Big Data and Knowledge

被引:4
|
作者
Palmirani, Monica [1 ]
机构
[1] Univ Bologna, Dipartimento Sci Giurid, CIRSHD, Via Galliera 3, I-40121 Bologna, Italy
来源
RIVISTA DI FILOSOFIA DEL DIRITTO-JOURNAL OF LEGAL PHILOSOPHY | 2020年 / 9卷 / 01期
关键词
Big data; Personal Data; Explicability; Knowledge Representation; Automated Decision-Making System; DECISION-MAKING; PARADIGM;
D O I
10.4477/97021
中图分类号
B [哲学、宗教];
学科分类号
01 ; 0101 ;
摘要
We intend to investigate the relationship between big data and artificial intelligence from the perspective of the right to explanation introduced by art. 22 GDPR, while also relying on the concepts of explicability and knowability. In the current debate, too much emphasis falls on algorithm transparency and less on the dataset. From a technical, legal, and philosophical perspective there is no right to arrive at a different independent opinion and to contradict the machine's decision if there is no transparency in the data that factored into the automated decision. In particular, counterfactual reasoning makes it necessary to change the antecedents in order to verify the consequents. This paper investigates the nature of big data, metadata, statistic and synthetic data, personal and nonpersonal data for demonstrating that explanation is a dynamic activity making it necessary to know the entire workflow from data to process.
引用
收藏
页码:73 / 91
页数:19
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