经济
计算机科学
标准模型(数学公式)
风险分析(工程)
数理经济学
业务
量具(枪械)
历史
考古
标识
DOI:10.1093/oxrep/grab013
摘要
Abstract The standard model for developing AI systems assumes a fixed, known objective that the AI system is required to optimize through its actions. Systems developed within the standard model have been increasingly successful. I briefly summarize the state of the art and its likely evolution over the next decade. Substantial breakthroughs leading to general-purpose AI are much harder to predict, but they will have an enormous impact on the global economy and on human roles therein. At the same time, I expect that the standard model will become increasingly untenable in real-world applications because of the difficulty of specifying objectives completely and correctly. I propose a new model for AI development in which the machine’s uncertainty about the true objective leads to qualitatively new modes of behaviour that are more robust, controllable, and deferential.
科研通智能强力驱动
Strongly Powered by AbleSci AI