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Publications

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      • 2022
      • Working Paper

      Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development

      By: Daniel Yue, Paul Hamilton and Iavor Bojinov
      Predictive model development is understudied despite its importance to modern businesses. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms) as the primary driver of model quality, the value of tools...  View Details
      Keywords: Analytics and Data Science
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      Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022.
      • 2022
      • Article

      Flatten the Curve: Efficiently Training Low-Curvature Neural Networks

      By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret
      Standard deep neural networks often have excess non-linearity, making them susceptible to issues such as low adversarial robustness and gradient instability. Commonmethods to address these downstream issues, such as adversarial training, are expensive and often...  View Details
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      Srinivas, Suraj, Kyle Matoba, Himabindu Lakkaraju, and Francois Fleuret. "Flatten the Curve: Efficiently Training Low-Curvature Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) (2022).
      • 2022
      • Article

      OpenXAI: Towards a Transparent Evaluation of Model Explanations

      By: Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik and Himabindu Lakkaraju
      While several types of post hoc explanation methods have been proposed in recent literature, there is very little work on systematically benchmarking these methods. Here, we introduce OpenXAI, a comprehensive and extensible opensource framework for evaluating and...  View Details
      Keywords: Measurement and Metrics; Analytics and Data Science
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      Agarwal, Chirag, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, and Himabindu Lakkaraju. "OpenXAI: Towards a Transparent Evaluation of Model Explanations." Advances in Neural Information Processing Systems (NeurIPS) (2022).
      • December 2022
      • Article

      Shaping Nascent Industries: Innovation Strategy and Regulatory Uncertainty in Personal Genomics

      By: Cheng Gao and Rory McDonald
      In nascent industries—whose new technologies are often poorly understood by regulators—contending with regulatory uncertainty can be crucial to organizational survival and growth. Prior research on nonmarket strategy has largely focused on established firms in mature...  View Details
      Keywords: Technological Change; Innovation; Qualitative Methods; New Categories; Entrepreneurship; Technological Innovation; Governing Rules, Regulations, and Reforms; Risk and Uncertainty; Strategy
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      Gao, Cheng, and Rory McDonald. "Shaping Nascent Industries: Innovation Strategy and Regulatory Uncertainty in Personal Genomics." Administrative Science Quarterly 67, no. 4 (December 2022): 915–967.
      • 2022
      • Article

      Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations

      By: Tessa Han, Suraj Srinivas and Himabindu Lakkaraju
      A critical problem in the field of post hoc explainability is the lack of a common foundational goal among methods. For example, some methods are motivated by function approximation, some by game theoretic notions, and some by obtaining clean visualizations. This...  View Details
      Keywords: Mathematical Methods; Decision Choices and Conditions; Analytics and Data Science
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      Han, Tessa, Suraj Srinivas, and Himabindu Lakkaraju. "Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations." Advances in Neural Information Processing Systems (NeurIPS) (2022).
      • November 2022
      • Article

      A Language-Based Method for Assessing Symbolic Boundary Maintenance between Social Groups

      By: Anjali M. Bhatt, Amir Goldberg and Sameer B. Srivastava
      When the social boundaries between groups are breached, the tendency for people to erect and maintain symbolic boundaries intensifies. Drawing on extant perspectives on boundary maintenance, we distinguish between two strategies that people pursue in maintaining...  View Details
      Keywords: Culture; Machine Learning; Natural Language Processing; Symbolic Boundaries; Organizations; Boundaries; Social Psychology; Interpersonal Communication; Organizational Culture
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      Bhatt, Anjali M., Amir Goldberg, and Sameer B. Srivastava. "A Language-Based Method for Assessing Symbolic Boundary Maintenance between Social Groups." Sociological Methods & Research 51, no. 4 (November 2022): 1681–1720.
      • November 2022
      • Article

      Measuring Inequality beyond the Gini Coefficient May Clarify Conflicting Findings

      By: Kristin Blesch, Oliver P. Hauser and Jon M. Jachimowicz
      Prior research has found mixed results on how economic inequality is related to various outcomes. These contradicting findings may in part stem from a predominant focus on the Gini coefficient, which only narrowly captures inequality. Here, we conceptualize the...  View Details
      Keywords: Economic Inequalty; Gini Coefficient; Income Inequality; Equality and Inequality; Social Issues; Health; Status and Position
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      Blesch, Kristin, Oliver P. Hauser, and Jon M. Jachimowicz. "Measuring Inequality beyond the Gini Coefficient May Clarify Conflicting Findings." Nature Human Behaviour 6, no. 11 (November 2022): 1525–1536.
      • November–December 2022
      • Article

      The Value of Descriptive Analytics: Evidence from Online Retailers

      By: Ron Berman and Ayelet Israeli
      Does the adoption of descriptive analytics impact online retailer performance, and if so, how? We use the synthetic difference-in-differences method to analyze the staggered adoption of a retail analytics dashboard by more than 1,500 e-commerce websites, and we find an...  View Details
      Keywords: Descriptive Analytics; Big Data; Synthetic Control; E-commerce; Online Retail; Difference-in-differences; Martech; Internet and the Web; Analytics and Data Science; Performance; Marketing; Retail Industry
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      Berman, Ron, and Ayelet Israeli. "The Value of Descriptive Analytics: Evidence from Online Retailers." Marketing Science 41, no. 6 (November–December 2022): 1074–1096.
      • 2022
      • Working Paper

      Communicating Corporate Culture in Labor Markets: Evidence from Job Postings

      By: Joseph Pacelli, Tianshuo Shi and Yuan Zou
      A company’s culture represents one of the most important factors that job seekers consider. In this study, we examine how firms craft their job postings to convey their cultures and whether doing so helps attract employees. We utilize state-of-the art machine learning...  View Details
      Keywords: Corporate Culture Significance; Labor Markets; Disclosure; Organizational Culture; Recruitment; Talent and Talent Management
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      Pacelli, Joseph, Tianshuo Shi, and Yuan Zou. "Communicating Corporate Culture in Labor Markets: Evidence from Job Postings." Working Paper, October 2022.
      • September 2022
      • Article

      Tone at the Bottom: Measuring Corporate Misconduct Risk from the Text of Employee Reviews

      By: Dennis W. Campbell and Ruidi Shang
      This paper examines whether information extracted via text-based statistical methods applied to employee reviews left on the website Glassdoor.com can be used to develop indicators of corporate misconduct risk. We argue that inside information on the incidence of...  View Details
      Keywords: Management Accounting; Management Control; Corporate Culture; Corporate Misconduct; Risk Measurement; Organizational Culture; Crime and Corruption; Risk and Uncertainty; Measurement and Metrics
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      Campbell, Dennis W., and Ruidi Shang. "Tone at the Bottom: Measuring Corporate Misconduct Risk from the Text of Employee Reviews." Management Science 68, no. 9 (September 2022): 7034–7053.
      • August 2022
      • Article

      Contract Duration and the Costs of Market Transactions

      By: Alexander MacKay
      The optimal duration of a supply contract balances the costs of reselecting a supplier against the costs of being matched to an inefficient supplier when the contract lasts too long. I develop a structural model of contract duration that captures this tradeoff and...  View Details
      Keywords: Supply Contracts; Intermediate Goods; Switching Costs; Vertical Relationships; Transaction Costs; Contract Duration; Identification; Supply Chain; Cost; Contracts; Auctions; Mathematical Methods
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      MacKay, Alexander. "Contract Duration and the Costs of Market Transactions." American Economic Journal: Microeconomics 14, no. 3 (August 2022): 164–212.
      • 2022
      • Article

      Data Poisoning Attacks on Off-Policy Evaluation Methods

      By: Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin and Himabindu Lakkaraju
      Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expensive. However, the extent to which such methods can be trusted under adversarial threats...  View Details
      Keywords: Analytics and Data Science; Cybersecurity; Mathematical Methods
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      Lobo, Elita, Harvineet Singh, Marek Petrik, Cynthia Rudin, and Himabindu Lakkaraju. "Data Poisoning Attacks on Off-Policy Evaluation Methods." Special Issue on Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022). Proceedings of Machine Learning Research (PMLR) 180 (2022): 1264–1274.
      • 2022
      • Article

      Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations

      By: Jessica Dai, Sohini Upadhyay, Ulrich Aivodji, Stephen Bach and Himabindu Lakkaraju
      As post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to ensure that the quality of the resulting explanations is consistently high across all subgroups of a population. For instance, it...  View Details
      Keywords: Prejudice and Bias; Mathematical Methods; Research; Analytics and Data Science
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      Dai, Jessica, Sohini Upadhyay, Ulrich Aivodji, Stephen Bach, and Himabindu Lakkaraju. "Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2022): 203–214.
      • 2022
      • Article

      Nonparametric Subset Scanning for Detection of Heteroscedasticity

      By: Charles R. Doss and Edward McFowland III
      We propose Heteroscedastic Subset Scan (HSS), a novel method for identifying covariates that are responsible for violations of the homoscedasticity assumption in regression settings. Viewing the problem as one of anomalous pattern detection, we use subset scanning...  View Details
      Keywords: Scan Statistics; Anomaly Detection; Regression; Model Diagnostics
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      Doss, Charles R., and Edward McFowland III. "Nonparametric Subset Scanning for Detection of Heteroscedasticity." Journal of Computational and Graphical Statistics 31, no. 3 (2022): 813–823.
      • 2022
      • Article

      Towards Robust Off-Policy Evaluation via Human Inputs

      By: Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez and Himabindu Lakkaraju
      Off-policy Evaluation (OPE) methods are crucial tools for evaluating policies in high-stakes domains such as healthcare, where direct deployment is often infeasible, unethical, or expensive. When deployment environments are expected to undergo changes (that is, dataset...  View Details
      Keywords: Analytics and Data Science; Research
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      Singh, Harvineet, Shalmali Joshi, Finale Doshi-Velez, and Himabindu Lakkaraju. "Towards Robust Off-Policy Evaluation via Human Inputs." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2022): 686–699.
      • 2022
      • Working Paper

      Measuring the Tolerance of the State: Theory and Application to Protest

      By: Veli Andirin, Yusuf Neggers, Mehdi Shadmehr and Jesse M. Shapiro
      We develop a measure of a regime's tolerance for an action by its citizens. We ground our measure in an economic model and apply it to the setting of political protest. In the model, a regime anticipating a protest can take a costly action to repress it. We define the...  View Details
      Keywords: Political Protests; Modeling And Analysis; Government and Politics; Conflict and Resolution
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      Andirin, Veli, Yusuf Neggers, Mehdi Shadmehr, and Jesse M. Shapiro. "Measuring the Tolerance of the State: Theory and Application to Protest." NBER Working Paper Series, No. 30167, June 2022.
      • June 2022
      • Article

      The Use and Misuse of Patent Data: Issues for Finance and Beyond

      By: Josh Lerner and Amit Seru
      Patents and citations are powerful tools for understanding innovation increasingly used in financial economics (and management research more broadly). Biases may result, however, from the interactions between the truncation of patents and citations and the changing...  View Details
      Keywords: Patents; Analytics and Data Science; Corporate Finance; Research
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      Lerner, Josh, and Amit Seru. "The Use and Misuse of Patent Data: Issues for Finance and Beyond." Review of Financial Studies 35, no. 6 (June 2022): 2667–2704.
      • 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

      Act Like a Scientist: Great Leaders Challenge Assumptions, Run Experiments, and Follow the Evidence

      By: Stefan Thomke and Gary W. Loveman
      Though they’ve been warned for decades about the dangers of overrelying on gut instinct and personal experience, managers keep failing to critically examine—much less challenge—the ideas their decisions are based on. To correct this problem they need to think and act...  View Details
      Keywords: Innovation and Management; Decision Making; Science; Leadership Style
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      Thomke, Stefan, and Gary W. Loveman. "Act Like a Scientist: Great Leaders Challenge Assumptions, Run Experiments, and Follow the Evidence." Harvard Business Review 100, no. 3 (May–June 2022): 120–129.
      • 2022
      • Article

      Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.

      By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
      As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a...  View Details
      Keywords: Machine Learning Models; Counterfactual Explanations; Adversarial Examples; Mathematical Methods
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      Pawelczyk, Martin, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, and Himabindu Lakkaraju. "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
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