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Navigating the Ethical Frontier: AI-Driven Advertising and Bias Mitigation

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  • Ameya Gokhale

Abstract

Integrating AI and Large Language Models in advertising has transformed the digital marketing landscape through enhanced personalization, predictive audience segmentation, and automated content generation. While these advancements have significantly improved campaign effectiveness and targeting accuracy, they also present critical ethical challenges, particularly in algorithmic bias and data privacy concerns. This article examines the manifestation of bias in ad targeting, content generation, and audience segmentation, while proposing comprehensive technical solutions for bias mitigation. Organizations can achieve ethical compliance and advertising effectiveness by implementing bias-aware frameworks, human-AI collaborative systems, and transparent technical architectures. The article demonstrates that properly integrating ethical considerations and transparent data practices can enhance consumer trust while maintaining high performance in AI-driven advertising systems.

Suggested Citation

  • Ameya Gokhale, 2025. "Navigating the Ethical Frontier: AI-Driven Advertising and Bias Mitigation," International Journal of Computing and Engineering, CARI Journals Limited, vol. 7(7), pages 14-24.
    • Handle: RePEc:bhx:ojijce:v:7:y:2025:i:7:p:14-24:id:2927
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    File URL: https://carijournals.org/journals/IJCE/article/view/2927
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    References listed on IDEAS

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    1. Hosahally, Shashank & Bharadwaj, Madan & Zaremba, Arkadiusz & Volkova, Olena, 2025. "Measuring digital advertising in a post-cookie era: A study of marketing-mix models, attribution and incrementality," Journal of Digital & Social Media Marketing, Henry Stewart Publications, vol. 12(4), pages 348-373, March.
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