Triple-Entry Accounting and Other Secure Methods to Preserve User Privacy and Mitigate Financial Risks in AI-Empowered Lifelong Education

Konstantinos Sgantzos (), Panagiotis Tzavaras, Mohamed Al Hemairy and Eva R. Porras
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Konstantinos Sgantzos: Department of Humanities, Social Sciences and Law, School of Applied Mathematical and Physical Sciences, National Technical University of Athens, Zografou Campus, 9, Iroon Polytechniou Str., 15772 Athens, Greece
Panagiotis Tzavaras: Department of Management and Marketing, School of Business Administration, European University Cyprus, P.O. Box 22006, 1516 Nicosia, Cyprus
Mohamed Al Hemairy: Research Institute of Science and Engineering [RISE], University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
Eva R. Porras: Department of Business Economics, Applied Economics II, and Fundamentals of Economic Analysis, Universidad Rey Juan Carlos, P.° de los Artilleros 38, Vicálvaro, 28032 Madrid, Spain

JRFM, 2025, vol. 18, issue 4, 1-21

Abstract: Within the past five years, and as Artificial Intelligence (AI) increasingly pervades the academic and educational landscape, a delicate balance has emerged between leveraging AI’s transformative potential and safeguarding individual privacy, which needs to be carefully maintained. The preservation of user privacy entails severe financial risks via penalties for the violation of directives such as General Data Protection Regulation (GDPR). This manuscript examines three neoteric approaches to data privacy protection in AI-empowered lifelong education. The first method uses Triple-Entry Accounting (TEA) together with Distributed Ledger Technology (DLT); the second method uses a transaction Merkle tree that can be used as a “proof of existence” so that the users can safeguard their personal information; and the third approach examines the advantages and disadvantages of an offline AI-tutor multimodal model that can operate without internet access. Finally, the ethical implications of deploying such technologies are critically discussed, emphasizing the necessity of achieving privacy while retaining the human factor in education.

Keywords: artificial intelligence; triple-entry accounting; distributed ledger technology; lifelong education; Merkle trees; data analysis; privacy (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2025
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