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  • All HBS Web  (11)
    • Faculty Publications  (3)

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    • All HBS Web  (11)
      • Faculty Publications  (3)

      Algorithmic Aversion Remove Algorithmic Aversion →

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      • January–February 2022
      • Article

      Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion

      By: Ryan Allen and Prithwiraj Choudhury
      How does a knowledge worker’s level of domain experience affect their algorithm-augmented work performance? We propose and test theoretical predictions that domain experience has countervailing effects on algorithm-augmented performance: on one hand, domain experience...  View Details
      Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance
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      Allen, Ryan, and Prithwiraj Choudhury. "Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion." Organization Science 33, no. 1 (January–February 2022): 149–169. ("Best PhD Student Paper" at SMS conference 2020.)
      • 2021
      • Article

      Fair Influence Maximization: A Welfare Optimization Approach

      By: Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice and Milind Tambe
      Several behavioral, social, and public health interventions, such as suicide/HIV prevention or community preparedness against natural disasters, leverage social network information to maximize outreach. Algorithmic influence maximization techniques have been proposed...  View Details
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      Rahmattalabi, Aida, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, and Milind Tambe. "Fair Influence Maximization: A Welfare Optimization Approach." Proceedings of the AAAI Conference on Artificial Intelligence 35th (2021).
      • 2020
      • Working Paper

      Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion

      By: Ryan Allen and Prithwiraj Choudhury
      Past research offers mixed perspectives on whether domain experience helps or hurts algorithm-augmented work performance. To reconcile these perspectives, we theorize that domain experience affects algorithm-augmented performance via two distinct countervailing...  View Details
      Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Decision-making; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance
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      Allen, Ryan, and Prithwiraj Choudhury. "Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion." Harvard Business School Working Paper, No. 21-073, October 2020. (Revised September 2021.)
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