Research on the Legal Protection of the Right to be Forgotten in the Context of the Era of Artificial Intelligence

Xianjun Tan

doi:10.63313/LH.9015

Authors

Xianjun Tan School of Law, Anhui University of Finance and Economics, Bengbu 233000, China Author

DOI:

https://doi.org/10.63313/LH.9015

Keywords:

Artificial Intelligence, Generative AI, Right to be Forgotten, Personal Information

Abstract

While artificial intelligence technology has changed the production mode of hu-man society, it has also exacerbated the occurrence of personal information in-fringement. Deletion of personal information is an important manifestation of the right to be forgotten and an important way to protect the right to personal information. However, in the context of generative AI, the realization of the right to be forgotten faces both technical and institutional dilemmas, and it is difficult to implement both the current law and the traditional technology of deleting personal information. In order to strengthen the protection of the right to be forgotten, based on the "inclusive and prudent" legal policy, further standardize data collection, expand the interpretation of "deletion", and strengthen the ad-ministrative supervision of the process of generative AI processing personal in-formation. Through the above measures, a balance between the protection of the right to be forgotten and technological development can be achieved.

References

[1] World Bank Group Publication（2023）generative artificial intelligence. Washington: WBG,2023.

[2] European Union General Data Protection Regulation（2018） Article 17.

[3] Yang Lixin, Han Xu（2015）Localization and Legal Application of the Right to Be Forgotten in China. Journal of Law Application, 2015, 24-34.

[4] Zheng Zhifeng（2015）Research on the Right to Be Forgotten in Cyber Society. Studies in Law and Business, 2015, 50-60.

[5] Yu Shiwen, Zhu Xuefeng, Geng Libo（2015）Natural Language Processing Technologies and Deep Linguistic Computing. Social Sciences in China, 2015, 127-135.

[6] Github:DeepSeek-ai/DeepSeek-R1.https://github.com/deepseek-ai/DeepSeek-R1?tab=readme-ov-file

[7] Lin Beizheng（2024）No Deletion, Only Oblivion: Interpretation and Reconstruction of the Obligation to Delete Personal Information in AI Large Models. Journal of Xi'an Jiaotong University (Social Sciences), 2024, 152-165.

[8] WACHTER S, MITTELSTADT B. A right to reasonable inferences: re-thinking data pro-tec-tion law in the age of big data and AI. https://papers.ssrn.com/abstract=3248829.

[9] Zhang Tao（2022）Exploring the Dimensions of Risk Control Paths for Personal In-for-mation Protection. Law Science, 2022, 57-71.

[10] Xu Lei（2024）Integrated Regulation of Content Risks in Generative Artificial Intelli-gence. Publishing Research, 2024, 59-66.

[11] Cao Jianfeng（2023）Towards Trustworthy AI: Governance Challenges and Responses to Generative Artificial Intelligence Like DeepSeek. Journal of Shanghai University of Political Science and Law (Legal Forum), 2023, 28-42.

[12] Dou Xiaodong（2023）Risk and Control: On Personal Information Protection in Generative Artificial Intelligence Applications. Tribune of Political Science and Law, 2023, 59-68.

[13] Huang Pei（2024）Challenges and Regulatory Responses to Risks in Personal Information Protection Posed by Generative AI. Modern Law Science, 2024, 101-115.

[14] Deng Jianpeng, Zhu Yicheng（2023）Legal Risks and Countermeasures of the DeepSeek Model. Journal of Xinjiang Normal University (Edition of Philosophy and Social Sciences), 2023, 91-101+2.

[15] Hei Yiming, Chen Wentao, Chen Jie, et al（2024）A Review of Security Risk Assessment and Defense Technologies for Large Models. China Information Security, 2024, 24-27.