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Judiciary

Using ANAI, citizen data scientists and other developers with limited macahine learning expertise can easily ingest data, generate insights and build/train ML models.

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AI in Legal
potential use cases

AI in Legal

Robot Judges

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.

Preliminary Case Analysis

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.

Speech Translation

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.

Document Management

Get help with document management and also assist with the anonymization of court documents and digitization of analog files using AI-based methods.

limits

challenges found

01
Bias
If not careful there is a high chance that the AI systems can learn all the biases within the data set and can lead to predictions that are neither correct and leads to further problems for innocent parties. 
02
Lack of Transparency
A Lack of transparency within an AI-based system due to companies preserving their trade secrets would undermine the rule of law as a safeguard to discern, understand and contest decisions. 
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03
Explainability of decisions

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. 

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04
Difficulty in setting up

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. 

our platform

With ANAI, Build The Best AI Solutions

  • ANAI allows for generating explanations for the predictions of the model helping the concerned parties understand its decision and not leave any doubts about the functioning of the system.
  • ANAI takes care of the responsibility through its Responsible AI-based solutions so that any biases or prejudices can be taken care of and the system is fair and robust.
  • ANAI provides a no code approach for implementing an end-to-end ML pipeline so that any institutions without the expertise can easily train and deploy ML models within their traditional systems.
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judiciary and artificial intelligence | aI in legal | artificial intelligence and law | artificial intelligence law

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