AIREVOLUTION

The Core Principle: Validate, Validate, Validate

Generative AI can inject bias and error at every stage of the model lifecycle (Mehrabi et al. 2021, Suresh & Guttag 2019). Consequently, for any researcher who chooses to use these tools, the primary task is not simply to generate outputs, but to continuously and rigorously validate them. This challenge

by Miklós Sebők - Rebeka Kiss • May 2, 2025

GenAI textbook Part 13 Chapter 1

Where Does Bias Come From? Exploring Dataset Imbalance, Annotation Bias, and Pre-existing Modelling Choices

Bias in artificial intelligence systems has become a critical concern as these technologies increasingly influence decision-making across domains such as healthcare, criminal justice, and employment. Bias manifests as systematic errors that lead to unfair or discriminatory outcomes, often disproportionately affecting marginalised groups. Understanding the origins of bias is essential for

by Miklós Sebők - Rebeka Kiss • Apr 30, 2025

Identifying and Managing Bias, Validation

The Core Principle: Validate, Validate, Validate

Where Does Bias Come From? Exploring Dataset Imbalance, Annotation Bias, and Pre-existing Modelling Choices