This study critically explores the ethical dimensions of Artificial Intelligence (AI) in digital marketing, with a particular emphasis on AI accountability and fairness among online consumers in Palestine. Employing a quantitative research design, the study utilizes Structural Equation Modeling (SEM) to analyze data collected from 385 participants. The primary aim is to examine how AI-driven marketing strategies shape perceptions of fairness, with accountability acting as a mediating variable. The results demonstrate that AI accountability significantly mediates the relationship between AI-generated marketing content and consumer perceptions of fairness, highlighting the critical role of accountability in promoting ethical AI practices. This research underscores the pressing need for transparency in AI systems, as well as the importance of mitigating algorithmic biases that may adversely affect consumer experiences. The findings offer actionable insights for businesses and policymakers, advocating for the development of comprehensive regulatory frameworks that ensure the ethical application of AI technologies in marketing while fostering consumer trust. By contributing to the ongoing discourse on AI ethics, this study provides a robust foundation for understanding the complex interplay between AI technologies, fairness, and accountability in digital marketing. These insights are particularly pertinent to industries leveraging AI for content creation, as they navigate the ethical challenges associated with consumer engagement in an increasingly digitalized environment.
Published in | Social Sciences (Volume 14, Issue 3) |
DOI | 10.11648/j.ss.20251403.14 |
Page(s) | 220-232 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2025. Published by Science Publishing Group |
Artificial Intelligence, Digital Marketing, AI Accountability, AI Fairness, Ethical Marketing
[1] | AI, N. (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). |
[2] | Aristotle. (EN). Nicomachean ethics (W. D. Ross, Trans.). The Internet Classics Archive. |
[3] | Basri, W. (2020). Examining the impact of artificial intelligence (AI)-assisted social media marketing on the performance of small and medium enterprises: toward effective business management in the Saudi Arabian context. International Journal of Computational Intelligence Systems, 13(1), 142-152. |
[4] | Benabdelouahed, R., & Dakouan, C. (2020). The use of artificial intelligence in social media: opportunities and perspectives. Expert journal of marketing, 8(1), 82-87. |
[5] | Biswal, B. K., Choudhary, S. L., Dixit, R. S., Srivastava, P., & Kumar, M. (2023). Exploring the Ethical Use of Artificial Intelligence in Marketing and Advertising. Journal of Informatics Education and Research, 3(2). |
[6] | Chollett, I., Escovar‐Fadul, X., Schill, S. R., Croquer, A., Dixon, A. M., Beger, M.,... Wolff, N. H. (2022). Planning for resilience: Incorporating scenario and model uncertainty and trade‐offs when prioritizing management of climate refugia. Global Change Biology. |
[7] | Coeckelbergh, M. (2020). AI ethics. MIT Press. |
[8] | Deng, G., Zhang, J., & Xu, Y. (2024). How e-commerce platforms build channel power: the role of AI resources and market-based assets. Journal of Business & Industrial Marketing, 39(2), 173-188. |
[9] | Du, S., & Xie, C. (2021). Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities. Journal of Business Research, 129, 961-974. |
[10] | Eickhoff, F., & Zhevak, L. (2023). The consumer attitude towards AI in marketing: An experimental study of consumers attitudes and purchase intention. In. |
[11] | Fedorko, R., Kráľ, Š., & Fedorko, I. (2022). Artificial Intelligence and Machine Learning in the Context of E-commerce: A Literature Review. Communication and Intelligent Systems: Proceedings of ICCIS 2021, 1067-1082. |
[12] | Gao, B., Wang, Y., Xie, H., Hu, Y., & Hu, Y. (2023). Artificial Intelligence in Advertising: Advancements, challenges, and ethical considerations in targeting, personalization, content creation, and ad optimization. SAGE Open, 13(4), 21582440231210759. |
[13] | Gonçalves, A. R., Pinto, D. C., Rita, P., & Pires, T. (2023). Artificial Intelligence and Its Ethical Implications for Marketing. Emerging Science Journal, 7(2), 313-327. |
[14] |
Gordon, J.-S., & Nyholm, S. (2021). Ethics of artificial intelligence. In Internet Encyclopedia of Philosophy.
https:// iep. utm. edu/ ethics- of- artificial- intel ligen c. |
[15] | Hagendorff, T. (2020). The ethics of AI ethics: An evaluation of guidelines. Minds and machines, 30(1), 99-120. |
[16] | Hanlon, A. (2020). Ethics in digital marketing and social media. The SAGE Handbook of Marketing Ethics, 424. |
[17] | ISO/IEC TR 24368:2022. (2022). Information technology — Artificial intelligence — Overview of ethical and societal concerns. International Organization for Standardization. |
[18] | Kant, I. (1797). The metaphysics of morals (Rev. ed.). Cambridge University Press, 1996. |
[19] | Kim, J., Giroux, M., & Lee, J. C. (2021). When do you trust AI? The effect of number presentation detail on consumer trust and acceptance of AI recommendations. Psychology & Marketing, 38(7), 1140-1155. |
[20] | Latan, H., Hair Jr, J. F., Noonan, R., & Sabol, M. (2023). Introduction to the partial least squares path modeling: Basic concepts and recent methodological enhancements. In Partial Least Squares path modeling: Basic concepts, methodological issues and applications (pp. 3-21). Cham: Springer International Publishing. |
[21] | Lintulahti, N. (2023). Creating a strategy for AI integration in content marketing. |
[22] | MacIntyre, A. (1981). After virtue: A study in moral theory. University of Notre Dame Press. |
[23] | Mbiazi, D., Bhange, M., Babaei, M., Sheth, I., & Kenfack, P. J. (2023). Survey on AI Ethics: A Socio-technical Perspective. arXiv preprint arXiv:2311.17228. |
[24] | Mgiba, F. (2020). Artificial intelligence, marketing management, and ethics: their effect on customer loyalty intentions: a conceptual study. The Retail and Marketing Review, 16(2), 18-35. |
[25] | Mittelstadt, B. (2019). Principles alone cannot guarantee ethical AI. Nature machine intelligence, 1(11), 501-507. |
[26] | Muhammadian, R. (2020). Artificial intelligence in marketing. How AI is Revolutionizing Digital Marketing. |
[27] |
Müller, V. C. (2020). Ethics of artificial intelligence and robotics. In E. N. Zalta (Ed.), Stanford Encyclopedia of Philosophy (Summer 2020 Edition).
https://plato.stanford.edu/archives/sum2020/entries/Press.ethics-ai/ |
[28] | Naz, H., & Kashif, M. (2024). Artificial intelligence and predictive marketing: an ethical framework from managers’ perspective. Spanish Journal of Marketing-ESIC. |
[29] | Novelli, C., Taddeo, M., & Floridi, L. (2023). Accountability in artificial intelligence: what it is and how it works. AI & SOCIETY, 1-12. |
[30] | Preeti Bharti. (2023). The Ethics of AI in Online Marketing: Examining the Impacts on Consumer privacy and Decision-making. |
[31] | Purwanto, A. (2021). Partial Least Squares Structural Squation Modeling (PLS-SEM) Analysis for Social and Management Research: A Literature Review. Journal of Industrial Engineering & Management Research, 2, 114-123. |
[32] | Rabbi, S. N. (2024). Ai in Digital marketing. |
[33] | Rabby, F., Chimhundu, R., & Hassan, R. (2021). Artificial intelligence in digital marketing influences consumer behaviour: A review and theoretical foundation for future research. Academy of marketing studies journal, 25(5), 1-7. |
[34] | Rathore, B. (2016). AI and the Future of Ethical Fashion Marketing: A Comprehensive Analysis of Sustainable Methods and Consumer Engagement. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 5(2), 14-24. |
[35] | Romele, A. (2022). Images of Artificial Intelligence: A Blind Spot in AI Ethics. Philosophy & Technology, 35(1), 1–19. |
[36] | Russell, S., & Norvig, P. (2014). Artificial intelligence: A modern approach (3rd ed.). Pearson. |
[37] | Schuberth, F., Rademaker, M. E., & Henseler, J. (2023). Assessing the Overall Fit of Composite Models Estimated by Partial Least Squares Path Modeling. European Journal of Marketing, 57(6), 1678-1702. |
[38] | Shaik, M. (2023). Impact of artificial intelligence on marketing. East Asian Journal of Multidisciplinary Research, 2(3), 993-1004. |
[39] | Turing, A. M. (2009). Computing machinery and intelligence. In Robert Epstein, Gary Roberts, & G. |
[40] | Winner, L. (1977). Autonomous technology: Technics-out-of-control as a theme in political thought. MIT. |
APA Style
Jadallah, N. I. (2025). Unveiling AI Ethics in Digital Marketing: A Study on Accountability and Fairness among Social Media Users in Palestine. Social Sciences, 14(3), 220-232. https://doi.org/10.11648/j.ss.20251403.14
ACS Style
Jadallah, N. I. Unveiling AI Ethics in Digital Marketing: A Study on Accountability and Fairness among Social Media Users in Palestine. Soc. Sci. 2025, 14(3), 220-232. doi: 10.11648/j.ss.20251403.14
@article{10.11648/j.ss.20251403.14, author = {Najwan Ibrahim Jadallah}, title = {Unveiling AI Ethics in Digital Marketing: A Study on Accountability and Fairness among Social Media Users in Palestine }, journal = {Social Sciences}, volume = {14}, number = {3}, pages = {220-232}, doi = {10.11648/j.ss.20251403.14}, url = {https://doi.org/10.11648/j.ss.20251403.14}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ss.20251403.14}, abstract = {This study critically explores the ethical dimensions of Artificial Intelligence (AI) in digital marketing, with a particular emphasis on AI accountability and fairness among online consumers in Palestine. Employing a quantitative research design, the study utilizes Structural Equation Modeling (SEM) to analyze data collected from 385 participants. The primary aim is to examine how AI-driven marketing strategies shape perceptions of fairness, with accountability acting as a mediating variable. The results demonstrate that AI accountability significantly mediates the relationship between AI-generated marketing content and consumer perceptions of fairness, highlighting the critical role of accountability in promoting ethical AI practices. This research underscores the pressing need for transparency in AI systems, as well as the importance of mitigating algorithmic biases that may adversely affect consumer experiences. The findings offer actionable insights for businesses and policymakers, advocating for the development of comprehensive regulatory frameworks that ensure the ethical application of AI technologies in marketing while fostering consumer trust. By contributing to the ongoing discourse on AI ethics, this study provides a robust foundation for understanding the complex interplay between AI technologies, fairness, and accountability in digital marketing. These insights are particularly pertinent to industries leveraging AI for content creation, as they navigate the ethical challenges associated with consumer engagement in an increasingly digitalized environment. }, year = {2025} }
TY - JOUR T1 - Unveiling AI Ethics in Digital Marketing: A Study on Accountability and Fairness among Social Media Users in Palestine AU - Najwan Ibrahim Jadallah Y1 - 2025/05/22 PY - 2025 N1 - https://doi.org/10.11648/j.ss.20251403.14 DO - 10.11648/j.ss.20251403.14 T2 - Social Sciences JF - Social Sciences JO - Social Sciences SP - 220 EP - 232 PB - Science Publishing Group SN - 2326-988X UR - https://doi.org/10.11648/j.ss.20251403.14 AB - This study critically explores the ethical dimensions of Artificial Intelligence (AI) in digital marketing, with a particular emphasis on AI accountability and fairness among online consumers in Palestine. Employing a quantitative research design, the study utilizes Structural Equation Modeling (SEM) to analyze data collected from 385 participants. The primary aim is to examine how AI-driven marketing strategies shape perceptions of fairness, with accountability acting as a mediating variable. The results demonstrate that AI accountability significantly mediates the relationship between AI-generated marketing content and consumer perceptions of fairness, highlighting the critical role of accountability in promoting ethical AI practices. This research underscores the pressing need for transparency in AI systems, as well as the importance of mitigating algorithmic biases that may adversely affect consumer experiences. The findings offer actionable insights for businesses and policymakers, advocating for the development of comprehensive regulatory frameworks that ensure the ethical application of AI technologies in marketing while fostering consumer trust. By contributing to the ongoing discourse on AI ethics, this study provides a robust foundation for understanding the complex interplay between AI technologies, fairness, and accountability in digital marketing. These insights are particularly pertinent to industries leveraging AI for content creation, as they navigate the ethical challenges associated with consumer engagement in an increasingly digitalized environment. VL - 14 IS - 3 ER -