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AI experts often don’t understand the internal processes and decision-making mechanisms of their AI black box models. This lack of accountability can lead to potential biases going unexamined and unchallenged. To promote the use of explainable AI and greater transparency and accountability in AI, legal practitioners should embrace the challenge of explainable AI, learn the basics of AI, and understand the importance of data. They should also consider the ethical implications of AI, use AI audit tools, and be aware of the legal implications of AI.