Posted in 2024
Funding from the Survival and Flourishing Fund
- 30 October 2024
We received funding from the SFF Fairness Track to fund work developing a benchmark for fair data-driven decision making with LLMs. We will develop a benchmark for both data analytics style decision-making and training fair models on data. Then we will assess state of the art AI systems engaging in these tasks across various levels of AI agency.
Dr. Brown is speaking in the Digital Defense Fund fall seminar series
- 08 October 2024
She is co-leading a session on AI basics titled, “Unmasking AI: the Mysteries and Magic of Artificial Intelligence”.
Dr. Brown is presenting at NSBE PDC
- 23 August 2024
NSBE’s Professional Development conference is a venue for working professionals to skill up. She is presenting the building a portfolio website workshop by invitation
Dr Brown will participate in the AI lab Fireside chat series
- 29 March 2024
title How to anticipate risks in AI-enhanced research
abstract ML-powered AI is increasingly appearing in all areas of research. However, ML is still in many ways a research output, more of a prototype than a polished, reliable, product. Even commercially released systems, because they are software, can be released without the same rigorous testing that commercially available research equipment has been traditionally be subject to. In this talk, I will draw connections between the ML research process and potential risks in applied ML and use of commercial AI in research.
Dr. Brown will present a workshop at NSBE 50
- 22 March 2024
The workshop will be a hands on workshop to build a profile website using github pages.
Dr. Brown gave a keynote at Middlebury College Women in Data Science conference
- 04 March 2024
title Data Science Skills in Unexpected Places
abstract Data science is a highly interdisciplinary pursuit, combining computer science and statistics with domain expertise to make sense of data. This means as data scientists we must work closely with domain experts or develop enough domain expertise of our own for each project. In this talk, I will share the story behind a few data science projects I have done: how high school social studies helped me develop a learning PTSD diagnosis, undergraduate advanced writing helps me measure understanding of fairness in AI, and how student leadership experiences help me design tools for data scientists to build better models.
Welcome to new undergraduates Lani, Noah, Trevor, and Rohan
- 23 January 2024
Lani will be working on understanding how problem formulation is/not described in current ML research.
Trevor and Noah will be joining Brendan to work on internal tooling for the lab.