JOURNAL OF DIALECTICS OF NATURE
A Comprehensive, Academic Journal of the Philosophy, History, Sociology and Cultural Studies of Science and Technology
Author Information
CHI Zhongjun
Information
<p>School of Marxism</p><p>China University of Mining and Technology</p><p>zjchi@cumt.edu.cn</p>
Research Articles
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Philosophical Reflection on the Hiding and Reconstructing of the Subject in the View of Big Data: Taking Educational Big Data as an Example Abstract: Educational big data can offer descriptive analysis and normative prediction of the subject behavior in educational activities by quantifying and calculating. However, educational big data technology not only transforms man, the subject of education, into readable data and information, but also constantly guides, directs, and promotes human behavior and activity. The core issue here is that the autonomy of human beings gives way to the technical system itself, that is, the main body of technical behavior has undergone a substantial shift. The underlying cause is the system of educational big data itself that pursues certainty obscures human beings, which leads to the concealment of the subject and triggers the objectification of the subject, the degeneration of inter-subjectivity communication, the absence of responsibility, and the paradox of subjectivity. There are three main strategies for solving these problems: improving the subject's data literacy, enhancing the transparency of the algorithm, and ensuring situational integrity of data and algorithmic decisions.Issue:Volume 40, lssue 11, November 2018Page: 1-10
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Ethical Reflections on Algorithmic Discrimination Abstract: Algorithmic discrimination involves three ethical issues: algorithmic fairness, the stigmatization of algorithmic identity, and privacy. The reasons are as follows: First, algorithmic discrimination can be caused by the preexisting bias in the data; Second, using algorithms itself may be a form of discrimination; Third, the sampling bias of the data and different weight settings in the algorithmic decision-making may also lead to algorithmic discrimination. Therefore, algorithmic discrimination can be avoided from three directions: the technical approach, the philosophic approach and the approach of rule of law, so as to realize algorithmic fairness.Issue:Volume 41, lssue 10, October 2019Page: 16-23
JOURNAL OF DIALECTICS OF NATURE
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