Publications
Publications
- March 2024
'Storrowed': A Generative AI Exercise
By: Mitchell Weiss
Abstract
"Storrowed" is an exercise to help participants raise their capacity and curiosity for generative AI. It focuses on generative AI for problem understanding and ideation, but can be adapted for use more broadly. Participants use generative AI tools to understand a problem and then to arrive at ideas for solving it.
The exercise begins with the following introduction: "A problem vexed Boston, Massachusetts, and its drivers. Trucks got stuck under the bridges on the city’s Storrow Drive so often that this predicament even had a name, 'Storrowing' or getting 'Storrowed'. Efforts to date, including signage, social media campaigns, and fines, among other measures, had not put an end to Storrowing. One driver—dismayed and delayed on the way to work behind one such run-in—wondered, 'What would AI have to say about why this keeps happening?'"
The exercise is accompanied by a game and can be run in teams; the best prompts keep the teams' trucks from "Storrowing."
The exercise begins with the following introduction: "A problem vexed Boston, Massachusetts, and its drivers. Trucks got stuck under the bridges on the city’s Storrow Drive so often that this predicament even had a name, 'Storrowing' or getting 'Storrowed'. Efforts to date, including signage, social media campaigns, and fines, among other measures, had not put an end to Storrowing. One driver—dismayed and delayed on the way to work behind one such run-in—wondered, 'What would AI have to say about why this keeps happening?'"
The exercise is accompanied by a game and can be run in teams; the best prompts keep the teams' trucks from "Storrowing."
Keywords
Citation
Weiss, Mitchell. "'Storrowed': A Generative AI Exercise." Harvard Business School Exercise 824-188, March 2024.