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1. Data Quality and Security: Ensuring the accuracy, integrity, and security of data is crucial, particularly in the face of increasing cyber threats and data breaches.
2. Bias and Fairness: AI algorithms must be designed to avoid bias and ensure fairness, transparency, and accountability.
3. Ethics and Responsibility: As AI becomes more pervasive, there is a growing need for ethics and responsibility in AI development and deployment.