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  • March 2024
  • Exercise

'Storrowed': A Generative AI Exercise

By: Mitchell Weiss
  • Format:Print
  • | Language:English
  • | Pages:3
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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."

Keywords

AI and Machine Learning; Problems and Challenges

Citation

Weiss, Mitchell. "'Storrowed': A Generative AI Exercise." Harvard Business School Exercise 824-188, March 2024.
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About The Author

Mitchell B. Weiss

Entrepreneurial Management
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Related Work

    • March 2024
    • Faculty Research

    'Storrowed'

    By: Mitchell Weiss
    • March 2024
    • Faculty Research

    'Storrowed': A Generative AI Exercise

    By: Mitchell Weiss
Related Work
  • 'Storrowed' By: Mitchell Weiss
  • 'Storrowed': A Generative AI Exercise By: Mitchell Weiss
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