Abstract
The right to be forgotten has been evolving for decades along with the progress of different statutes and cases and, finally, independently enacted by the General Data Protection Regulation, making it widely applied across Europe. However, the related provisions in the regulation fail to enable machine learning systems to realistically forget the personal information which is stored and processed therein.
This failure is not only because existing European rules do not stipulate standard codes of conduct and corresponding responsibilities for the parties involved, but they also cannot accommodate themselves to the new environment of machine learning, where specific information can hardly be removed from the entire cyberspace. There is also evidence in the technical, legal, and social spheres to elaborate on the mismatch between the rules of the right to be forgotten and the novel machinery background based on the above reasons.
To mitigate these issues, this article will draw lessons from the cyberspace regulation theories and expound on their insights into realizing the right and the strategies they offered to reframe a new legal scheme of the right. This innovative framework entails a combination of technological, legal, and possibly social measures taken by online intermediaries which make critical decisions on the personal data given the so-called stewardship responsibilities. Therefore, the application of the right to be forgotten in the machinery landscape will plausibly be more effective.
Recommended Citation
Zeyu Zhao,
The Application of the Right to be Forgotten in the Machine Learning Context: From the Perspective of European Laws,
31
Cath. U. J. L. & Tech
73
(2022).
Available at:
https://scholarship.law.edu/jlt/vol31/iss1/5
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