Regulations on Three Big Data Discriminations Inducing Transaction Costs--From the Perspective of Legal Aid

DOI

10.2991/aebmr.k.210917.020How to use a DOI?

Keywords

Big Data Discrimination, Transaction Cost, Legal Aid

Abstract

Individuals in transactions suffer from three types of big data discrimination: biased selection, false association, and malicious recommendation, which could induce additional transaction cost. Through algorithm model, enterprises process and derive the initial data of individuals. In this process, enterprises have added unfavorable algorithmic judgment conditions for individuals, restricting the individual’s freedom of transaction and the right to choose, leading to unfairness in the transaction and increasing transaction cost for individuals. This article proposes that in order to suppress the adverse consequences of big data discrimination, data and algorithms should be included in regulatory objects at the same time, early warning mechanisms should be established, and supervising agencies should be stationed in data platforms by means of legal aid.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiu Ye
AU  - Huihui Dong
PY  - 2021
DA  - 2021/09/18
TI  - Regulations on Three Big Data Discriminations Inducing Transaction Costs--From the Perspective of Legal Aid
BT  - Proceedings of the 2021 International Conference on Financial Management and Economic Transition (FMET 2021)
PB  - Atlantis Press
SP  - 117
EP  - 121
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.210917.020
DO  - 10.2991/aebmr.k.210917.020
ID  - Ye2021
ER  -