AI Literacy for Court Administrators (Cert)

Chatbots for justice: Building AI-powered legal solutions st...
Course info

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Course info

AI Literacy for Court Administrators (Cert)

Content

Registration
Access Event Registration System sample
Verify Payment Status
Content
> Intro to AI
AI is not a lawyer sample
Level 1 (pp.9-39) of AI Readiness Guide (PDF) sample
NCSC AI guidelines for courts (PDF) sample
AI foundations in the courts sample
Fundamentals of AI in the Court System sample
Getting the Best of GenAI - How to Use Prompt Engineering sample
How to use prompt engineering sample
AI Due Diligence Survey (PDF) sample
> AI Vendors
Vendor Engagement & Procurement (pp.54-60) of AI Readiness Guide (PDF) sample
> AI Literacy
Establishing GenAI literacy in courts: What judges and court administrators... sample
> Ethics
How to navigate ethics for common AI use cases in courts sample
Ethics of GenAI - A Guide for Judges and Legal Professionals sample
Principles and Practices for Using AI Responsibly - Resource 1 (Video) sample
Principles and Practices for Using AI Responsibly - Resource 2 (PDF) sample
> AI Use Case
Using GenAI to streamline HR tasks in courts sample
AI in Action - Current Applications in State Courts sample
Upskilling court staff & driving operational efficiency through AI chatbots sample
A Technical Deep Dive into AI-powered Chatbots sample
Chatbots for justice: Building AI-powered legal solutions step by step sample
AI-Assisted Translation in Courts: Exploring Opportunities & Navigating Risks sample
> AI Evidence
Deepfakes - Evidentiary Issues for State Courts sample
Deepfakes on trial: How judges are navigating AI evidence authentication sample
Assessment
Court Administrators Comprehensive Test
Evaluation
Court Administrators Role-Based Learning Evaluation

Completion rules

All units must be completed
Leads to a certificate with a duration: 1 year

Close

This blog explains step by step how courts can successfully experiment with AI and chatbots.

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What is a primary method recommended to mitigate "hallucinations" when using Large Language Models (LLMs) for legal applications?

Increasing the model's training data by providing the entire internet as context.

Removing all human oversight to allow the AI to learn independently.

Grounding responses in providing context through techniques like retrieval-augmented generation.

Focusing only on rare languages to reduce the likelihood of errors.

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