Sarah Lebovitz

University of Virginia - McIntire School of Commerce

P.O. Box 400173

Charlottesville, VA 22904-4173

United States

  • University of Virginia - McIntire School of Commerce

SCHOLARLY PAPERS

4

DOWNLOADS

910

SSRN CITATIONS

9

CROSSREF CITATIONS

0

Scholarly Papers (4)

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1.

Minimal and Adaptive Coordination: How Hackathons’ Projects Accelerate Innovation without Killing it

Number of pages: 67 Posted: 06 Dec 2018 Last Revised: 06 May 2020
Hila Lifshitz-Assaf, Sarah Lebovitz and Lior Zalmanson
Harvard University Lab for Innovation Sciences, University of Virginia - McIntire School of Commerce and Coller School of Management -Tel Aviv University
Downloads 452 (103,430)
Citation 4

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innovation, hackathons, temporality, new product development, coordination

2.

To engage or not to engage with AI for critical judgments: How professionals deal with opacity when using AI for medical diagnosis

Accepted for publication at Organization Science Special Issue on Theorizing Emerging Technologies
Number of pages: 24 Posted: 13 Nov 2019 Last Revised: 13 Jan 2022
Sarah Lebovitz, Hila Lifshitz-Assaf and Natalia Levina
University of Virginia - McIntire School of Commerce, Harvard University Lab for Innovation Sciences and New York University
Downloads 420 (113,131)

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artificial intelligence, opacity, technology adoption and use, professional judgment, uncertainty, innovation, medical diagnosis

3.

How Maker Tools Can Accelerate Ideation

MIT Sloan Research Paper Forthcoming
Number of pages: 7 Posted: 05 Jan 2022
Hila Lifshitz-Assaf and Sarah Lebovitz
Harvard University Lab for Innovation Sciences and University of Virginia - McIntire School of Commerce
Downloads 38 (682,526)

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4.

Is AI Ground Truth Really ‘True’? The Dangers of Training and Evaluating AI Tools Based on Experts’ Know-What

Citation: Lebovitz, S., Levina, N., Lifshitz-Assaf, H. (2021). "Is AI ground truth really true? The dangers of training and evaluation AI tools based on experts' know-what." Management Information Systems Quarterly, 45(3b), pp: 1501-1525 available online: https://doi.10.25300/MISQ/2021/16564
Posted: 05 May 2021 Last Revised: 21 Mar 2023
Sarah Lebovitz, Natalia Levina and Hila Lifshitz-Assaf
University of Virginia - McIntire School of Commerce, New York University and Harvard University Lab for Innovation Sciences

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artificial intelligence, evaluation, uncertainty, new technology, professional knowledge work, innovation, know-how, medical diagnosis, ground truth