Publications
Publications
Show Results For
- All HBS Web
(436)
- Faculty Publications (111)
- 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
- November–December 2020
- Article
The Risks You Can't Foresee: What to Do When There's No Playbook
By: Robert S. Kaplan, Herman B. Leonard and Anette Mikes
No matter how good their risk management systems are, companies can’t plan for everything. Some risks are outside people’s realm of experience or so remote no one could have imagined them. Some result from a perfect storm of coinciding breakdowns, and some materialize... View Details
- Article
Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs
By: Michael G. Endres, Florian Hillen, Marios Salloumis, Ahmad R. Sedaghat, Stefan M. Niehues, Olivia Quatela, Henning Hanken, Ralf Smeets, Benedicta Beck-Broichsitter, Carsten Rendenbach, Karim R. Lakhani, Max Helland and Robert A. Gaudin
Periapical radiolucencies, which can be detected on panoramic radiographs, are one of the most common radiographic findings in dentistry and have a differential diagnosis including infections, granuloma, cysts, and tumors. In this study, we seek to investigate the... View Details
- Article
Paper Versus Practice: A Field Investigation of Integrity Hotlines
By: Eugene Soltes
In an effort to motivate firms to more rapidly detect potential misconduct, legislators, regulators, and enforcement agencies incentivize firms to have integrity or “whistleblowing” hotlines. These hotlines provide individuals an opportunity to report alleged... View Details
- 2020
- Working Paper
Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation
By: Michael Yeomans and Alison Wood Brooks
Although most humans engage in conversations constantly throughout their lives, conversational mistakes are commonplace— interacting with others is difficult, and conversation re-quires quick, relentless perspective-taking and decision making. For example: during every... View Details
- 2020
- Conference Presentation
A Performance-optimized Limb Detection Model Selectively Predicts Behavioral Responses Based on Movement Similarity
By: X. Zhao, J. De Freitas, L. Tarhan and G. A. Alvarez
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
- May 2020
- Article
Scalable Holistic Linear Regression
By: Dimitris Bertsimas and Michael Lingzhi Li
We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting... View Details
- 2019
- Article
The Frequency of Corporate Misconduct: Public Enforcement versus Private Reality
By: Eugene F. Soltes
Perceptions about the frequency of misconduct—among the public, academics and even
regulators—have largely been formed by examining enforcement statistics, which rely on the detection and sanctioning of the misconduct. This study aims to illuminate the real occurrence... View Details
- November 9, 2019
- Article
Effect of Revealing Authors' Conflicts of Interests in Peer Review: Randomized Controlled Trial
By: Leslie K. John, George Loewenstein, Andrew Marder and Michael Callaham
Objective: To assess the impact of disclosing authors’ conflict of interest declarations to peer reviewers at a medical journal.
Design: Randomised controlled trial.
Setting: The study was conducted within the manuscript review process at the... View Details
Design: Randomised controlled trial.
Setting: The study was conducted within the manuscript review process at the... View Details
- Article
Effect of Different Financial Incentive Structures on Promoting Physical Activity Among Adults: A Randomized Clinical Trial
By: Chethan Bachireddy, Andrew Joung, Leslie K. John, Francesca Gino, Bradford Tuckfield, Luca Foschini and Katherine L. Milkman
Importance: Few adults engage in recommended levels of physical activity. Financial incentives can promote physical activity, but little is known about how their structure influences their effectiveness; for example, whether incentives are more effective if they are... View Details
- 2020
- Working Paper
Are ISS Recommendations Informative? Evidence from Assessments of Compensation Practices
By: Ana Albuquerque, Mary Ellen Carter and Susanna Gallani
Using detailed information from the largest proxy advisor in the U.S., Institutional Shareholder Services (ISS), we examine whether proxy advisors’ assessments of firms’ compensation practices are able to identify poor compensation practices as measured by subsequent... View Details
- Article
Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications
By: Daniel Elsner, Pouya Aleatrati Khosroshahi, Alan MacCormack and Robert Lagerström
Existing application performance management (APM) solutions lack robust anomaly detection capabilities and root cause analysis techniques that do not require manual efforts and domain knowledge. In this paper, we develop a density-based unsupervised machine learning... View Details
- September 2018 (Revised December 2019)
- Case
Zebra Medical Vision
By: Shane Greenstein and Sarah Gulick
An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making... View Details
Keywords: Radiology; Machine Learning; X-ray; CT Scan; Medical Technology; Probability; FDA 510(k); Diagnosis; Business Startups; Health Care and Treatment; Information Technology; Applications and Software; Competitive Strategy; Product Development; Commercialization; Decision Choices and Conditions; Health Industry; Medical Devices and Supplies Industry; Technology Industry; Israel
- 2018
- Working Paper
Detecting Anomalies: The Relevance and Power of Standard Asset Pricing Tests
By: Malcolm Baker, Patrick Luo and Ryan Taliaferro
The two standard approaches for identifying capital market anomalies are cross-sectional coefficient tests, in the spirit of Fama and MacBeth (1973), and time-series intercept tests, in the spirit of Jensen (1968). A new signal can pass the first test, which we label a... View Details
- 2018
- Simulation
Financial Analysis Simulation: Data Detective
By: Suraj Srinivasan and V.G. Narayanan
In this simulation, students learn to identify typical industry characteristics revealed in financial data. Equipped with an interactive and flexible set of tools, students analyze disguised financials and—using their knowledge of operational practices and reasoning... View Details
- November 2021
- Article
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data
By: William Herlands, Edward McFowland III, Andrew Gordon Wilson and Daniel B. Neill
Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately consider the anomalousness of each individual data point have low detection power for subtle,... View Details
- Article
Why Compliance Programs Fail: And How to Fix Them
By: Hui Chen and Eugene Soltes
Firms spend millions of dollars annually on whistle-blower hotlines, training, and other efforts to ensure adherence to laws, regulations, and company policies. Yet malfeasance remains entrenched in the corporate world. Why? Too many firms treat compliance as a... View Details
- February 2018
- Article
Retention Futility: Targeting High-Risk Customers Might Be Ineffective.
By: Eva Ascarza
Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models... View Details
- 2023
- Working Paper
Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection
By: Edward McFowland III, Sriram Somanchi and Daniel B. Neill
In the recent literature on estimating heterogeneous treatment effects, each proposed method makes its own set of restrictive assumptions about the intervention’s effects and which subpopulations to explicitly estimate. Moreover, the majority of the literature provides... View Details