AI based Content Creation and Product Recommendation Applications in E-commerce: An Ethical overview

Aditi M Jain and Ayush Jain

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025, vol. 11, issue 1, 3720-3728

Abstract: As e-commerce rapidly integrates artificial intelligence (AI) for content creation and product recommendations, these technologies offer significant benefits in personalization and efficiency. AI driven systems automate product descriptions, generate dynamic advertisements, and deliver tailored recommendations based on consumer behavior, as seen in major platforms like Amazon and Shopify. However, the widespread use of AI in e-commerce raises crucial ethical challenges, particularly around data privacy, algorithmic bias, and consumer autonomy. Bias—whether cultural, gender based, or socioeconomic—can be inadvertently embedded in AI models, leading to inequitable product recommendations and reinforcing harmful stereotypes. This paper examines the ethical implications of AI driven content creation and product recommendations, emphasizing the need for frameworks to ensure fairness, transparency, and need for more established and robust ethical standards. We propose actionable best practices to remove bias and ensure inclusivity, such as conducting regular audits of algorithms, diversifying training data, and incorporating fairness metrics into AI models. Additionally, we discuss frameworks for ethical conformance that focus on safeguarding consumer data privacy, promoting transparency in decision making processes, and enhancing consumer autonomy. By addressing these issues, we provide guidelines for responsibly utilizing AI in e-commerce applications for content creation and product recommendations, ensuring that these technologies are both effective and ethically sound.

Keywords: Ethical AI; Ethical AI in E-commerce; Respon-sible AI in E-commerce; AI-Driven Content Creation; Bias Miti-gation in E-commerce; Algorithmic Bias; Product Recommenda-tions AI; AI Ethics Frameworks; Fairness in AI; Transparency in AI (search for similar items in EconPapers)
Date: 2025
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2410414
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v11:y2025:i1:id:997

DOI: 10.32628/CSEIT2410414

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