A user types a prompt into a chat interface; this prompt is transformed into a big collection of numbers, which are then multiplied against the billions of numerical values that define the program’s constituent neural networks, creating a cascade of frenetic math directed toward the humble goal of predicting useful words to output next. The result of these efforts might very well be jaw-dropping in its nuance and accuracy, but behind the scenes its generation lacks majesty. The system’s brilliance turns out to be the result less of a ghost in the machine than of the relentless churning of endless multiplications.

In their article, Scientist Spotlight Homework Assignments Shift Students’ Stereotypes of Scientists and Enhance Science Identity in a Diverse Introductory Science Class,” Jeffrey Schinske, Heather Perkins, Amanda Snyder, and Mary Wyer created a “scientist spotlight” weekly homework assignment to introduce counter stereotypical examples of scientists and provide a diverse representation of contributions to science. Each week, students reviewed a resource regarding these scientists’ research and personal history in lieu of other textbook readings. Through their analysis, the scholars were able to study and detect shifts in both scientist stereotypes and the students’ ability to see their possible selves in science.