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  • 标题:Machine Learning Ethics in the Context of Justice Intuition
  • 本地全文:下载
  • 作者:Natalia Mamedova ; Arkadiy Urintsov ; Nina Komleva
  • 期刊名称:SHS Web of Conferences
  • 印刷版ISSN:2416-5182
  • 电子版ISSN:2261-2424
  • 出版年度:2019
  • 卷号:69
  • 页码:1-7
  • DOI:10.1051/shsconf/20196900150
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:The article considers the ethics of machine learning in connection with such categories of social philosophy as justice, conviction, value. The ethics of machine learning is presented as a special case of a mathematical model of a dilemma - whether it corresponds to  the  “learning”  algorithm  of  the  intuition  of   justice or not. It has been established that the use of machine learning for decision making has a prospect only within the limits of the intuition of justice field based on fair algorithms. It is proposed to determine the effectiveness of the decision, considering the ethical component and given ethical restrictions. The cyclical nature of the relationship between the algorithmic algorithms subprocesses in machine learning and the stages of conducting mining analysis projects using the CRISP methodology has been established. The value of ethical constraints for each of the algorithmic processes has been determined. The provisions of the Theory of System Restriction are applied to find a way to measure the effect of ethical restrictions on the “learning”  algorithm.
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