
Move Fast, but without Bias: Ethical AI ...
Gentile, Mary;Kras...
Move Fast, but without Bias: Ethical AI Development in a Start-up Culture (B)
Gentile, Mary; Krasniansky, Adriana
OB-1412 | Published August 11, 2022 | 2 pages. Case
Collection: Darden School of Business
Product Details
This case set is part of the Giving Voice to Values (GVV) curriculum. To see other material in the GVV curriculum, please visit http://store.darden.virginia.edu/giving-voice-to-values. Taylor is a senior product manager at Catalise, a start-up that develops artificial intelligence (AI) diagnostic technology for mental health disorders. When Taylor is promoted to this position, her first project is to manage the launch of Catalisten, an AI-based software that diagnoses major depressive disorder by analyzing patients’ speech patterns. Company leaders expect Catalisten to be the company’s new blockbuster product and expedite its launch to ensure a competitive advantage. As Taylor onboards onto the Catalisten team, she learns that the product, which is nearly complete, misdiagnoses female patients at significantly higher rates than male patients. When Taylor raises the concern to a team member, she is pushed to “bury” the algorithm’s discrepancy in order to protect the product launch time line. In the A case, Taylor’s challenge is to convince Catalise’s chief product officer to delay Catalisten’s launch to address the AI software’s gender bias. In this B case, students follow Taylor as she approaches her chief product officer about delaying Catalisten’s launch and addressing the product’s bias. This case set is intended for use at the MBA level in courses in business innovation, entrepreneurship, engineering, technology product development, tech ethics, and leadership and ethics. It could be taught to advanced undergraduates who have developed a foundation in GVV, ethical decision-making, or computer science.
This case set is designed to help students learn how to do the following: (1) demystify software and technology development as a people-led process, (2) codify and uphold internal procedures that protect ethical decision-making, (3) anticipate relationships between technology development and downstream social outcomes, (4) understand the impact of using different product and organizational success metrics, and (5) balance the pressures of project time lines with values-minded leadership.
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