Algorithmic Bias and Gender Representation: Feminist Perspectives on AI-Driven Marketing

Aarti and Dr Swati Chauhan
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Aarti: Manav Rachna International Institute of Research Studies Faridabad
Dr Swati Chauhan: Manav Rachna International Institute of Research Studies Faridabad

International Journal of Research and Innovation in Social Science, 2025, vol. 9, issue 16, 206-215

Abstract: The use of Artificial Intelligence and Machine Learning in marketing is increasing, leading to more personalized content and targeted advertising. However, concerns are being raised about biased algorithms, particularly regarding gender representation. Due to the use of biased historical data, AI systems can reinforce gender stereotypes and exclude women and non-binary individuals from marketing campaigns. This paper examines the implications of algorithmic bias in AI-based marketing from a feminist perspective, drawing parallels to critiques of gender portrayal and discrimination in literature. Feminist theories argue that technology is shaped by the biases of its designers. This can be seen in AI-powered marketing, where biased algorithms lead to advertisements that reinforce traditional gender stereotypes. This study reveals how these biases in digital advertising further marginalize and objectify marginalized groups. The research also draws parallels between the fight for gender equality in storytelling and the challenges faced in the digital world. A Room of One's Own by Virginia Woolf delves into the persistent issues of discrimination, dominance, and representation of gender, which are still relevant today. The book emphasizes the importance of women having autonomy and accurate portrayal, mirroring the current movement towards diverse and empowering AI models. The research highlights the need for a feminist and intersectional approach to address bias in marketing algorithms. It stresses the significance of using diverse training data and promoting transparency in creating ethical AI systems. The inclusion of literature in discussions is crucial in reshaping societal norms for a more equitable environment in AI-driven marketing. This paper emphasizes the importance of collaboration between technology, policies, and feminist discussions to ensure fair and diverse gender representation in AI marketing.

Date: 2025
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