The capabilities of a new class of tools, colloquially known as generative artificial
intelligence (AI), is a topic of much debate. One prominent application thus far is the …

Text-to-image generative models often reflect the biases of the training data, leading to
unequal representations of underrepresented groups. This study investigates inclusive text …

Face recognition systems have significantly advanced in recent years, driven by the
availability of large-scale datasets. However, several issues have recently came up …

Deployed multimodal models can fail in ways that evaluators did not anticipate. In order to
find these failures before deployment, we introduce MultiMon, a system that automatically …

Abstract Diffusion Models (DMs) have emerged as powerful generative models with
unprecedented image generation capability. These models are widely used for data …

Diffusion models are becoming increasingly popular in synthetic data generation and image
editing applications. However, these models can amplify existing biases and propagate …

This is the interim publication of the first International Scientific Report on the Safety of
Advanced AI. The report synthesises the scientific understanding of general-purpose AI--AI …

State-of-the-art face recognition systems require huge amounts of labeled training data.
Given the priority of privacy in face recognition applications, the data is limited to celebrity …

Recently, there has been increased interest in fair generative models. In this work, we
conduct, for the first time, an in-depth study on fairness measurement, acritical component in …

This article utilizes speculative and visual storytelling alongside interdisciplinary research on
artificial intelligence (AI) and algorithmic oppression to engage in a thought experiment on …