Using Predictive Justice Algorithms for Issuing Court Judgments with Efficient Prediction “development of Legal-tech Prospects in The Judiciary System in Iraq And Kurdistan Region”

Abstract

After the emergence of Artificial Intelligence-AI algorithms and the mechanisation of human life by combining the physical and digital dimensions of things, and harnessing this mechanisation to serve human civilisation by simulating human intelligence, through digital technology programs (Algorithm) and Machine Learning-ML models, the research suggests to the criminal-judicial institution of the Iraq and the Kurdistan Region, the use of the latest Deep Learning-DL model in the field of criminal justice, the Hybrid Neural Network, namely a Long Short-Term Memory-LSTM network with a Convolutional Neural Network-CNN, in order to predict court judgments effectively, using effective judicial data (DataSets), this would be achieve through the following steps: 1-Selecting priorities for judicial work; 2-Testing features with a high degree of reliability and accuracy within the total of legal data entered; 3-Choosing only the features that are most relevant to the legal case (Crime Analysis Process); 4-Using the LSTM-CNN model to predict the lawsuit judgments. Noting that the recent judicial authorities' use of this model showing accuracy with a percentage 92.05 and precision with a percentage of 93, recall with a percentage of 94, and F1-score 1 with a percentage of 93.