<ul><li>AI systems lack intuition, empathy, and contextual awareness, making them prone to failures in real-world unpredictable situations.</li><li>Biases in AI, reflecting the data it is fed, can lead to societal failures and real-world consequences, such as racial disparities in healthcare and biased decision-making in law enforcement.</li><li>AI failures can have life-or-death consequences, as seen in the case of Uber's self-driving car accident and financial mishaps, like the Knight Capital trading algorithm misfiring.</li><li>Investing in rigorous AI testing is crucial for avoiding disasters, earning customer trust, complying with regulations, and safeguarding the future.</li></ul>

The Hidden Risks of AI: Why Rigorous Testing is the Key to Success

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