Deep Learning-Based Intelligent Robot in Sentencing

Abstract

This work aims to explore the application of deep learning-based artificial intelligence technology in sentencing, to promote the reform and innovation of the judicial system. First, the concept and the principles of sentencing are introduced, and the deep learning model of intelligent robot in trials is proposed. According to related concepts, the issues that need to be solved in artificial intelligence sentencing based on deep learning are introduced. The deep learning model is integrated into the intelligent robot system, to assist in the sentencing of cases. Finally, an example is adopted to illustrate the feasibility of the intelligent robot under deep learning in legal sentencing. The results show that the general final trial periods for cases of traffic accidents, copyright information, trademark infringement, copyright protection, and theft are 1,049, 796, 663, 847, and 201 days, respectively; while the final trial period under artificial intelligence evaluation based on the restricted Boltzmann deep learning model is 458, 387, 376, 438, and 247 days, respectively. The accuracy of trials is above 92%, showing a high application value. It can be observed that expect theft cases, the final trial period for others cases has been effectively reduced. The intelligent robot assistance under the restricted Boltzmann deep learning model can shorten the trial period of cases. The deep learning intelligent robot has a certain auxiliary role in legal sentencing, and this outcome provides a theoretical basis for the research of artificial intelligence technology in legal sentencing.

The Influence of Artificial Intelligence on Copyright Law

“…The breakthrough came with the advent of deep learning in the 2000s, a subset of machine learning that uses multi-layered neural networks to analyze various forms of data, such as images, sound, and text. Deep learning models have dramatically improved the performance of AI systems in tasks such as image and speech recognition, natural language processing, and decisionmaking, often surpassing human performance in specific domains (Chen, 2022;Ma, 2022). The continuous evolution of AI technologies, driven by advances in computational power, data availability, and algorithmic innovations, has expanded the scope of AI applications, transforming industries and society.…”

“…Thus, exploring the implications of AI on the notions of authorship and originality is imperative for adapting copyright law in the digital age. Furthermore, advancements in deep learning and neural networks have enabled AI to make decisions and generate content with minimal human intervention (Chen, 2022;Ma, 2022). This technological leap has significant implications for copyright law, as it T necessitates a reevaluation of the criteria for protection and the rights attributable to AI-generated works.…”