Analysis of Personal Data Preservation Policy in Utilizing AI-Based Chatbot Applications in Indonesia

Authors

  • Ilham Gemiharto Universitas Padjadjaran

DOI:

https://doi.org/10.25299/medium.v12i1.17772

Keywords:

AI-based chatbots, personal data protection, privacy policies, user awareness, regulatory landscape

Abstract

The increasing adoption of AI-based chatbot applications in Indonesia raises concerns about personal data preservation. This qualitative case study investigated the issue through in-depth interviews with chatbot users, developers, and government officials/regulators. This study's findings revealed a gap in user awareness of privacy policies and concerns about data misuse. Developers face challenges balancing personalization with privacy, while regulators acknowledge the need to continuously adapt the legal framework. The study recommends enhancing transparency, user empowerment, and regulatory oversight to ensure the responsible and ethical use of personal data in chatbot interactions.

Downloads

Download data is not yet available.

References

Anthony, C. J., Elliott, S. N., DiPerna, J. C., & Lei, P.-W. (2023). To be fair: Development and illustration of the Comprehensive Appraisal of Fairness Evidence (CAFE) model to advance SEL assessment practices. Social and Emotional Learning: Research, Practice, and Policy, 1, 100006. https://doi.org/10.1016/j.sel.2023.100006 DOI: https://doi.org/10.1016/j.sel.2023.100006

Butori, R., & Lancelot Miltgen, C. (2023). A construal level theory approach to privacy protection: The conjoint impact of benefits and risks of information disclosure. Journal of Business Research, 168, 114205. https://doi.org/10.1016/j.jbusres.2023.114205 DOI: https://doi.org/10.1016/j.jbusres.2023.114205

Chauncey, S. A., & McKenna, H. P. (2023). A framework and exemplars for ethical and responsible use of AI Chatbot technology to support teaching and learning. Computers and Education: Artificial Intelligence, 5, 100182. https://doi.org/10.1016/j.caeai.2023.100182 DOI: https://doi.org/10.1016/j.caeai.2023.100182

Cheng, X., Zhang, X., Yang, B., & Fu, Y. (2022). An investigation on trust in AI-enabled collaboration: Application of AI-Driven chatbot in accommodation-based sharing economy. Electronic Commerce Research and Applications, 54, 101164. https://doi.org/10.1016/j.elerap.2022.101164 DOI: https://doi.org/10.1016/j.elerap.2022.101164

Cheng, Z., Zhu, T., Zhu, C., Ye, D., Zhou, W., & Yu, P. S. (2023). Privacy and evolutionary cooperation in neural-network-based game theory. Knowledge-Based Systems, 282, 111076. https://doi.org/10.1016/j.knosys.2023.111076 DOI: https://doi.org/10.1016/j.knosys.2023.111076

Cherif, E., Bezaz, N., & Mzoughi, M. (2021). Do personal health concerns and trust in healthcare providers mitigate privacy concerns? Effects on patients’ intention to share personal health data on electronic health records. Social Science & Medicine, 283, 114146. https://doi.org/10.1016/j.socscimed.2021.114146 DOI: https://doi.org/10.1016/j.socscimed.2021.114146

Criado, N., & Such, J. M. (2015). Implicit Contextual Integrity in Online Social Networks. Information Sciences, 325, 48–69. https://doi.org/10.1016/j.ins.2015.07.013 DOI: https://doi.org/10.1016/j.ins.2015.07.013

Martens, M., De Wolf, R., Vadendriessche, K., Evens, T., & De Marez, L. (2021). Applying contextual integrity to digital contact tracing and automated triage for hospitals during COVID-19. Technology in Society, 67, 101748. https://doi.org/10.1016/j.techsoc.2021.101748 DOI: https://doi.org/10.1016/j.techsoc.2021.101748

Martínez-García, A., Alvarez-Romero, C., Román-Villarán, E., Bernabeu-Wittel, M., & Luis Parra-Calderón, C. (2023). FAIR principles to improve the impact on health research management outcomes. Heliyon, 9(5), e15733. https://doi.org/10.1016/j.heliyon.2023.e15733 DOI: https://doi.org/10.1016/j.heliyon.2023.e15733

Perdana, A., Lee, H. H., Koh, S., & Arisandi, D. (2021). Data analytics in small and mid-size enterprises: Enablers and inhibitors for business value and firm performance. International Journal of Accounting Information Systems, 100547. https://doi.org/10.1016/j.accinf.2021.100547 DOI: https://doi.org/10.1016/j.accinf.2021.100547

Riyadi, G. (2021). Data Privacy in the Indonesian Personal Data Protection Legislation. Retrieved from https://www.cips-indonesia.org/publications/data-privacy-in-the-indonesian-personal-data-protection-legislation DOI: https://doi.org/10.35497/341482

Sebastian, G. (2023). Privacy and Data Protection in ChatGPT and Other AI Chatbots. International Journal of Security and Privacy in Pervasive Computing, 15(1), 1–14. https://doi.org/10.4018/IJSPPC.325475 DOI: https://doi.org/10.4018/IJSPPC.325475

Syafrina, A. E., & Irwansyah. (2018). Privacy Threats in Big Data. Jurnal Penelitian Komunikasi Dan Opini Publik, 22(2). https://doi.org/10.33299/jpkop.22.2.1503 DOI: https://doi.org/10.33299/jpkop.22.2.1503

Downloads

Published

2024-06-30