Events Calendar

NL Seminar-Getting AI to Do Things I Can't

Speaker: Ruiqi Zhong, Cal-Berekely

Talk Title: Getting AI to Do Things I Can't

Series: NL Seminar

Abstract: REMINDER

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Is it possible to tame powerful AI systems even when we struggle to determine the ground truth ourselves? In this talk, I will cover two example NLP tasks 1. automatically searching for goal-relevant patterns in large text collections and explaining them to humans in natural language 2. labeling complex SQL programs using non-programmers with the aid of our AI system and achieving accuracy on par with database experts. In both cases, we build tools that help humans scrutinize the AI's behavior with high effectiveness but low effort, bringing new insights that human experts have not anticipated.

Biography: Ruiqi Zhong is a 4th year Ph.D. student advised by Jacob Steinhardt and Dan Klein, working on NLP and AI Alignment.

Ruiqi Zhong attends th Univ. of California Berkeley, he is working on NLP and AI Alignment. His research aims to enable humans to effectively supervise AI systems on tasks where the ground truth is hard to obtain. He reads about epistemology and labor economy in his spare time.


Host: Jon May and Justin Cho

More Info: https://nlg.isi.edu/nl-seminar/

Webcast: https://www.youtube.com/watch?v=dHkYN33TtLM

Location: Information Science Institute (ISI) - Virtual and ISI-Conf Rm#689

WebCast Link: https://www.youtube.com/watch?v=dHkYN33TtLM

Audiences: Everyone Is Invited

Contact: Pete Zamar

Event Link: https://nlg.isi.edu/nl-seminar/