AI Algorithm Evaluation and Regulation: Challenges and Countermeasures for Artificial Intelligence Risk Management

Artificial intelligence has been widely applied in various fields, and the evaluation and supervision of its algorithms have become important issues in artificial intelligence risk management. This article aims to explore the challenges faced by AI algorithm evaluation and regulation, and propose some solutions to promote the effective implementation of artificial intelligence risk management. This article mainly explores the regulatory challenges faced by AI algorithm evaluation from the perspectives of data privacy protection, algorithm inexplicability, fairness and bias, responsibility and accountability. And further analyze the impact of challenges on artificial intelligence risk management from aspects such as trust crisis caused by data privacy leakage, algorithm inexplicability that may weaken the reliability of risk prediction, and strengthen technical and legal means for data privacy protection, increase understanding and interpretation ability for the decision-making process of algorithms, establish fairness and bias detection mechanisms, and clarify responsibilities and accountability systems, Propose solutions and suggestions to address the challenges of AI algorithm evaluation and regulation, and call for cooperation from all sectors to jointly promote the development of artificial intelligence risk management.