Talk: Making Sense of Data with AI: Lowering Barriers, Expanding Who Participates

Generative AI tools like Chat GPT have shifted who gets to participate in data analysis and how. Opportunities exist for large language models (LLMs) to support tasks like code writing for data cleaning and exploration. This has potential to make it easier to engage with data, particularly for those that lack formal technical skills or have limited technical support. In this talk, Jennifer reflects on how LLMs have changed her own workflow by streamlining analysis and lowering barriers to iterating and exploring. She also poses questions around who gets to be considered a data analyst now, and what skills or literacies may matter most.

Jennifer Posada is a UMBC PhD student working with professor Lujie Karen Chen in the Lab for Informatics for Human Flourishing. Her research is focused on  Automation and AI for Personal Informatics Data storytelling.