Harvey Lederman: Propositional Attitudes and Reference in Language Models

Harvey Lederman: Propositional Attitudes and Reference in Language Models

Author: Daniel Bashir January 11, 2024 Duration: 2:10:34

In episode 106 of The Gradient Podcast, Daniel Bashir speaks to Professor Harvey Lederman.

Professor Lederman is a professor of philosophy at UT Austin. He has broad interests in contemporary philosophy and in the history of philosophy: his areas of specialty include philosophical logic, the Ming dynasty philosopher Wang Yangming, epistemology, and philosophy of language. He has recently been working on incomplete preferences, on trying in the philosophy of language, and on Wang Yangming’s moral metaphysics.

Have suggestions for future podcast guests (or other feedback)? Let us know here or reach us at editor@thegradient.pub

Subscribe to The Gradient Podcast:  Apple Podcasts  | Spotify | Pocket Casts | RSSFollow The Gradient on Twitter

Outline:

* (00:00) Intro

* (02:15) Harvey’s background

* (05:30) Higher-order metaphysics and propositional attitudes

* (06:25) Motivations

* (12:25) Setup: syntactic types and ontological categories

* (25:11) What makes higher-order languages meaningful and not vague?

* (25:57) Higher-order languages corresponding to the world

* (30:52) Extreme vagueness

* (35:32) Desirable features of languages and important questions in philosophy

* (36:42) Higher-order identity

* (40:32) Intuitions about mental content, language, context-sensitivity

* (50:42) Perspectivism

* (51:32) Co-referring names, identity statements

* (55:42) The paper’s approach, “know” as context-sensitive

* (57:24) Propositional attitude psychology and mentalese generalizations

* (59:57) The “good standing” of theorizing about propositional attitudes

* (1:02:22) Mentalese

* (1:03:32) “Does knowledge imply belief?” — when a question does not have good standing

* (1:06:17) Sense, Reference, and Substitution

* (1:07:07) Fregeans and the principle of Substitution

* (1:12:12) Follow-up work to this paper

* (1:13:39) Do Language Models Produce Reference Like Libraries or Like Librarians?

* (1:15:02) Bibliotechnism

* (1:19:08) Inscriptions and reference, what it takes for something to refer

* (1:22:37) Derivative and basic reference

* (1:24:47) Intuition: n-gram models and reference

* (1:28:22) Meaningfulness in sentences produced by n-gram models

* (1:30:40) Bibliotechnism and LLMs, disanalogies to n-grams

* (1:33:17) On other recent work (vector grounding, do LMs refer?, etc.)

* (1:40:12) Causal connections and reference, how bibliotechnism makes good on the meanings of sentences

* (1:45:46) RLHF, sensitivity to truth and meaningfulness

* (1:48:47) Intelligibility

* (1:50:52) When LLMs produce novel reference

* (1:53:37) Novel reference vs. find-replace

* (1:56:00) Directionality example

* (1:58:22) Human intentions and derivative reference

* (2:00:47) Between bibliotechnism and agency

* (2:05:32) Where do invented names / novel reference come from?

* (2:07:17) Further questions

* (2:10:04) Outro

Links:

* Harvey’s homepage and Twitter

* Papers discussed

* Higher-order metaphysics and propositional attitudes

* Perspectivism

* Sense, Reference, and Substitution

* Are Language Models More Like Libraries or Like Librarians? Bibliotechnism, the Novel Reference Problem, and the Attitudes of LLMs



Get full access to The Gradient at thegradientpub.substack.com/subscribe

Hosted by Daniel Bashir, The Gradient: Perspectives on AI moves beyond surface-level headlines to explore the intricate machinery and human ideas shaping artificial intelligence. Each episode is built on a foundation of deep research, leading to conversations that are both technically substantive and broadly accessible. You'll hear from researchers, engineers, and philosophers who are actively building and critiquing our technological future, discussing not just how AI systems work, but the larger implications of their integration into society. This isn't about speculative hype; it's a grounded examination of real progress, persistent challenges, and ethical considerations from those on the front lines. The discussions peel back layers on topics like model architecture, policy, and the fundamental science behind the algorithms becoming part of our daily lives. For anyone curious about the substance behind the buzz-whether you have a technical background or are simply keen to understand a defining technology of our age-this podcast offers a crucial and thoughtful resource. Tune in for a consistently detailed and nuanced take that treats artificial intelligence with the complexity it deserves.
Author: Language: English Episodes: 100

The Gradient: Perspectives on AI
Podcast Episodes
Andrew Lee: How AI will Shape the Future of Email [not-audio_url] [/not-audio_url]

Duration: 1:03:40
In episode 118 of The Gradient Podcast, Daniel Bashir speaks to Andrew Lee.Andrew is co-founder and CEO of Shortwave, a company dedicated to building a better product experience for email, particularly by leveraging AI.…
Joss Fong: Videomaking, AI, and Science Communication [not-audio_url] [/not-audio_url]

Duration: 1:23:59
Episode 117“You get more of what you engage with. Everyone who complains about coverage should understand that every click, every quote tweet, every argument is registered by these publications as engagement. If what you…
Kate Park: Data Engines for Vision and Language [not-audio_url] [/not-audio_url]

Duration: 41:34
In episode 116 of The Gradient Podcast, Daniel Bashir speaks to Kate Park. Kate is the Director of Product at Scale AI. Prior to joining Scale, Kate worked on Tesla Autopilot as the AI team’s first and lead product manag…
Ben Wellington: ML for Finance and Storytelling through Data [not-audio_url] [/not-audio_url]

Duration: 1:07:40
In episode 115 of The Gradient Podcast, Daniel Bashir speaks to Ben Wellington.Ben is the Deputy Head of Feature Forecasting at Two Sigma, a financial sciences company. Ben has been at Two Sigma for more than 15 years, a…
Venkatesh Rao: Protocols, Intelligence, and Scaling [not-audio_url] [/not-audio_url]

Duration: 2:18:35
“There is this move from generality in a relative sense of ‘we are not as specialized as insects’ to generality in the sense of omnipotent, omniscient, godlike capabilities. And I think there's something very dangerous t…
Sasha Rush: Building Better NLP Systems [not-audio_url] [/not-audio_url]

Duration: 54:03
In episode 113 of The Gradient Podcast, Daniel Bashir speaks to Professor Sasha Rush.Professor Rush is an Associate Professor at Cornell University and a Researcher at HuggingFace. His research aims to develop natural la…
Nicholas Thompson: AI and Journalism [not-audio_url] [/not-audio_url]

Duration: 59:43
In episode 111 of The Gradient Podcast, Daniel Bashir speaks to Nicholas Thompson.Nicholas is the CEO of The Atlantic. Previously, he served as editor-in-chief of Wired and editor of Newyorker.com. Nick also cofounded At…
Russ Maschmeyer: Spatial Commerce and AI in Retail [not-audio_url] [/not-audio_url]

Duration: 55:41
In episode 109 of The Gradient Podcast, Daniel Bashir speaks to Russ Maschmeyer.Russ is the Product Lead for AI and Spatial Commerce at Shopify. At Shopify, he leads a team that looks at how AI can better empower entrepr…