Bias and Fairness: Biases from the data that AI systems are trained on may be inherited by the systems, resulting in discrimination, unjust outcomes, and the maintenance of social injustices.

Ethical Concerns: The application of AI brings up moral concerns like accountability, privacy, monitoring, and autonomy. Frameworks and rules are required to guarantee ethical AI development and application.

Interpretability: It might be difficult to comprehend how AI models, particularly deep learning models, make decisions because many of them are regarded as "black boxes." To promote transparency and foster trust, interpretable AI is essential.

Data Privacy: Large data sets are frequently used by AI systems, which raises questions about data security and privacy. Data misuse or unauthorized access might result in privacy violations and other dangers.

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