Experimental Methodology of Ethical Governance in Artificial Intelligence

人工智能伦理治理的实验方法论探究

Abstract

In recent years, the breakthrough development of artificial intelligence technology has brought a lot of convenience to human society, but at the same time, it has also brought risks and challenges that can not be underestimated. Therefore, a series of related research on the ethical governance of artificial intelligence have emerged. At present, the main governance strategies include the construction of ethical governance model and the advocacy of ethical service concept. This paper attempts to propose a third strategy as a parallel scheme, that is, to carry out ethical governance in artificial intelligence based on experimental methodology. The importance of carrying out ethical governance in artificial intelligence by experimental method lies in its ability to effectively improve the efficiency of identifying ethical risks, evaluating ethical governance framework and resolving ethical governance conflicts. Experimental approaches to ethical governance in artificial intelligence include computational experiments and social experiments. The former aims to simulate and test scenes with computer simulation technology, while the latter aims to study problems in real scenes through social investigation, social interview and other methods. These two experimental methods have their own implementation process and application scenarios, but there are also difficulties and problems in the actual development process. In general, carrying out ethical governance in artificial intelligence with experimental methods and exploring the risk impact mechanism through pre-designed controllable experiments are conducive to fundamentally improving the effectiveness of ethical governance in artificial intelligence and providing solutions for narrowing the gap from what it is to how to do in ethical governance in artificial intelligence.