期刊文献+

强人工智能的刑事责任体系构建

On Building a System of Criminal Responsibility for Strong Artificial Intelligence
下载PDF
导出
摘要 关于强人工智能时代是否会来的争论持续不断,但是考虑到人工智能的飞速发展,我们应当对强人工智能的到来做好充足的应对。我国当前的刑事责任体系尚且能够应对弱人工智能所造成的社会危害,但难以应对强人工智能时代下的违法犯罪行为。究其本质,在于我们并未赋予强人工智能以法律主体地位,因此,人类应当在赋予强人工智能刑事责任主体地位的前提下,构建强人工智能的刑事责任体系。同时,根据智能化程度划分强人工智能的刑事责任能力,并将现有刑罚体系中的四种刑罚方式适用于将来的强人工智能。 There are endless debates about whether the era of strong artificial intelligence will come.However,given the rapid development of artificial intelligence,we must make adequate preparations for the advent of strong artificial intelligence.Although China’s current system of criminal responsibility can deal with the social harms caused by weak artificial intelligence,it is difficult to handle illegal and criminal acts in the era of strong artificial intelligence.The essential reason is that we have not granted strong artificial intelligence the status as a legal subject.Therefore,the human beings should build a system of criminal responsibility for strong artificial intelligence on the premise of granting strong artificial intelligence the status as a subject of criminal responsibility.At the same time,the strong artificial intelligence’s capacity for criminal responsibility should be divided according to the degree of its intelligence,and the four punishment methods in current system of criminal punishment can be applied to future strong artificial intelligence.
作者 纪康 李赫 Ji Kang;Li He(East China University of Political Science and Law,Shanghai 200042,China)
机构地区 华东政法大学
出处 《贵州警察学院学报》 2021年第1期53-59,共7页 Journal of Guizhou Police College
基金 国家社会科学基金重大项目(14ZDB147)
关键词 强人工智能 自主意识 刑事责任能力 神经科学 strong artificial intelligence independent consciousness capacity for criminal responsibility neuroscience
  • 相关文献

参考文献11

二级参考文献44

  • 1李亚宁.关于人工智能极限研究的哲学问题[J].四川大学学报(哲学社会科学版),1999(6):14-19. 被引量:5
  • 2王黔玲.人工智能会超过人类智能吗?[J].社会科学研究,1996(3):11-15. 被引量:3
  • 3徐春.以人为本与人类中心主义辨析[J].北京大学学报(哲学社会科学版),2004,41(6):33-38. 被引量:32
  • 4沈骊天.当代自然辩证法[M].南京:南京大学出版社,2000..
  • 5拉·梅特里.人是机器[M].北京:商务印书馆,1999.20.65.
  • 6[美]雷·库兹韦尔.奇点临近.李庆城,董振华,田源译.北京:机械工业出版社,2011:9.
  • 7唐旖浓.美国类脑芯片发展历程. [2016-5-21] .http://www. eepw.com.cn/article/271641.htm.
  • 8电子产品世界. 高通 zeroth 认知平台, 让手机认识世界. [2015-3-9]. http://www.eepw.com.cn/article/270655.htm.
  • 9Chen T, Du Z, Sun N, et al. Diannao: A small-footprint highthroughput accelerator for ubiquitous machine-learning//ACM Sigplan Notices. New York: ACM, 2014, 49(4): 269-284.
  • 10Chen Y, Luo T, Liu S, et al. Dadiannao: A machine-learning supercomputer//Proceedings of the 47th Annual IEEE/ ACM International Symposium on Microarchitecture. Washington:IEEE Computer Society, 2014: 609-622.

共引文献500

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部