Desafios éticos da precificação com inteligência artificial: uma análise interdisciplinar

• Ano de defesa: 2024
• Autor(a) principal: Schmiedel, Carlos Eduardo
• Orientador(a): Ramalho, Rogério de Sá
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Informação - PPGCI
• Palavras-chave em Português: Precificação ética; Inteligência artificial; Ciência da Informação; Algoritmos de IA; Transparência e responsabilidade; Impacto social; Inteligência artificial explicável (XAI)
• Área do conhecimento CNPq: CIENCIAS SOCIAIS APLICADAS::CIENCIA DA INFORMACAO::TEORIA DA INFORMACAO
• Link de acesso: https://hdl.handle.net/20.500.14289/22810

This master's dissertation explores the ethical challenges associated with the use of artificial intelligence (AI) in pricing strategies, offering an interdisciplinary analysis grounded in Information Science. As digital technologies increasingly permeate the retail sector, ethical considerations in AI-driven pricing mechanisms become crucial due to their significant social impacts, including potential discrimination and price manipulation. This research deeply examines the intersection of technology, ethics, and economics within pricing practices, focusing on the transformative role of AI in establishing dynamic and personalized pricing models. Through an extensive literature review and case study analysis, this study highlights the dual potential of AI to both enhance pricing efficiency and perpetuate unethical practices such as discriminatory pricing. It emphasizes the importance of ethical pricing not only in adhering to legal compliance but also in fostering consumer trust and corporate responsibility. The findings reveal that while technological advancements facilitate the implementation of sophisticated pricing models, they also raise significant ethical concerns that require rigorous transparency and regulatory oversight. The thesis advocates for the development of clear ethical pricing policies that outline fair pricing practices and improve transparency in AI applications. It proposes the integration of Explainable AI (XAI) to demystify AI operations for consumers, reducing suspicions of manipulation and promoting fairness. Additionally, it calls for robust regulatory frameworks aligned with the rapid pace of technological change to ensure that AI-enhanced pricing strategies positively contribute to social equity and corporate accountability. This research contributes to academic discourse by providing a nuanced understanding of the ethical implications of AI in pricing, offering guidelines for companies to implement ethical practices, and suggesting areas for future research in AI pricing regulation and governance. In doing so, it aims to pave the way for more equitable economic practices that harness the potential of AI while safeguarding against its risks.