Risks, failures, and ethical dilemmas of AI technologies and trust

This chapter explores the risks, failures, and ethical dilemmas associated with artificial intelligence (AI) technologies, with a focus on their implications for public trust. While AI promises significant benefits across sectors, from health care to commerce, its rapid adoption also introduces risks at both individual and systemic levels. Issues such as data quality, algorithmic bias, and privacy concerns can lead to malfunctions and injustices that undermine the reliability of AI systems. Additionally, the inherent complexity of AI models, often operating as “black boxes,” complicates accountability and transparency, intensifying public concerns about trust and fairness. Ethical dilemmas arise in areas like algorithmic decision-making, where the lack of explainability and accountability questions the moral integrity of AI systems. This chapter emphasizes the need for sustainable and ethical AI design that aligns with societal values and legal standards to foster trust. International guidelines and ethical frameworks, such as those proposed by the European Union, highlight the importance of transparency, privacy, and accountability in AI. By addressing these ethical and operational challenges, stakeholders can contribute to a more responsible and trust-based integration of AI into society, ensuring its benefits while mitigating associated risks.