Syllabus
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Syllabus

Intelligence: Artificial and Otherwise (ATCM

Instructor: David Rheams

Office: Let’s find a coffee shop or Teams

Office hours: By Appointment

Email: davidc.rheams@utdallas.edu

Class Website Link

Lecture: ATCM 2.918

Location:

Department:

⚠️Course Policies

πŸ“œ Course Description

The course inquires into the nature and character of intelligence understood as a cognitive process that transpires via semiosis, or a process of meaning-making. We will ask questions such as: How do we recognize intelligence? Who and/or what might be considered intelligent? What does this mean exactly, especially in the context of emerging debates regarding new technologies called "Artificial Intelligence"? In order to address these questions, we will engage materials (e.g., popular, theoretical, historical, etc.) across a variety of fields, including but not limited to: neuroscience/cognitive science, cybernetics and early AI, philosophy, literature, and aesthetics. We will analyze cultural objects produced using AI tools; we will conduct experiments with such tools, e.g., ChatGPT , Dall-E 2, etc. Ultimately, we will contemplate the implications of the variations on the "A" in "AI," e.g., "artificial," "augmented," "alternative," etc. The culminating assignment will be critical and creative.

This class is an applied philosophy of science. In other words, we seek clarity on how do we do artificial intelligence, why do we make these specific tools, and how do we plan to use them. Most importantly, the class investigates how these tools guide our decision making and finds ways that we can be both more critical and more cognizant of the tools we make.

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Remember that you’re an active participant in putting this class together. This isn't a class where I present information, and your job is to memorize it for future use. Instead, the goal of the class is to uncover ideas and present them in a new light. Students will be asked to help facilitate lectures and contribute to case studies throughout the semester. In addition, we will be working in groups during almost every class.

Technologies & Platforms

🧰 What You'll Get Out of This Class

  • The ability to think critically about technology
  • The ability to be reflexive and challenge your own ideas
  • A deep understanding of how we are building AI as an infrastructure

πŸ“š Readings

All readings are provided for you - no need to buy textbooks. I've provided links to all readings on the class website.

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Selected Texts

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Race After Technology_ Abolitionist Tools for the New Jim Code-Polity

Polity

2019

Ruha Benjamin

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Reassembling the Social

Oxford University Press

2005

Bruno Lator

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Artificial Unintelligence

MIT Press

2018

Meredith Broussard

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A Prehistory of the Cloud

MIT Press

2015

Tung-Hui Hu

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The Structure of Scientific Revolutions

U of Chicago Press

1962

Thomas Kuhn

The Second Self

MIT Press

1984

Sherry Turkle

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The Creativity Code

Harper Collins

2019

Marcus du Sautoy

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Epistemic Cultures

Harvard University Press

1999

Knorr Cetina, K. (Karin)

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Sorting Things Out

MIT Press

200

Geoffrey C. Bowker & Susan Leigh Star

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The Mangle of Practice

U of Chicago Press

1995

Andrew Pickering

πŸ—“ Schedule

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Course Schedule

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Monthly Calendar

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Monthly Calendar

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June 2024
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πŸ† Grading

Breakdown

πŸ“ŒMid Term (20%)

πŸ“ŒFacilitations (20%)

πŸ“ŒPresentations (5%)

πŸ“ŒWeekly Journal (20%)

πŸ“ŒFinal (35%)

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Assignment Submission: Turn in everything via eLearning. For papers, please submit your work as a Google Docs link (one that I can edit) as it is easier to give feedback in this format.

Scale

A 90%-100% B 80%-89% C 70%-79% D 60%-69% F < 60%

😒 Plagiarism

Presenting someone else’s ideas as your own, either verbatim or recast in your own words – is a serious academic offense with severe consequences. In short, don't do it.