As machine learning-enabled Text-to-Image (TTI) systems are becoming increasingly
prevalent and seeing growing adoption as commercial services, characterizing the social …

Generative AI systems across modalities, ranging from text, image, audio, and video, have
broad social impacts, but there exists no official standard for means of evaluating those …

As machine learning-enabled Text-to-Image (TTI) systems are becoming increasingly
prevalent and seeing growing adoption as commercial services, characterizing the social …

Prompt engineering is a technique that involves augmenting a large pre-trained model with
task-specific hints, known as prompts, to adapt the model to new tasks. Prompts can be …

Bias amplification is a phenomenon in which models increase imbalances present in the
training data. In this paper, we study bias amplification in the text-to-image domain using …

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 …

Recent progress in generative models has resulted in models that produce both realistic as
well as relevant images for most textual inputs. These models are being used to generate …

How can generative artificial intelligence (GAI) be used for sociological research? The
author explores applications to the study of text and images across multiple domains …

Rigorous and reproducible evaluation is critical for assessing the state of the art and for
guiding scientific advances in Artificial Intelligence. Evaluation is challenging in practice due …

Generative AI systems produce a range of ethical and social risks. Evaluation of these risks
is a critical step on the path to ensuring the safety of these systems. However, evaluation …