Application of Machine Learning Based Assumptions in Legal Profession-An Appraisal

Algorithms that integrate Artificial and Machine learning have the potential to significantly impact several industries, including the legal sector. The application of AI and ML offers promise for the backlog of cases, inefficiency, and access to justice in India's judicial system. In this post...

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Bibliographic Details
Published in2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE) pp. 827 - 832
Main Authors Singh, Devendra, Kumar, Santosh, Singh, Rupendra, Kaushik, Tarun Kumar, Tomer, Aditya
Format Conference Proceeding
LanguageEnglish
Published IEEE 09.05.2024
Subjects
access to justice
accessibility
accuracy
Artificial Intelligence (AI)
backlog of cases
Data privacy
efficiency
Ethics
Explainable AI
India
inefficiencies
Law
legal research tools
legal system
Machine Learning (ML)
Machine learning algorithms
Natural language processing
Natural Language Processing (NLP)
Prediction algorithms
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Summary:Algorithms that integrate Artificial and Machine learning have the potential to significantly impact several industries, including the legal sector. The application of AI and ML offers promise for the backlog of cases, inefficiency, and access to justice in India's judicial system. In this post, we'll take a look at how AI and ML may improve India's judicial system, shedding light on how these technologies might streamline processes while also addressing existing issues. Artificial intelligence (AI) legal research tools could greatly simplify case law study and precedent recognition. Natural Language Processing (NLP) algorithms can swiftly sift through reams of legal documents, providing much-needed information to lawyers and judges. The standard for arguments and decisions is raised, and the legal process is accelerated as a result. Technology that analyzes contracts and screens documents with the use of artificial intelligence may make legal transactions go more smoothly and cheaper. Machine learning algorithms have the potential to save companies time and money by identifying risky wording, outliers, and bad contracts in a matter of minutes.
DOI:10.1109/IC3SE62002.2024.10593058