ML4STS lab#

We study how to do Machine Learning for Socio-technical Systems. This means we apply data science using ML models to understand the world with other scientists, study and evaluate ML systems directly, and build tools to help data scientists to employ best practices. Most of our work right now focuses on fairness of automated decision making systems and some includes collaboration with other scientists.

News#

See the news page for a more complete list.

  • 2024-08-23 : Dr. Brown is presenting at NSBE PDC

    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

  • 2024-03-29 : Dr Brown will participate in the AI lab Fireside chat series

    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.

  • 2024-03-22 : Dr. Brown will present a workshop at NSBE 50

    The workshop will be a hands on workshop to build a profile website using github pages.

  • 2024-03-04 : Dr. Brown gave a keynote at Middlebury College Women in Data Science conference

    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.

  • 2024-01-23 : Welcome to new undergraduates Lani, Noah, Trevor, and Rohan

    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.