Talks
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Empirical Progress on Debate: Where We Are, What's Next, and What's Missing
A brief talk laying out the state of affairs with AI debate for scalable oversight, plus early thoughts on intent alignment and what remains to be done beyond debate.
video slides slides (long)
A brief talk laying out the state of affairs with AI debate for scalable oversight, plus early thoughts on intent alignment and what remains to be done beyond debate.
video slides slides (long)
Delivered Oct 25, 2024
at the
Alignment Workshop.
Delivered Nov 11, 2024
in longer form (unrecorded) at
UT Austin.
AI Alignment via Language Understanding: Defining, Measuring, and Making Progress
Thoughts on the relationship between language understanding, AI Alignment, and scalable oversight, where I introduce "Human–Machine Coordination Games" as a paradigm for evaluating alignment, and discuss some of our debate experiments in this context.
video slides
Thoughts on the relationship between language understanding, AI Alignment, and scalable oversight, where I introduce "Human–Machine Coordination Games" as a paradigm for evaluating alignment, and discuss some of our debate experiments in this context.
video slides
Delivered Mar 12, 2024
at the
AI Objectives Institute.
The Case for Scalable, Data-Driven Theory: A Paradigm for Scientific Progress in NLP
This is the best entry point to my thesis work, laying out my proposal for how to use machine learning to do better science, specifically in the case of syntax and semantics.
video slides paper
This is the best entry point to my thesis work, laying out my proposal for how to use machine learning to do better science, specifically in the case of syntax and semantics.
video slides paper
Delivered Dec 07, 2023
as the best paper talk at
The Big Picture Workshop.
An Introduction to NLP, for Scientists
A summary of the contemporary state of NLP and a (novel at the time, as far as I'm aware) proposal for how to use language models for scientific data analysis. Includes spicy takes on the relationship between deep learning and psychiatric drugs and more.
video slides colab
A summary of the contemporary state of NLP and a (novel at the time, as far as I'm aware) proposal for how to use language models for scientific data analysis. Includes spicy takes on the relationship between deep learning and psychiatric drugs and more.
video slides colab
Delivered Apr 05, 2023
as a guest lecture for Madalina Vlasceanu's graduate regression class at NYU.
From Models of Language to Models of Truth
An early discussion of my thoughts on language understanding with machines and the relationship between AI alignment and philosophical progress.
slides
An early discussion of my thoughts on language understanding with machines and the relationship between AI alignment and philosophical progress.
slides
Delivered Jan 28, 2023
at the
Philosophy, AI, and Society Workshop.
Philosophical Foundations of AI Ethics
An introduction to foundational issues in AI ethics from a philosophical perspective. I try to connect contemporary views and disagreements to their philosophical roots in consequentialism, deontology, social contract theory, and critical theory.
video slides
An introduction to foundational issues in AI ethics from a philosophical perspective. I try to connect contemporary views and disagreements to their philosophical roots in consequentialism, deontology, social contract theory, and critical theory.
video slides
Delivered Jan 25, 2022
for Yulia Tsvetkov's UW class on
Computational Ethics in NLP.
Representing Meaning with Question-Answer Pairs
A 10-minute, accessible colloquium talk summarizing some of my early PhD work on crowdsourcing representations of language structure and meaning. My experience with the projects described in this talk led me to invest further in QA-SRL.
video slides
A 10-minute, accessible colloquium talk summarizing some of my early PhD work on crowdsourcing representations of language structure and meaning. My experience with the projects described in this talk led me to invest further in QA-SRL.
video slides
Delivered Nov 07, 2019
at the
UW Allen School Colloquium.