DSC 190: History of Data Science (Winter 2026, UCSD)

DSC 190: History of Data Science (is a History of Empire)

Instructor: Prof. Stuart Geiger ([email protected])

Time: MWF 4-4:50pm, W 5-5:50pm. In-class attendance and participation are mandatory every Wednesday. Every Friday will have a recorded/remote-friendly lecture. Some Mondays will require in-person attendance.

Must make EASy request: Due to registrar restrictions, you must make an EASy request to take this class.

Course summary: In this class, we will take a critical humanities approach to the 6,000 year old history of people seeking to know and act in their worlds through the collection and analysis of recorded observations. From the first censuses, maps, and accounting records to the most recent wave of artificial intelligence, the history of data science is inextricable from the history of civilizations and empires. We will also trace the short history of “data science/scientist” in the 21st century as the latest instance of a long line of fields and professions that organized themselves around having a more universal or domain-independent expertise.

In many ways, this class is about data ethics and society, as told through the long arc of the history of technology and science, or “techno-science” for short. To take a historical account of data science is NOT about memorizing names and dates, marveling about how far we have come, romanticizing a simpler time, debating utopian vs dystopian science fiction forecasts, or practicing statistics as it was done in prior eras.

Rather, we will reckon with the role that techno-scientific experts have always played in making the world knowable at scale, and in doing so, often re-make the world so it is more legible for those in power. Every generation faces a new, unprecedented, revolutionary change in the order of things, which is often deeply linked to new technologies and ways of knowing. Techno-scientific experts have always had complicated relationships to society and power. Historical thinking helps us abstractly reason about the social, political, economic, and cultural roles of quantification, data management, standardization, classification, prediction, automation, and surveillance.

If you’ve ever had confusion or disagreement over questions like “So what actually is this ‘data science’ thing? Is it a real field/profession? Is it actually different than computer science, statistics, or AI?”, this class is for you. The confusion and disagreement many of you face is not just because “data science” is relatively new or that another “AI summer” is upon us. Fields and professions are always emerging and changing, especially in relation to new technology and socio-political-economic changes. More importantly, these never-ending debates about what “data science,” “artificial intelligence,” and related terms actually are (as if they were natural species to be taxonomized) is instead one deeply bound up in another question, one we ask far less often: “What are the roles of techno-scientific experts in society?”

To answer these questions together, we will go on an adventure across time and space. This class will sharpen your critical thinking skills, expand your perspective of how data and computing is used, help you navigate the complex roles that techno-scientific experts have always played in relation to power, and lead you on a personal journey in which you will identify and articulate your own orientation to what “data science” and related terms is and ought to be. This class is highly recommended for students who are interested in graduate schools and leadership positions in industry or civil society. The pedagogy of this course is designed more like a small graduate seminar, which will let me write highly specific and relevant letters of recommendation.

While this is a humanities class with zero coding, math, or statistics assignments, it is specifically designed for data science majors who may or may not have much existing experience or familiarity with historical or humanities thinking. Assignments will generally require students to apply concepts that link cases from history to similarly-shaped issues in our current moment. This class will also require students to trace the short-term micro-history of data science as a field and profession. A final project will require archival work tracing the short history how an institution of their choice (like a potential industry employer or graduate school) has oriented to “data science”, “artificial intelligence”, or other terms over the past 20 years.

It is not possible to take this class remotely. In-class attendance and participation will be required for the Wed 4-4:50pm class and Wed 5-5:50pm discussion (we will all walk together from Peterson Hall to Center Hall). Wed class will not be recorded. Assignments will include in-class hand-written writing assignments and exams. Fridays will always be a recorded/remote-friendly attendance-optional lecture, while some Mondays will require in-person attendance. As a 4-unit class, students should expect to do 6-8 hours of work a week outside of class. Students should not take this class if they are not prepared to think and write in-class without generative AI. Students who take this class will expand their cognitive capacity for cutting through hype and thinking critically about the role of technology and technologists in society.