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Using ANAI, citizen data scientists and other developers with limited macahine learning expertise can easily ingest data, generate insights and build/train ML models.
Deploy AI-powered ‘robot judges’ within the judiciary to adjudicate small claims and to resolve contract disputes between two parties to solve the cases in a quick manner and save time for everyone.
Make initial preliminary analyses on huge documents and case papers by using document analysis and NLP-based models to take the workload of people and to increase accuracy and speed.
Neural Networks can be trained with natural language models and judiciary domain-specific terms for the cases to be solved quickly and to keep the language from being an obstacle during court hearings.
Get help with document management and also assist with the anonymization of court documents and digitization of analog files using AI-based methods.
A lack of explainability on the decisions of the system might be unethical to the concerned parties as there must always be some way to trace out the model’s outcome and what lead to it.
Building and setting up such complicated AI systems will be difficult as the tech talent required for such endeavors is expensive and harder to get and also the overall cost of building and maintaining such systems is high.