[1]陈小平.人工智能中的封闭性和强封闭性——现有成果的能力边界、应用条件和伦理风险[J].智能系统学报,2020,15(1):114-120.[doi:10.11992/tis.202001001]
CHEN Xiaoping.Criteria of closeness and strong closeness in artificial intelligence——limits, application conditions and ethical risks of existing technologies[J].CAAI Transactions on Intelligent Systems,2020,15(1):114-120.[doi:10.11992/tis.202001001]
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CHEN Xiaoping.Criteria of closeness and strong closeness in artificial intelligence——limits, application conditions and ethical risks of existing technologies[J].CAAI Transactions on Intelligent Systems,2020,15(1):114-120.[doi:10.11992/tis.202001001]
人工智能中的封闭性和强封闭性——现有成果的能力边界、应用条件和伦理风险
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
15
期数:
2020年第1期
页码:
114-120
栏目:
学术论文—人工智能基础
出版日期:
2020-01-05
- Title:
- Criteria of closeness and strong closeness in artificial intelligence——limits, application conditions and ethical risks of existing technologies
- Keywords:
- artificial intelligence; closeness; strong-closeness; knowledge; grounding; decision-theoretical planning; reasoning; deep learning
- 分类号:
- TP18
- 摘要:
- 针对现有人工智能技术的两种代表性途径——暴力法和训练法，以及它们结合的一种典型方式，给出了规范化描述，AI研究中的知识被重新定义为从模型到现实场景的完闭降射，进而提出人工智能的封闭性准则和强封闭性准则。封闭性准则刻画了暴力法和训练法在理论上的能力边界；强封闭性准则刻画了暴力法和训练法在工程中的应用条件。两项准则还为开放性人工智能技术的进一步研究提供了新的概念基础。
- Abstract:
- Criteria of closeness and strong closeness in artificial intelligence (AI) are proposed in this paper. The first criterion suggests that knowledge in AI takes conceptual root in a kind of pragmatic correspondence, called consummated grounding, from a model to the scenario that the model is expected to represent. Consummated grounding is critical to advancing both development and explanation of intelligent systems. Under the condition of the second criterion, which aims at real-world applications, existing AI technology surpasses human beings in the same kind of ability, can be successfully applied to realize a lot of projects in current industries, and will not be out of control in itself. The criteria also set up a further conceptual basis for developing AI technology competent to deal with open scenarios.
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备注/Memo
收稿日期:2020-01-02。
基金项目:国家自然科学基金项目(U1613216)
作者简介:陈小平，教授，中国人工智能学会人工智能伦理道德专委会主任，主要研究方向为人工智能理论基础和智能机器人关键技术。提出基于“开放知识”的机器人智能技术路线，并在“可佳”和“佳佳”智能机器人系统中进行了持续性研究和工程实现。团队自主研发的“可佳”机器人2015年获国际服务机器人精确测试第一名，2014年获国际服务机器人标准测试第一名，2013年获第23届世界人工智能联合大会最佳自主机器人奖和通用机器人技能奖。2005年以来团队在机器人世界杯上先后获得12项世界冠军。多次获得国际学术会议最佳论文奖。获2010年度中科大“杰出研究”校长奖
通讯作者:陈小平.E-mail:xpchen@ustc.edu.cn
更新日期/Last Update:
1900-01-01