As AI technology continues to evolve,it plays an increasingly significant role in everyday life and social governance.However,the frequent occurrence of issues such as algorithmic bias,privacy breaches,and data leaks ...As AI technology continues to evolve,it plays an increasingly significant role in everyday life and social governance.However,the frequent occurrence of issues such as algorithmic bias,privacy breaches,and data leaks has led to a crisis of trust in AI among the public,presenting numerous challenges to social governance.Establishing technical trust in Al,reducing uncertainties in AI development,and enhancing its effectiveness in social governance have become a consensus among policymakers and researchers.By comparing different types of AI,the paper proposes and conceptualizes the idea of trustworthy Al,then discusses its characteristics and its value and impact pathways in social governance.The analysis addresses how mismatches in technological trust can affect social stability and the advancement of AI strategies.The paper highlights the potential of trustworthy AI to improve the efficiency of social governance and solve complex social problems.展开更多
Artificial intelligence(AI) has accelerated the advancement of financial services by identifying hidden patterns from data to improve the quality of financial decisions. However, in addition to commonly desired attrib...Artificial intelligence(AI) has accelerated the advancement of financial services by identifying hidden patterns from data to improve the quality of financial decisions. However, in addition to commonly desired attributes,such as model accuracy, financial services demand trustworthy AI with properties that have not been adequately realized. These properties of trustworthy AI are interpretability, fairness and inclusiveness, robustness and security,and privacy protection. Here, we review the recent progress and limitations of applying AI to various areas of financial services, including risk management, fraud detection, wealth management, personalized services, and regulatory technology. Based on these progress and limitations, we introduce FinBrain 2.0, a research framework toward trustworthy AI. We argue that we are still a long way from having a truly trustworthy AI in financial services and call for the communities of AI and financial industry to join in this effort.展开更多
文摘As AI technology continues to evolve,it plays an increasingly significant role in everyday life and social governance.However,the frequent occurrence of issues such as algorithmic bias,privacy breaches,and data leaks has led to a crisis of trust in AI among the public,presenting numerous challenges to social governance.Establishing technical trust in Al,reducing uncertainties in AI development,and enhancing its effectiveness in social governance have become a consensus among policymakers and researchers.By comparing different types of AI,the paper proposes and conceptualizes the idea of trustworthy Al,then discusses its characteristics and its value and impact pathways in social governance.The analysis addresses how mismatches in technological trust can affect social stability and the advancement of AI strategies.The paper highlights the potential of trustworthy AI to improve the efficiency of social governance and solve complex social problems.
基金Project supported by the National Natural Science Foundation of China (Nos. 62172362 and 72192823)。
文摘Artificial intelligence(AI) has accelerated the advancement of financial services by identifying hidden patterns from data to improve the quality of financial decisions. However, in addition to commonly desired attributes,such as model accuracy, financial services demand trustworthy AI with properties that have not been adequately realized. These properties of trustworthy AI are interpretability, fairness and inclusiveness, robustness and security,and privacy protection. Here, we review the recent progress and limitations of applying AI to various areas of financial services, including risk management, fraud detection, wealth management, personalized services, and regulatory technology. Based on these progress and limitations, we introduce FinBrain 2.0, a research framework toward trustworthy AI. We argue that we are still a long way from having a truly trustworthy AI in financial services and call for the communities of AI and financial industry to join in this effort.
