Spring 2026 Computer Science 4580. 3/4/2026

Video of the Day

Lying and 6 Other Things Babies Learn Early

Logical Problem of the Day

Truth is more complicated that the logicians would have you believe. Quotes about Truth

There is a new discussion topic: when should a computer lie? In the GARP ethics paper, Kant proposes the categorical imperative which includes the universal law: It is wrong to lie. Well, pace Kant.

Are These 10 Lies Justified? from The New York Times, December 14, 2015. See comments as well.

Using polleverywhere, list which of the ten lies from the NYT article you believe are justified. https://pollev.com/slade

Canvas Quiz of the Day (need daily password)

Most days, there will be a simple canvas quiz related to the lecture. You need a password to activate the quiz, which I will provide in class. These quizzes will count toward your class participation grade. The quiz is available only during class.

Click for today's quiz.

Announcements

Let us know if you have an upcoming event you would like to share with the class.

Yale Information Society Project Free lunch. This week.

I, Claudius, New Yorker, February 16, 2026.

Clawed On Anthropic and the Department of War. Dean Ball, March 2, 2026. Dean is speaking tomorrow at the Law School.

Also, I forwarded an email from Bloomberg re Killer AI. Check it out.

Lecture

I have office hours Mondays and Wednesdays from 2:30-3:30pm pm, on zoom, id 459 434 2854.

Assignments

You can begin work on the project.

I posted a note on Ed Discussions about the weighting of homeworks:

The homeworks, class quizzes and discussions comprise 40% of the grade. Each homework is weighted 10%, as is the combined quizzes and discussion points. You need to complete 50% of the quizzes to get full credit.
The paper is 20%
The project is 40%.

Homework 1 notes:

The program with the highest winning average: Freeman Irabaruta. (47.42610000%)
A good example of using AI: Joanne Zhao.

The Realm of Decisions

We shall explore Langer's mindlessness / mindfulness dichotomy for decision making. For the next class and the coming weeks: Give an example of an explanation you thought interesting because it was especially good or bad. It can be personal or from the news. Use the Discussions section of canvas (not Ed Discussion). You earn a quiz point by posting to Discussions. Try to analyze it along the mindless / mindful spectrum.

The Science of Abstraction and the Abstraction of Science

This is more big picture stuff.

Mathematical World. Euclid started with a handful of axioms and proved a boatload of geometry theorems. Presumably you did as well in high school. Algebra, trigonometry, calculus, and their cousins followed the same path. Starting with a few assumptions and rules of inference (or proof), mathematicians have built solid models of the abstract mathematical world.
Physical World. Physicists (using math) have developed compelling explanations along the spectrum from sub-atomic particles to vast galaxies. There are no real gaps from one level of abstraction to another. The same can be said of chemists, who use the elements of the periodic table as the building blocks of all matter in the universe.
Living World. Biologists have a similar spectrum of abstraction, from DNA molecules to cells to tissue to living organisms to societies and ecosystems. Along the way, they use the theory of evolution to explain how we arrived at the current state. They also explain how an organism develops from a single cell to an adult creature, largely along a similar path as evolution itself. (Ontogeny recapitulates phylogeny.)
Intentional World. That leaves with the intentional world - activies that involve goals, desires, emotions, and relationships. This is actually what most people care about. It covers decision making, persuasion, negotiation, ethics, economics, political science, history, and even art, literature, and religion. The GBDM framework is an attempt to create the periodic table for human intentional behavior. Using the molecular structure of goals and relationships, we hope to build explanations of human behavior that may be modeled and replicated in a computer. We are addressing the scientific question of how people think and the technological question of how to get computers to think like people.

Computer science has been called the science of abstraction. See Music and Computation, Slade, 2025.

The Yale AI Project: Cognitive Modelling

See The Yale Artificial Intelligence Project: A Brief History Stephen Slade, AI Magazine, 1987.

See Conceptual Dependency and Its Descendants Steven Lytinen, 1992.

Conceptual Dependency (CD) (slides)
MARGIE: parse English into CD, infer other concepts, generate natural languge (English and German, later Chinese)
- Task Orientation
- Psychological process model
- Canonical representation of knowledge
- Translation, synonomy, paraphrase
- Inference
- Ambiguity
Scripts, plans, goals and understanding (the book Searle read)
- Scripts: SAM, FRUMP
- Plans: PAM, TALESPIN
  One day Joe Bear was hungry. He asked his friend Irving Bird where some honey was. Irving told him there was a beehive in the oak tree. Joe threatened to hit Irving if he didn’t tell him where some honey was.
  One day Joe Bear was hungry. He asked his friend Irving Bird where some honey was. Irving told him there was a beehive in the oak tree. Joe walked to the oak tree. He ate the beehive.
Learning, memory, and explantion
- Memory Organization Packets (MOPS)
- Bower, Black, and Turner
- CYRUS
- IPP
- Case-based systems (later topic)
The Yale AI Songbook

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