Participatory approaches to artificial intelligence (AI) and machine learning (ML) are gaining
momentum: the increased attention comes partly with the view that participation opens the …

Abstract Evaluation practices in natural language generation (NLG) have many known flaws,
but improved evaluation approaches are rarely widely adopted. This issue has become …

Abstract We present the Pathways [1] Autoregressive Text-to-Image (Parti) model, which
generates high-fidelity photorealistic images and supports content-rich synthesis involving …

Responsible innovation on large-scale Language Models (LMs) requires foresight into and
in-depth understanding of the risks these models may pose. This paper develops a …

This paper aims to help structure the risk landscape associated with large-scale Language
Models (LMs). In order to foster advances in responsible innovation, an in-depth …

Recent image generation models such as Stable Diffusion have exhibited an impressive
ability to generate fairly realistic images starting from a simple text prompt. Could such …

AI models are increasingly applied in high-stakes domains like health and conservation.
Data quality carries an elevated significance in high-stakes AI due to its heightened …

Large language models have led to remarkable progress on many NLP tasks, and
researchers are turning to ever-larger text corpora to train them. Some of the largest corpora …

Recently, there has been an increased interest in demographically grounded bias in natural
language processing (NLP) applications. Much of the recent work has focused on describing …

As research and industry moves towards large-scale models capable of numerous
downstream tasks, the complexity of understanding multi-modal datasets that give nuance to …