Legal risks refer to the potential for losses or adverse consequences that arise from the legal implications of actions, decisions, or events. In the context of machine learning, these risks can stem from issues such as bias in algorithms, violations of privacy laws, and failures to comply with regulations that govern data usage. Understanding these risks is crucial for ensuring fairness, accountability, and transparency in machine learning models.
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