This spring I am teaching a new course at UT San Antonio built around that observation. It is called MDC 1213, Where Does AI Come From? The Sociocultural Foundations of Mathematics, Data and Computing, and it is open to anyone. No calculus. No programming. No prior course. It has been a dream of mine for many years to be able to teach it.

Course details

Anyone can audit it, students and non-students. UTSA students, register with CRN 50089 in ASAP. Seats are limited to thirty, so register early. Non-students can attend online: simply register as an auditor; auditors will receive a Zoom link by January 15th, 2027 (no AI note takers allowed).

• Course: MDC 1213, Section 001, CRN 50089
• Semester: Spring 2027
• Schedule: Tuesdays and Thursdays, 10:00 to 11:15 am
• Where: McKinney Humanities Building, Room MH 3.02.48
• How: UTSA students in person. Auditors online.
• Instructor: Juan B. Gutiérrez, Ph.D., Professor of Mathematics
• Questions: juan.gutierrez3@utsa.edu

Three objects, three ages. A papyrus from about 1550 BCE, on which a scribe named Ahmose copied arithmetic problems for the officials who would measure fields and ration grain.

A punched card from the 1890s, the medium on which the United States census was, for the first time, tabulated by machine.

A photograph from 1946 of Jean Jennings Bartik and Frances Bilas Spence programming ENIAC by hand, cable by cable.

Thirty-five centuries separate the papyrus from the photograph. The same thing is happening in all three. Someone is recording, counting, and calculating on behalf of an institution, and the institution is using the result to know something about people and to decide something for them. Artificial intelligence is the newest instrument in that line. It is not the last.

The thesis

Mathematics, record keeping, and computation are usually taught as fixed procedures: here is how you add fractions, here is how you fill in the form, here is how you write the loop. The procedures change every generation. What persists is their social role.

The course argues, and then tests chapter by chapter, that the capacity to quantify has worked for thousands of years as a selection mechanism. The institutions that could count better, record more durably, and calculate faster rose over the ones that could not. Temple scribes, Renaissance bankers with their double-entry ledgers, the clerks who compiled London’s plague mortality bills, the census bureaus that bought Hollerith’s machines, the credit agencies that score us today: each held a technology of counting, and each gained standing from it.

That is not a complaint about mathematics. It is a reason to learn it. My own conclusion after thirty years of work across government, academia, and industry is that people who control records control institutions, and the only durable response a free society has found is to expand access to quantitative skills deliberately and continually. A course that hands students that key belongs in the first year of college, not the last.

Three questions

Every topic in the course is read through the same three questions:

1. Who counted?

2. What did the counting cost, and to whom?

3. What can the counted contest?

These questions were relevant in Uruk five thousand years ago. They are relevant to anyone who has been denied a loan by a score nobody would explain, flagged by a model nobody would show them, or left out of a statistic that then decided their neighborhood’s funding. They will remain relevant wherever institutions keep records about people.

What we will explore

The course moves from deep history to the present. A sample of the topics:

• The mathematics of money: interest, loans, and the credit score as a modern ledger
• How to lie, and detect lies, with statistics, and what happens when data lies by design
• Geometry, proportion, and symmetry in art, with the golden ratio and Fibonacci along the way
• Networks and social ties, and what graph theory says about who is connected to whom
• Language machines: where the systems that write our emails came from, in plain terms
• Work in the age of AI, and the human computers whose jobs the machines took first
• Games and strategic decisions, music and mathematics, AI in healthcare
• The mathematics of democracy: voting rules, apportionment, and gerrymandering by the numbers
• Fairness by design, minds and machines, and the creative machine

The semester ends with a capstone. Each student designs a cultural data analysis of their own, on real records, using tools that require no code. The point is not to produce programmers. The point is to produce citizens who can look at a number an institution has attached to them and ask the three questions with confidence.

Who should take it

Students in any major. The course assumes nothing beyond arithmetic. Everything that looks like a formula is presented as compressed arithmetic, in tables first and in symbols second. If you have ever decided that mathematics was not for you, this is the course that disagrees.

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*Images, all public domain via Wikimedia Commons: [Rhind Mathematical Papyrus](https://commons.wikimedia.org/wiki/File:Egyptian_A%27h-mos%C3%A8_or_Rhind_Papyrus_(1065×1330).png), British Museum EA10057; [Hollerith punched card](https://commons.wikimedia.org/wiki/File:Hollerith_Punched_Card.jpg), Library of Congress; [Betty Jennings Bartik and Frances Bilas Spence operating ENIAC](https://commons.wikimedia.org/wiki/File:Two_women_operating_ENIAC_(full_resolution).jpg), United States Army.*