4.1 - CC: Computation
Artificial Intelligence Policy
🧠 Think:
- How do computers work? Can they ”simulate” minds? Or can they be minds? Practically, what goes into making a computer, and how do technological constraints structure the nature of AI itself?
📺 Watch:
- Veritasium, “The World’s Most Important Machine”
- CGP Grey, “How Machines Learn” (Note: this video has been retitled “How AI, like ChatGPT, learns”)
- and “How Machines Really Learn” New Title: How AI, like ChatGPT, really learns
- 3Blue1Brown, “Large Language Models explained briefly”
- recommended, but not required: “Transformers explained visually”
🎧 Listen:
- Complexity Podcast Episode 3: What Kind of Intelligence is an LLM?
🌐 Browse:
- Hicks et al, “ChatGPT is Bullshit” Ethics and Information Technology
- Wolfram, S. “What is ChatGPT doing?”
- A few items on evaluating AI Intelligence:
- Humanity’s Last Exam: website and article: Phan et al, Humanity’s Last Exam
- Ullman, “Large Language Models Fail on Trivial Alterations to Theory-of-Mind Tasks”
- Mitchell, “How do we know how smart AI systems are?”
- The Silicon Engine: A Timeline of Semiconductors in Computers. Computer History Museum.
- “It’s the Most Indispensable Machine in the World - and It Depends on This Woman” Wall Street Journal
📚 Additional Resources:
- Complexity Podcast, Episode 2: The Relationship Between Language and Thought. We (regrettably) won’t get to this episode of the Complexity podcast in our class, but this is a good time to listen to it if you have time.
- Only a few videos from 3Blue1Brown’s series on Neural Networks are assigned above, but the entire sequence is worth watching for a non-technical overview: https://www.3blue1brown.com/topics/neural-networks (YouTube)
- Andrej Karpathy, 2025. “A Deep Dive into LLMs like ChatGPT”. (YouTube)
- Witt, Stephen. The Thinking Machine: Jensen Huang, Nvidia, and the World’s Most Coveted Microchip is worth reading in its entirety, but in particular, chapter 6, “Jellyfish” is an excellent non-technical overview of neural nets
- Similarly, the Crash Course: Artificial Intelligence series provides a high level overview of many current AI principles
- There is also a Crash Course: Computer Science for more about computers themselves
- Finally, if you are already statistically inclined, the final episodes of Crash Course: Statistics also cover elements of machine learning and big data analysis building off of core statistical concepts
- Edwards, 2025. “With the launch of o3-pro, let’s talk about what AI “reasoning” actually does” Ars Technica.
- Rumelhart, “The Architecture of the Mind: A Connectionist Approach” Mind Design III
- Churchland and Sejnowski, “The Computational Brain” Mind Design III
- Cowie and Woodard, “The Mind is Not (Just) a System of Modules Shaped (Just) by Natural Selection” Mind Design III
- Vaswani et al, “Attention Is All You Need” (Google paper)
TipTip
- “📖 Read”, “🎧 Listen”, and/or “📺 Watch” items are required content for the day, and should be read/heard/watched before class on that day.
- “🌐 Browse” items should be briefly looked at but do not need to be read deeply unless you want to
- “📚 Additional Resources” do not need to be looked at; they are there to serve, if useful, as further references for your debates, final projects, and general edification later.