Learning from AI Failures: Prevention and Best Practices

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This presentation explores AI failures, starting with their significance and common types. It delves into AI’s evolution, highlighting its role and technological foundations. We systematically study failure stages—from harmless mistakes to critical ethical issues—and identify causes such as design flaws, insufficient testing, and unpredictable data. Real-world examples illustrate these failures’ impact. Finally, we discuss preventative strategies, emphasising ethical development and best...