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Ubiquitous Surveillance (A)
Gentile, Mary; Danks, David; Harrell, Maralee Case OB-1403 / Published July 8, 2022 / 4 pages. Collection: Darden School of Business
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Product Overview

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. In this A case, Tasha, leader of a data analytics team at Gotham Children’s Hospital, is confronted with an ethical dilemma when her supervisor, Beatriz, suggests a facial recognition system at the hospital. The proposed project would draw on images in the hospital’s database, as well publicly available images and information about arrest records, to identify visitors and trigger alarms when flagged individuals enter certain areas of the hospital. While her team is interested in the project, Tasha is concerned about privacy, bias in automated systems, public relations, and opportunity costs. This case set is intended to be used with students from a wide range of backgrounds, including especially team leads (who may have an MBA or other graduate-level degree) and data scientists. It would be particularly useful in courses on data ethics, technological innovation, technology management, and data law or policy.



Learning Objectives

(1) Students should be able to develop arguments against potentially unethical technologies, even when it is technically feasible to create such technologies. (2) Students should be able to identify how technology design choices prioritize or implement particular values (realizing that technology design is not a purely technical matter), and thereby make and influence design decisions to advance or realize their values.


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  • Overview

    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. In this A case, Tasha, leader of a data analytics team at Gotham Children’s Hospital, is confronted with an ethical dilemma when her supervisor, Beatriz, suggests a facial recognition system at the hospital. The proposed project would draw on images in the hospital’s database, as well publicly available images and information about arrest records, to identify visitors and trigger alarms when flagged individuals enter certain areas of the hospital. While her team is interested in the project, Tasha is concerned about privacy, bias in automated systems, public relations, and opportunity costs. This case set is intended to be used with students from a wide range of backgrounds, including especially team leads (who may have an MBA or other graduate-level degree) and data scientists. It would be particularly useful in courses on data ethics, technological innovation, technology management, and data law or policy.

  • Learning Objectives

    Learning Objectives

    (1) Students should be able to develop arguments against potentially unethical technologies, even when it is technically feasible to create such technologies. (2) Students should be able to identify how technology design choices prioritize or implement particular values (realizing that technology design is not a purely technical matter), and thereby make and influence design decisions to advance or realize their values.