# AI Literacy for Legal AI Systems: A practical approach

arXiv: https://arxiv.org/abs/2505.18006 · HTML: https://mlsanity.com/paper/2505.18006/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 66 references that are in the map.
- First posted on arXiv 23 May 2025.

## Builds on (most cited first, 6 of 6)

- [Large Language Models in Law: A Survey](https://mlsanity.com/paper/2312.03718/) (2023)
- [Why Fairness Cannot Be Automated: Bridging the Gap Between EU Non-Discrimination Law and AI](https://mlsanity.com/paper/2005.05906/) (2020)
- [Generative AI Literacy: Twelve Defining Competencies](https://mlsanity.com/paper/2412.12107/) (2024)
- [Unlocking the Black Box: Analysing the EU Artificial Intelligence Act's Framework for Explainability in AI](https://mlsanity.com/paper/2502.14868/) (2025)
- [A Comparative User Study of Human Predictions in Algorithm-Supported Recidivism Risk Assessment](https://mlsanity.com/paper/2201.11080/) (2022)
- [Non-Asimov Explanations Regulating AI through Transparency](https://mlsanity.com/paper/2111.13041/) (2021)

## Abstract (arXiv)

Legal AI systems are increasingly being adopted by judicial and legal system deployers and providers worldwide to support a range of applications. While they offer potential benefits such as reducing bias, increasing efficiency, and improving accountability, they also pose significant risks, requiring a careful balance between opportunities, and legal and ethical development and deployment. AI literacy, as a legal requirement under the EU AI Act and a critical enabler of ethical AI for deployers and providers, could be a tool to achieve this. The article introduces the term "legal AI systems" and then analyzes the concept of AI literacy and the benefits and risks associated with these systems. This analysis is linked to a broader AI-L concept for organizations that deal with legal AI systems. The outcome of the article, a roadmap questionnaire as a practical tool for developers and providers to assess risks, benefits, and stakeholder concerns, could be useful in meeting societal and regulatory expectations for legal AI.