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AI Bias in Marketing: Challenges, DEI Concerns, and Mechanisms for Ethical Innovation
Abstract
Artificial Intelligence is changing modern marketing through personalized engagement, trend prediction, and large-scale content generation. As generative models spread across advertising, consumer analytics, and creative work, worries about bias, fairness, and representation are increasing. When AI is trained on unbalanced data, it can reinforce stereotypes, misrepresent cultural identities, or ignore marginalized groups. This creates ethical and commercial risks related to DEI. Biased systems can damage consumer trust, harm brand reputation, and clash with new regulatory standards. This chapter looks at how bias shows up in marketing systems, why it matters, and what technical, organizational, and regulatory methods can promote more inclusive AI practices. It draws from literature, industry cases, and fairness frameworks. It outlines strategies like auditing datasets, designing inclusively, ensuring human oversight, and improving governance. Ultimately, it views DEI as the ethical basis for responsible AI marketing that can handle future challenges.
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