Machine Predictions and Synthetic Text: A Roundtable

Since it was published in March 2021, "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?" has sparked impassioned conversations on the unintended consequences and potential harms of prominent natural language processing (NLP) projects. While this groundbreaking paper has been influential in computer and data science—prompting reflection on the dangers of relying on poorly conceptualized and curated data—it is only beginning to be discussed by humanities scholars who use NLP methods in their research.

For this roundtable, two co-authors of "Stochastic Parrots" will speak with three leading digital humanities scholars about the implications of the article for humanities research employing NLP methods. Together, they will discuss how the authors’ attention to process (data gathering, documentation, standards) and ethics in AI can be turned to humanists creating data and models for the study of literature, history, and culture.

Panelists

• Angelina McMillan-Major (University of Washington, Computational Linguistics)
• Gimena del Rio Riande (University of Buenos Aires, Romance Philology)
• Lauren Klein (Emory University, English and Quantitative Theory & Methods)
• Margaret Mitchell (CEO & Research Scientist, Ethical AI LLC)
• Ted Underwood (University of Illinois, Information Science)

Moderator

• Toma Tasovac (DARIAH-EU)

Register for the Zoom webinar.

This event is part of the NEH-funded New Languages for NLP project and is co-sponsored by the Center for Statistics and Machine Learning at Princeton and DARIAH-EU.