My work aims to pave the way towards a better understanding of the societal and environmental impacts of AI models, datasets and systems.

Some of my current projects are:

  • Evaluating the carbon emissions of AI models – my longstanding project is getting a better idea of how much carbon is emitted by AI models and what are the factors that influence it - see my “BLOOM” and “Counting Carbon” articles.
  • Stable Diffusion Bias Explorer – a demo for exploring the biases in text-to-image models like Stable Diffusion and Dall-E 2.
  • The Data Measurements Tool – a tool for exploring and analyzing common datasets used for training and evaluating Machine Learning models.
  • This Climate Does Not Exist – in which we use Generative Adversarial Networks (GANs) to visualize the potential future impacts of climate change.
  • CodeCarbon – I am contributing to creating a calculator to quantify the CO2 emissions produced during the training of AI algorithms.
  • Big Science – BigScience is a one-year long research workshop on very large language models as used and studied in the field of Natural Language Processing and more generally Artifical Intelligence research. I am co-chairing the carbon footprint working group within the project.