NicFab Podcast English

NicFab Podcast English@nicfabpodcast_en

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Season 1 episodes (5)

Legal Prompting - Chain-of-thought e few-shot prompting nel legal
S01:E05

Legal Prompting - Chain-of-thought e few-shot prompting nel legal

Two techniques change the way a model approaches a legal problem: chain-of-thought — the explicit request to lay out the logical steps before the conclusion — and few-shot prompting — providing two or three well-chosen examples to steer format and method of the answer. In this episode we look at: how to structure step-by-step reasoning with a concrete example on data transfers outside the EU (Chapter V GDPR, Schrems II); how to pick few-shot examples without introducing bias; how to combine the two techniques for the analysis of complex decisions; the three limits to be aware of: context length, example bias, and plausibility that is not legal correctness; why documenting prompt, examples and verification is already AI governance. Chain-of-thought and few-shot are not tricks: they are the way we translate our legal method into instructions understandable to the model. In the next episode we will apply these techniques to the analysis of contracts and clauses. 🎧 Also on Apple Podcasts, Spotify, Amazon Music, and Podcast Index. 🌐 nicfab.eu

Legal Prompting - RAG and its risks in the legal domain
S01:E04

Legal Prompting - RAG and its risks in the legal domain

In this episode, we talk about RAG — Retrieval-Augmented Generation — in the legal domain. What it is, how it works, and, most importantly, what risks it introduces for the legal professional. RAG allows a model to work with documents provided by the user rather than relying solely on its training data. The idea is powerful, but the process conceals concrete pitfalls: retrieval based on linguistic rather than legal similarity, document fragmentation that breaks argumentative structure, outdated sources retrieved without validity checks, opacity in how fragments are used, and implications for professional secrecy. Four practical safeguards: verify the sources, check the segmentation, choose the infrastructure carefully, and document every use. Subscribe to the newsletter at nicfab.eu

Legal Prompting - Drafting privacy notices with artificial intelligence
S01:E03

Legal Prompting - Drafting privacy notices with artificial intelligence

How to use artificial intelligence to work on privacy notices without losing legal control. Three concrete operations: checking completeness against Article 13 of the GDPR, simplifying the language in compliance with Article 12, and adapting a base notice to different contexts, such as employees or apps. Each operation includes a structured prompt example. With the three Legal Prompting premises: human supervision, regulatory framework, and infrastructure choice. Episode 3 of the Legal Prompting series — NicFab Podcast. Newsletter and insights: nicfab.eu

Legal Prompting - Analyzing Supervisory Authorities' Decisions
S01:E02

Legal Prompting - Analyzing Supervisory Authorities' Decisions

Second episode of the Legal Prompting series. How to use artificial intelligence to analyze a supervisory authority’s decision on data protection: why “analyze this document” is not enough, how to build a structured prompt (role, context, specific instructions, output format), the traps to watch for — normative hallucinations, loss of argumentative nuances, fabricated cross-references — and the compliance implications of using cloud-based models. Read the column in the newsletter → nicfab.eu

Legal Prompting - Introduction
S01:E01

Legal Prompting - Introduction

The first episode of the NicFab Podcast is dedicated to Legal Prompting: how to use artificial intelligence in legal and professional contexts with method, awareness, and a critical eye. This episode introduces the three fundamental premises of the series: language models do not reason like lawyers; the use of AI in professional settings falls within a specific regulatory framework (GDPR, AI Act, professional ethics); and the choice of model and infrastructure is a compliance decision even before it is a technical one.