HON-H 240 (Hutton Honors College) Language, Intelligence, and the Machine

January 2024

Times: Tuesday and Thursday 9:45-11:00 AM

Course Material Spring 2024

Course Description

Science permeates society, but the reverse is also true. The agendas of scientists, ethical norms in science, and the goals of scientific endeavors all have societal underpinnings. This course considers how science affects societal forms and functions and how society affects the scientific enterprise.

Addressing state-of-the-art technologies in Artificial Intelligence, Linguistic and Natural Language Processing capabilities of advanced Large Language Models, and the perspectives of Machines becoming intelligent. This course addresses not just the technologies and applications of AI and possible Artificial General Intelligence but also aspects of human cognition and intelligence from a psycholinguistic perspective, as well as philosophical and sociological issues, risks, and improvements for society and human life.

Textbook and Reading Material

We are not using a textbook. We will use chapters from different books, academic papers, and online publications.

Searle, John. R. (1980) Minds, brains, and programs. Behavioral and Brain Sciences 3 (3): 417-457. (Online version)
Turing, Alan (October 1950), “Computing Machinery and Intelligence,” Mind, LIX (236): 433–460, doi:10.1093/mind/LIX.236.433, ISSN 0026-4423.
Hofstadter, Douglas R. and Daniel C. Dennett (2001) The Mind’s I: Fantasies and Reflections on Self and Soul. Basic Books, reprint, from 1981.
Jurafsky, Dan and James H. Martin (2023) Speech and Language Processing. (3rd ed. draft)
Introduction to Psychology. Copyright © 2015 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.
- Chapter 10. Intelligence and Language
Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report

GPT and LLMs:

Wolfram, Stephen (2023), “What Is ChatGPT Doing … and Why Does It Work?,” Stephen Wolfram Writings. writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work.
Radford, Alec, et al. (2019) Language Models are Unsupervised Multitask Learners.
Brown, Tom B., et al. (2020) Language Models are Few-Shot Learners.
OpenAI et al. (2023) GPT-4 Technical Report.

Online course materials:

Pesetsky, David (2012) Introduction to Linguistics. MIT OpenCourseware.
The Virtual Linguistics Campus.

Discussion and Debates:

A Skeptical Take on the A.I. Revolution. The Ezra Klein Show with Gary Marcus, NYT.
Doug Hofstadter on why today’s AI terrifies him. YouTube video. Full interview.

Legislature:

The EU Artificial Intelligence Act. (Summary)
Copyright and Artificial Intelligence (in the US).
Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government (US Gov.) (Factsheet)