Research On The Risks Of Algorithmic Governance In The Age Of Big Data

At present,governments of various countries are increasingly applying algorithmic governance in many different fields,from the police and legal systems to processing visa applications and helping doctors to save patients.Algorithmic governance is used to improve the efficiency and accuracy of government work and policy.However,there are many risks in the application of algorithm governance within the context of big data,such as fairness,discrimination against minority groups,ethics,opaque decision-making,lack of a definition of fairness in the algorithmic governance system,and discrimination via data collection.These risks will have consequences for policy makers.Although the government has a certain degree of transparency due to its legal framework,countries around the world currently do not have any system to review algorithmic systems before using them and each national government department has not defined when algorithms should and should not be used,how to implement the algorithm and what kind of ethical and fairness standards should be used when implementing algorithmic decision making systems.Thus governments lack the strict standards required to prevent the potential risks of algorithm governance and existing risk control systems are in adequate.Therefore,in the age of big data,understanding the risks of algorithmic governance and controlling them is even more important in the age of big data.The research focus of this article will be on how governments of various countries integrate big data algorithms into their government work.By studying the structure of big data algorithms used within governments this research hope to futher understand how these algorithms are utlised and,in the process,how the governments are trying to control the risks associated with these systems.The research will also propose a new regulatory system,how to implement this regulatory system quickly,economically,and efficiently to better control the risks associated with algorithm governance and improve citizens trust in algorithmic decision making.