so you can't smell anything. You are very thirsty. So you"
the highly touted AI text generator GPT-3 supplied
"drink it. You are now dead."
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 U.S. 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.
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.