Abstract：With the development of artificial intelligence in deep learning technology in recent years, emotional computing and personality computing technology are maturing day by day and have achieved good performance in many practical application scenarios. Applying artificial intelligence emotional computing technology to the field of crime risk assessment can effectively solve the problem of intra-individual difference prediction factor assessment, which is difficult to be solved by current mainstream risk assessment tools, and the problem of distortion of results caused by social approval of participants being assessed. At present, the mainstream assessment tools are mainly structured clinical assessment tools and statistical actuarial assessment tools. The limitations of structured clinical violence risk assessment tools are mainly reflected in the following aspects: there are explanatory barriers to the inherent causal mechanism between mental disorders and violent crimes, and individuals with mental disorders may not necessarily have high risk of violent crimes; Although the statistical actuarial crime risk assessment tool performs well in prediction validity, it lacks the explanation of causal mechanism between prediction factors and criminal acts, so it is difficult to form a systematic explanation of the causes of criminal acts. A large number of relevant factors are incorporated into the statistical actuarial evaluation tool, which makes the tool more "bloated" and takes a lot of time to complete an evaluation. Most statistical actuarial evaluation tools obtain data through self-evaluation and self-presentation, which are easily affected by social approval effect and distort the data. The mainstream crime risk assessment tools are mainly applied to the field of crime risk assessment in prisons and re-crime risk assessment after leaving prison. Due to the long time-consuming operation of static assessment tools, the unwillingness of criminals in prisons to cooperate with the assessment work, and the serious deviation of assessment results from methods such as social approval effect, the static assessment tools are confronted with realistic difficulties such as assessment distortion, time-consuming and labor-consuming, and difficulty in realizing dynamic real-time crime risk assessment in prisons. In order to solve the above practical difficulties, a dynamic crime risk assessment tool based on emotional psychology and supported by artificial intelligence emotional computing technology has been developed, which focuses on solving the problems of violence risk and escape risk assessment that are the focus of crime risk assessment in prisons. The crime risk dynamic assessment tool is based on emotional psychology and supported by artificial intelligence emotional computing technology. It objectively observes and calculates the emotional time series state of the assessment object, and automatically obtains the emotional type and emotional fluctuation degree of the assessment object at a certain point in time. The dynamic criminal risk assessment tool based on emotional computing technology can solve the problem of risk factor assessment and prediction of intra-individual differences, which is difficult to solve with previous tools. At the same time, because emotion computing technology mainly uses cameras to collect individual image data, it does not need appraisers to answer questions, which can effectively avoid the appearance of social approval effect. The future development of the crime risk dynamic assessment tool is mainly to realize the echo with the static assessment tool to realize the measurement technology.