首页|Study Results from University of Chinese Academy of Social Sciences Update Under standing of Artificial Intelligence (The Challenge of Artificial Intelligence Sc ientists to the Epistemology of Science)
Study Results from University of Chinese Academy of Social Sciences Update Under standing of Artificial Intelligence (The Challenge of Artificial Intelligence Sc ientists to the Epistemology of Science)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting from the University of Chines e Academy of Social Sciences by NewsRx journalists, research stated, “ [Purpose/Significance] This study aims to explore the challeng es that artificially intelligent (AI) scientists may bring to scientific epistem ology. [Method/Process] Scientific discove ry has long been of interest to AI researchers. The next big step in AI is the d evelopment of AI scientists.” The news reporters obtained a quote from the research from University of Chinese Academy of Social Sciences: “AI scientists should be able to independently moti vate, make, understand, and communicate discoveries. Although the current robot scientists are still just a form of AI-driven automated experimental apparatus, and the best AI systems today cannot define their own hypothesis space and exper imental design. At best, they can be considered to be a primitive form of AI sci entists. Clearly, the specific path of AI-driven scientific research or the tran sition to AI scientists will inevitably be influenced by the frontier developmen t of AI. Current AI systems must overcome the following major technical challeng es: 1) making strategic choices in their research goals; 2) developing the abili ty to generate exciting and novel hypotheses in areas that push boundaries; 3) d esigning innovative approaches and experiments to test hypotheses that go beyond the use of prototype experiments; 4) focusing on and describing important disco veries in a way that can be understood by human scientists. The highly autonomou s AI scientists can either make discoveries on their own or collaborate with oth er human and machine scientists to make Nobel-level discoveries. After reviewing the relevant AI applications in scientific research, this study illustrates the main characteristics of AI scientists and the two disruptive changes they bring about at the epistemological level: a leap in AI capabilities and AI for Scienc e as the 5th paradigm of scientific research. [Results/Conclu sions] The implications of AI for Science are revolutionary, but recent AI-driven explorations in scientific research increasingly support th e possibility of its realization. In this situation, discussions on the epistemo logical issues of relevant sciences need to go beyond general philosophical deba tes and instead explore epistemological strategies for the coming scientific rev olution in AI. In view of the coming scientific revolution in AI, this study pro poses four strategies. First, we should pay more attention to the problems and s olutions in the process of developing AI scientists. Second, the key to advancin g the scientific revolution in AI is to find ways to eliminate factors that may lead to failure.”
University of Chinese Academy of Social SciencesArtificial IntelligenceEmerging TechnologiesMachine Learning
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