Exploring Ethical Considerations and Their Influence on Sustainable Development Practices
Keywords:
AI, machine learning, trend prediction, rapid fashion, ethics, sustainability, excessive production, algorithmic prejudiceAbstract
This paper examines the ethical implications and sustainability impacts of AI-driven trend forecasting in the fast-fashion sector using secondary data (peer-reviewed articles, industry reports and reputable analyses). We synthesize literature on how machine learning and predictive analytics are used for trend discovery and demand prediction, outline the principal ethical concerns (privacy, algorithmic bias, accountability), and analyse how these technologies can both mitigate and worsen environmental harms (overproduction, GHG emissions, waste). The paper concludes with policy and managerial recommendations for aligning AI trend forecasting with sustainable fashion objectives. Key findings show that while AI offers opportunities to improve demand matching and reduce waste, current deployment in fast fashion risks accelerating short lifecycle trends and overproduction unless governance, transparency, and sustainability-oriented objectives are embedded into systems.
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