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Publications

Publications

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  • All HBS Web  (109)
    • Faculty Publications  (17)

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    • All HBS Web  (109)
      • Faculty Publications  (17)

      Black Box Explanations Remove Black Box Explanations →

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      • 2022
      • Working Paper

      Racial Diversity in Private Capital Fundraising

      By: Johan Cassel, Josh Lerner and Emmanuel Yimfor
      Black- and Hispanic-owned funds control a very modest share of assets in the private capital industry. We find that the sensitivity of follow-on fundraising to fund performance is greater for minority-owned groups, particularly for underperforming groups. We...  View Details
      Keywords: Buyouts; Capital Formation; Minorities; Venture Capital; Minority-owned Businesses; Race; Diversity; Investment Funds; Financial Services Industry
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      Cassel, Johan, Josh Lerner, and Emmanuel Yimfor. "Racial Diversity in Private Capital Fundraising." Harvard Business School Working Paper, No. 23-020, September 2022.
      • 2022
      • Article

      Towards the Unification and Robustness of Post hoc Explanation Methods

      By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
      As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two...  View Details
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      Agarwal, Sushant, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, and Himabindu Lakkaraju. "Towards the Unification and Robustness of Post hoc Explanation Methods." Symposium on Foundations of Responsible Computing (FORC) (2022).
      • Article

      Reliable Post hoc Explanations: Modeling Uncertainty in Explainability

      By: Dylan Slack, Sophie Hilgard, Sameer Singh and Himabindu Lakkaraju
      As black box explanations are increasingly being employed to establish model credibility in high stakes settings, it is important to ensure that these explanations are accurate and reliable. However, prior work demonstrates that explanations generated by...  View Details
      Keywords: Black Box Explanations; Bayesian Modeling; Decision Making; Risk and Uncertainty; Information Technology
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      Slack, Dylan, Sophie Hilgard, Sameer Singh, and Himabindu Lakkaraju. "Reliable Post hoc Explanations: Modeling Uncertainty in Explainability." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
      • October 2021
      • Article

      Judgment Aggregation in Creative Production: Evidence from the Movie Industry

      By: Hong Luo, Jeffrey T. Macher and Michael Wahlen
      We study a novel, low-cost approach to aggregating judgment from a large number of industry experts on ideas that they encounter in their normal course of business. Our context is the movie industry, in which customer appeal is difficult to predict and investment costs...  View Details
      Keywords: Judgment Aggregation; Quality Uncertainty; Creative Industry; Project Evaluation And Selection; Creativity; Film Entertainment; Judgments; Motion Pictures and Video Industry
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      Luo, Hong, Jeffrey T. Macher, and Michael Wahlen. "Judgment Aggregation in Creative Production: Evidence from the Movie Industry." Management Science 67, no. 10 (October 2021): 6358–6377.
      • Article

      Towards the Unification and Robustness of Perturbation and Gradient Based Explanations

      By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
      As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two...  View Details
      Keywords: Machine Learning; Black Box Explanations; Decision Making; Forecasting and Prediction; Information Technology
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      Agarwal, Sushant, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, and Himabindu Lakkaraju. "Towards the Unification and Robustness of Perturbation and Gradient Based Explanations." Proceedings of the International Conference on Machine Learning (ICML) 38th (2021).
      • Article

      Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses

      By: Kaivalya Rawal and Himabindu Lakkaraju
      As predictive models are increasingly being deployed in high-stakes decision-making, there has been a lot of interest in developing algorithms which can provide recourses to affected individuals. While developing such tools is important, it is even more critical to...  View Details
      Keywords: Predictive Models; Decision Making; Framework; Mathematical Methods
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      Rawal, Kaivalya, and Himabindu Lakkaraju. "Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses." Advances in Neural Information Processing Systems (NeurIPS) 33 (2020).
      • Article

      Robust and Stable Black Box Explanations

      By: Himabindu Lakkaraju, Nino Arsov and Osbert Bastani
      As machine learning black boxes are increasingly being deployed in real-world applications, there has been a growing interest in developing post hoc explanations that summarize the behaviors of these black boxes. However, existing algorithms for generating such...  View Details
      Keywords: Machine Learning; Black Box Models; Framework
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      Lakkaraju, Himabindu, Nino Arsov, and Osbert Bastani. "Robust and Stable Black Box Explanations." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020): 5628–5638. (Published in PMLR, Vol. 119.)
      • 2020
      • Article

      'How Do I Fool You?': Manipulating User Trust via Misleading Black Box Explanations

      By: Himabindu Lakkaraju and Osbert Bastani
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      Lakkaraju, Himabindu, and Osbert Bastani. "'How Do I Fool You?': Manipulating User Trust via Misleading Black Box Explanations." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2020): 79–85.
      • 2019
      • Working Paper

      Judgment Aggregation in Creative Production: Evidence from the Movie Industry

      By: Hong Luo, Jeffrey T. Macher and Michael Wahlen
      This paper studies a novel, light-touch approach to aggregate judgment from a large number of industry experts on ideas that they encounter in their normal course of business. Our context is the movie industry, in which customer appeal is difficult to predict and...  View Details
      Keywords: Judgment Aggregation; Creativity; Film Entertainment; Judgments; Motion Pictures and Video Industry
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      Luo, Hong, Jeffrey T. Macher, and Michael Wahlen. "Judgment Aggregation in Creative Production: Evidence from the Movie Industry." Harvard Business School Working Paper, No. 19-082, January 2019. (Revised September 2019.)
      • Article

      Faithful and Customizable Explanations of Black Box Models

      By: Himabindu Lakkaraju, Ece Kamar, Rich Caruana and Jure Leskovec
      As predictive models increasingly assist human experts (e.g., doctors) in day-to-day decision making, it is crucial for experts to be able to explore and understand how such models behave in different feature subspaces in order to know if and when to trust them. To...  View Details
      Keywords: Interpretable Machine Learning; Black Box Models; Decision Making; Framework
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      Lakkaraju, Himabindu, Ece Kamar, Rich Caruana, and Jure Leskovec. "Faithful and Customizable Explanations of Black Box Models." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2019).
      • August 2017 (Revised July 2018)
      • Case

      MannKind Corporation: Take a Deep Breath, This Time Afrezza Will Work

      By: Elie Ofek and Amanda Dai
      In June 2014, MannKind Corporation announced that after years of development and billions of dollars in expenses, the FDA had finally approved its drug, Afrezza. MannKind would thus be the only company with an inhalable insulin on the market. As an alternative to...  View Details
      Keywords: Health Care and Treatment; Product Launch; Product Positioning; Marketing Strategy; Adoption; Pharmaceutical Industry
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      Ofek, Elie, and Amanda Dai. "MannKind Corporation: Take a Deep Breath, This Time Afrezza Will Work." Harvard Business School Case 518-031, August 2017. (Revised July 2018.)
      • 2011
      • Working Paper

      Inside the Black Box of the Corporate Staff: An Exploratory Analysis Through the Lens of E-Mail Networks

      By: Toby E. Stuart
      The corporate staff is central in theories of the multi-business firm, but empirical evidence on its function is limited. In this paper, we examine the high-level role of two units of a corporate staff through analysis of electronic communications. We find sharp...  View Details
      Keywords: Theory; Business Ventures; Internet and the Web; Communication; Employment; Management Teams; Networks
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      Kleinbaum, Adam M., and Toby Stuart. "Inside the Black Box of the Corporate Staff: An Exploratory Analysis Through the Lens of E-Mail Networks." Harvard Business School Working Paper, No. 12-051, December 2011.
      • October 2010 (Revised November 2010)
      • Background Note

      Plavix: Drugs in the Age of Personalized Medicine

      By: Richard G. Hamermesh, Mara G. Aspinall and Rachel Gordon
      PIavix, one of the world's best selling drugs in 2010, appears to have a limited future. Its patent was due to expire soon, and recently new data had been discovered that indicated that a small subset of the population would be at risk for stroke, heart attack, or even...  View Details
      Keywords: Health Care and Treatment; Product Positioning; Business and Government Relations; Genetics; Competitive Strategy; Pharmaceutical Industry
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      Hamermesh, Richard G., Mara G. Aspinall, and Rachel Gordon. "Plavix: Drugs in the Age of Personalized Medicine." Harvard Business School Background Note 811-001, October 2010. (Revised November 2010.)
      • October 2008
      • Article

      Organizational Responses to Environmental Demands: Opening the Black Box

      By: Magali Delmas and Michael W. Toffel
      This paper combines new and old institutionalism to explain differences in organizational strategies. We propose that differences in the influence of corporate departments lead their facilities to prioritize different external pressures and thus adopt different...  View Details
      Keywords: Environmental Sustainability; Management Practices and Processes; Decisions; Adoption
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      Delmas, Magali, and Michael W. Toffel. "Organizational Responses to Environmental Demands: Opening the Black Box." Strategic Management Journal 29, no. 10 (October 2008): 1027–1055.
      • 2001
      • Article

      From Guilford to Creative Synergy: Opening the Black Box of Team Level Creativity

      By: T. R. Kurtzberg and T. M. Amabile
      Previous research, from Guilford's founding tradition to more modern research on individual creativity and general group processes, falls short of adequately describing team-level creativity. Alhough researchers have addressed brainstorming in groups with mixed...  View Details
      Keywords: Creativity; Groups and Teams; Theory; Research; Organizational Culture
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      Kurtzberg, T. R., and T. M. Amabile. "From Guilford to Creative Synergy: Opening the Black Box of Team Level Creativity." Special Issue on Commemorating Guilford's 1950 Presidential Address Creativity Research Journal 13, nos. 3/4 (2001).
      • 14 Aug 2017
      • Conference Presentation

      Interpretable and Explorable Approximations of Black Box Models

      By: Himabindu Lakkaraju, Ece Kamar, Rich Caruana and Jure Leskovec
      Citation
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      Lakkaraju, Himabindu, Ece Kamar, Rich Caruana, and Jure Leskovec. "Interpretable and Explorable Approximations of Black Box Models." Paper presented at the 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), Halifax, NS, Canada, August 14, 2017.
      • Teaching Interest

      Large-Scale Investment (LSI, MBA Elective Curriculum)

      By: Benjamin C. Esty
      Large-Scale Investment (LSI) is a case-based course about project finance that is designed for second-year MBA students. Project finance involves the creation of a legally independent project company financed with nonrecourse debt for the purpose of investing in a...  View Details
      Keywords: Project Finance; Corporate Finance; Corporate Governance; Valuation; Capital Budgeting
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