Julia B Barnett



Google Scholar


she / her

PhD Candidate at Northwestern

Hello! I'm Julia Barnett and I'm a PhD student in Technology and Social Behavior, which is a dual PhD program in computer science and communications at Northwestern University. My research interests lie in algorithmic ethics, algorithmic impact, reducing the sociotechnical harms of algorithmic systems, and deep generative audio. Most recently I built a framework for identifying the most similar songs from training data to pieces of generated music in order to enable training data attribution of generative music models with Bryan Pardo and Hugo Flores García.

I'm advised by Nicholas Diakopoulos, and right now we are researching different areas in the ethical AI space with a focus on algorithmic impact. We most recently explored how to utilize large language models (LLMs) such as GPT-4 to simulate the effects of policy through scenario building. Prior to that we focused on the ability to anticipate societal impacts of algorithms through mediums such as crowdsourcing. Currently I am working with Ágnes Horvát investigating the intersectional penalty of gender and ethnic diversity of scientific teams on success in scientific publications and also with Bryan Pardo to build an interface that uncovers the influences of generated pieces of music to provide a path for the end-user to move from ignorant appropriator to informed creator.

I completed a Master's Degree in Data Science at the Barcelona Graduate School of Economics in 2019, and I got my Bachelor's Degree in Business Analytics, International Business, and Marketing from Villanova University in 2018. Before my PhD I finished up a two year stint as a Senior Data Analyst at The Washington Post.

Recent Updates

July 2024: My paper "Simulating Policy Impacts: Developing a Generative Scenario Writing Method to Evaluate the Perceived Effects of Regulation" with Kimon Kieslich and Nick Diakopoulos got accepted at the 7th AAAI/ACM Conference on AI, Ethics, and Society (AIES). [PDF]

July 2024: My fist post of a series, Decoding US Copyright Law and Fair Use for Generative AI Legal Cases, was published in the Generative AI in the Newsroom blog 👩🏻‍⚖️

June 2024: My paper "Exploring Musical Roots: Applying Audio Embeddings to Empower Influence Attribution for a Generative Music Model" with Bryan Pardo and Hugo Flores García got accepted at the 25th International Society for Music Information Retrieval (ISMIR).

April-June 2024: Helped teach a course on introduction to law and digital technologies at Northwestern 👩🏻‍⚖️

March-April 2024: Taught a seminar at Skokie Public Library on the Ethics of Generative AI in the Media 📚

February 2024: Successfully defended my computer science qualifying exam! 🥳

January 2024: Released a pre-print for new work: Exploring Musical Roots: Applying Audio Embeddings to Empower Influence Attribution for a Generative Music Model

January 2024: Presented recent work on exploring musical roots: empowering influence attribution for generative music models at Northwestern's "Human-centered AI and Music: A One-day Symposium on the Design and Implications of Generative Models in Music." 🎵🤖

September 2023: Attended and did a poster presentation at the Chicago Human+AI Lab (CHAI)'s Symposium on Human+AI.

August 2023: Presented my paper on  The Ethical Implications of Generative Audio Models: A Systematic Literature Review at Artificial Intelligence, Ethics, and Society (AIES) 2023 in Montreal, Quebec, Canada.

August 2023: My work on the ethical implications of generative audio models was featured in the Montreal AI Ethics Institute blog.

June 2023: Presented on joint work with Orsolya Vásárhelyi, Ágnes Horvát, and Stasa Milojevic about intersectional inequalities in the success of scientific publication at the International Conference on Science of Science and Innovation at Northwestern University in Evanston.

June 2023: Finished all my coursework! 🤠