Ethical and Legal Considerations behind the Prevalence of ChatGPT: Risks and Regulations
DOI:
https://doi.org/10.54097/fcis.v4i1.9418Keywords:
ChatGPT, Artificial Intelligence, Ethical Risks, Legal Risks, Regulating PathAbstract
In response to the prevalence of ChatGPT, this paper summarized its technical model, core capabilities, and application scenarios, analyzed the ethical risks such as autonomy, moral misconduct, human alienation, and value reconstruction, as well as legal risks such as legal entity status, copyright ownership, data security, and algorithmic black box. Then proposed the regulating principles of tool positioning, safety, legality, transparency, credibility, fairness, shared responsibility, and the regulating path of encouraging the development of autonomous, safe and controllable technologies, improving artificial intelligence legislation and justice, and establishing a diverse governance system.
Downloads
References
X. X. Ling, D.M. Wang, J. Yuan: Cold Thoughts on Ethics of Science, Technology and Academia after the Popularity of ChatGPT, Journal of Xinjiang Normal University (Philosophy and Social Sciences Edition), vol. 44 (2023), 1-14.
Information on https://k.sina.com.cn/ article_16495 97805 62 52dd6d01900zmro.html.
Information on https://www.thepaper. cn/news Detail_ forward _22444219.
Information on https: //www. thepaper. cn/news Detail_ forward _22750400.
Information on https://www. 163.com/ dy/article/ I3JB1QL10 514BQ68.html.
Information on http://www.moj. gov.cn/ pub/ sfbgw/ lfyjzj/ lflfyjzj /202304/t20230411_476092.html.
Information on https://www.163. com/dy/ article/ HVSJBNST 0553VCCF.html.
G. Uttazzo: Artificial consciousness: hazardous questions and answers, Artificial Intelligence in Medicine, vol. 44 (2008), 143-148.
P. O. Haikonen: Machine consciousness: new opportunities for information technology industry, International Journal of Machine Consciousness, vol. 1 (2009), 181-184.
M. Radovan: Computation and Understanding (IOS Press, U.S.A 1997), p.123-125.
A.J. Zhang, L. Jia: Algorithm "comfort zone" and its breaking out of cocoon -- also on the algorithm content of ChatGPT, Party and Government Research, vol. 1 (2023), 1-10.
C.S. Ma: Social Risks and Legal Regulation of Artificial Intelligence, Legal Science (Journal of Northwest University of Political Science and Law), vol. 36 (2018), 47-55.
M. P. Lynch: (2017). The Truth about Us: Why You're not as Smart as You Think You Are. (Electronic Industry Press, China 2017). p.65-66.
Information on http:/ /finance.china. com/ industrial/ 111 73306/ 20170612/30706950.html.
Z.Y. Li: Ultimate Replication - How Artificial Intelligence Will Promote Social Change (China Machine Press, China 2016), p.36-38. (In Chinese).
Z.H. Zheng: Ethical crisis and legal regulation of artificial intelligence algorithms, Legal Science (Journal of Northwest University of Political Science and Law), vol. 39 (2021), 14-26.
J. Markoff: A Brief History of Artificial Intelligence ( Zhejiang People's Publishing House, China 2017), p. 47-50. (In Chinese).
L.K. Zhu: The path and limits of giving strong artificial intelligence legal personality, Guangdong Social Sciences, vol. 5 (2021), 240-253.
C.X. Peng, J.D. Chen: On the Considerations of Legal Personality of Artificial Intelligence, Contemporary Law Review, vol. 33 (2019), 52-62.
X.Q. Liu: The Evolution of Criminal Responsibility in the Age of Artificial Intelligence: Yesterday, Today and Tomorrow, Law Science, vol. 1 (2019), 79-93.
Z. Zhu: How Attribution is Possible: Free Will and Legal Responsibility in the Age of Artificial Intelligence, Comparative Law Review, vol. 1. (2022), 39-54.
X.Q. Liu: Attribution and Nature Recognition of Criminal Responsibility for Artificial Intelligence Products, Journal of East China University of Political Science and Law, vol. 24 (2021), 50-59.
Q. Xiong: Determination of Copyright in Content Generated by Artificial Intelligence, Intellectual Property, vol. 3 (2017), 3-8.
J.P. Deng, Y.C. Zhu: Legal Risks of ChatGPT Model and Countermeasures, Journal of Xinjiang Normal University (Philosophy and Social Sciences Edition), vol. 5. (2023), 1-11.
Information on http:// finance. people. Com. cn/n1/ 2023/ 0210/ c1004-32621303.html.
Information on https://www. copyright. gov/ newsnet/ 2023/ 1004.html.
Information on https://www.sohu.com/a/638940097_161795.
Information on https://www.secrss.com/articles/51620.
J. Burrell: How the machine “thinks”: Understanding opacity in machine learning algorithms, Big Data & Society, vol. 3 (2016), 1-12.
J.J. Wu, W.E. Guo: Legalization Governance of Algorithmic Black Boxes in the Age of Artificial Intelligence, Science & Technology and Law (English & Chinese), vol. 1 (2021), 19-28.
Information on https://www. thepaper.cn/news Detail_ forward _22368224.
Information on https://epaper.gmw.cn/gmrb/html/2022-01/ 20/ nw. D110000gmrb_20220120_1-14.htm.
Information on http://www. xinhuanet.com/ tech/ 20230 130/ d4a5e32d5aef4ea181b5d6b74446d8bc/c.html.
R. Baldwin, M. Cave, M. Lodge: Understanding Regulation: Theory, Strategy, and Practice (SDX Joint Publishing Company, China 2017), p. 59-61. (In Chinese).


