AI for Criminal Law Analysis
AI for Criminal Law Analysis uses machine learning to predict outcomes and analyze legal patterns.
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Online
Mentor Based
Moderate
3 Days ( 1.5 Hours Per Day)
07-Apr-2025
3:00 PM IST
About
AI for Criminal Law Analysis employs advanced algorithms to scrutinize legal documents, predict case outcomes, and identify trends, enhancing accuracy and efficiency in legal evaluations.
Aim
The primary aim of AI for Criminal Law Analysis is to improve legal decision-making by providing precise predictive insights and data-driven analysis, thereby streamlining judicial processes and enhancing case outcome accuracy.
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Workshop Objectives
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Case Prediction and Outcomes Analysis
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Evidence Analysis
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Fraud Detection and Prevention
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Document Automation and Managemen
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Sentencing Guidelines Assistance
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Legal Research Acceleration
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Risk Assessment Tools
Workshop Structure
Day 1: AI Tools in Criminal Case Analysis
- Introduction to AI-based forensic analysis tools and their application in criminal law.
Day 2: Predictive Policing and AI
- Examining the use of AI in predictive policing, including ethical concerns and effectiveness.
Day 3: AI in Sentencing and Rehabilitation
- Discussion on how AI is being used to assist in sentencing decisions and rehabilitation programs.
Participant’s Eligibility
- Criminal lawyers with an interest in AI.
- Forensic analysts seeking AI application insights.
- Law enforcement officers exploring tech integration.
- Legal scholars studying AI’s legal impacts.
- AI developers focused on legal applications.
- Policymakers involved in criminal justice reform.
- Ethics experts interested in AI implications.
- Technology students specializing in AI innovations.
Important Dates
Registration Ends
18/02/2025
Indian Standard Timing 3:00 PM
Workshop Dates
07/04/2025 to 09/04/2025
Indian Standard Timing 3:00 PM
Workshop Outcomes
- Enhanced accuracy in evidence evaluation.
- Improved efficiency in case processing times.
- Increased transparency in policing methods.
- Data-driven insights for judicial sentencing.
- Ethical frameworks developed for AI use.
- Advanced training tools for legal professionals.
- Reduced rates of recidivism through AI-driven programs.
- Strengthened capabilities in fraud detection and prevention
Mentor, Conference Profile

Name :Devinder Singh Anand
Designation :Assistant Professor
Affiliation :University Institute of Legal Studies, Chandigarh University
Mr. Devinder Singh Anand is an Assistant Professor in the UILS Department at the Chandigarh University. He received his LL.M Degree from Panjab University in 2013 and submitted his Ph.D. Thesis in May 2024. He worked as a Lecturer in Various Companies/MNCs Since 2013. He has 11 Years of Experience in the field of Law. His Area of Expertise includes Criminal Law and Constitutional Law. He published more than 7 Research papers in renowned peer-reviewed journals and various papers presented at the National and International Conferences.
Fee Structure
Student
INR. 1699 | USD. 60
Ph.D. / Researcher
INR. 1999 | USD. 65
Academician
INR. 2199 | USD. 75
Industry Professional
INR. 2699 | USD. 95
Certificate
- Access to Live Lectures
- Access to Recorded Sessions
- e-Certificate
- Query Solving Post Workshop
Future Career Prospects
- AI Policy Advisor – Shaping regulations for AI in legal systems.
- Legal Tech Entrepreneur – Innovating new AI-driven legal technologies.
- AI Training Specialist – Educating law enforcement on AI tools.
- Judicial Tech Consultant – Integrating AI into judicial processes.
- Legal Data Analyst – Managing and analyzing legal data sets.
- AI Intellectual Property Lawyer – Specializing in AI-related patents and copyrights.
- Legal Document Automation Specialist – Streamlining document handling with AI.
- AI Risk Assessment Manager – Evaluating risks in AI deployments in criminal law.
Job Opportunities
- AI Legal Analyst
- Forensic Data Scientist
- AI Ethics Compliance Officer
- Predictive Policing Coordinator
- AI Solutions Developer for Legal Applications
- Criminal Justice AI Researcher
- AI-Enhanced Sentencing Advisor
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