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1.5 Analyzing AI LEGAL Issues Through the Lens of Trustworthiness

When AI systems lack trustworthiness, they can trigger not just technical failures, but serious social and legal conflicts. Case-based analysis reveals how trust, or its absence, shapes the way AI systems interact with and impact society.

This subsection explores AI trustworthiness issues through real-world examples, including legal liability controversies in autonomous vehicle accidents, bias in social media algorithms, and privacy violations due to poor data governance. These examples highlight unresolved risks as AI becomes more embedded in everyday decision-making, infrastructure, and social systems.

This section also examines why trust breaks down, what went wrong in each case, and how efforts to restore trust were implemented. By understanding both the risks of trust failure and the responses that followed, we can identify the conditions under which AI becomes not only effective, but socially legitimate.