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- May 2025
- Teaching Note
The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation
By: Tsedal Neeley
Teaching Note for HBS Case No. 425-720. Florian Hillen, co-founder and CEO of VideaHealth, a startup using artificial intelligence (AI) to detect dental conditions on x-rays, spent the early years of his company laying the groundwork for an AI factory. This AI factory,... View Details
Keywords: Diagnostics; Organization Design; Change Management; Disruption; Transformation; Health Care and Treatment; AI and Machine Learning; Technological Innovation; Technology Adoption; Disruptive Innovation; Management Style; Organizational Culture; Success; Adoption; Technology Industry; Health Industry; United States
- January 2025
- Technical Note
AI vs Human: Analyzing Acceptable Error Rates Using the Confusion Matrix
By: Tsedal Neeley and Tim Englehart
This technical note introduces the confusion matrix as a foundational tool in artificial intelligence (AI) and large language models (LLMs) for assessing the performance of classification models, focusing on their reliability for decision-making. A confusion matrix... View Details
- January 2025
- Case
The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation (A)
By: Tsedal Neeley, Levi Stroud, Ruth Page and Dave Habeeb
Pre-abstract:
This multimedia case should be assigned to students in advance of class. Instructors should consider the timing of making the (B) Case videos available to students, as they may reveal key case details.
Abstract: Florian Hillen, co-founder... View Details
Abstract: Florian Hillen, co-founder... View Details
- January 2025
- Supplement
The VideaHealth AI Factory: CEO Florian Hillen on Speed, Scale, and Innovation (B)
By: Tsedal Neeley, Levi Stroud, Ruth Page and Dave Habeeb
Pre-abstract:
This multimedia case should be assigned to students in advance of class. Instructors should consider the timing of making the (B) Case videos available to students, as they may reveal key case details.
Abstract: Florian Hillen, co-founder... View Details
Abstract: Florian Hillen, co-founder... View Details
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
- Working Paper
Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application
By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely... View Details
- 2023
- Article
Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset
By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,... View Details
- 2023
- Article
Post Hoc Explanations of Language Models Can Improve Language Models
By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance... View Details
- December 2023
- Article
When Should the Off-Grid Sun Shine at Night? Optimum Renewable Generation and Energy Storage Investments
By: Christian Kaps, Simone Marinesi and Serguei Netessine
Globally, 1.5 billion people live off the grid, their only access to electricity often limited to operationally-expensive fossil fuel generators. Solar power has risen as a sustainable and less costly option, but its generation is variable during the day and... View Details
- September–October 2023
- Article
Interpretable Matrix Completion: A Discrete Optimization Approach
By: Dimitris Bertsimas and Michael Lingzhi Li
We consider the problem of matrix completion on an n × m matrix. We introduce the problem of interpretable matrix completion that aims to provide meaningful insights for the low-rank matrix using side information. We show that the problem can be... View Details
Keywords: Mathematical Methods
- 2023
- Working Paper
PRIMO: Private Regression in Multiple Outcomes
By: Seth Neel
We introduce a new differentially private regression setting we call Private Regression in Multiple Outcomes (PRIMO), inspired the common situation where a data analyst wants to perform a set of l regressions while preserving privacy, where the covariates... View Details
- 2023
- Working Paper
The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities
By: David S. Scharfstein and Sergey Chernenko
We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement bias in... View Details
- 2023
- Working Paper
Remote Work across Jobs, Companies, and Space
By: Stephen Hansen, Peter John Lambert, Nick Bloom, Steven J. Davis, Raffaella Sadun and Bledi Taska
The pandemic catalyzed an enduring shift to remote work. To measure and characterize
this shift, we examine more than 250 million job vacancy postings across five
English-speaking countries. Our measurements rely on a state-of-the-art language-processing
framework... View Details
- December 2022
- Article
'Just Letting You Know…': Underestimating Others' Desire for Constructive Feedback
By: Nicole Abi-Esber, Jennifer E. Abel, Juliana Schroeder and Francesca Gino
People often avoid giving feedback to others even when it would help fix a problem immediately. Indeed, in a pilot field study (N=155), only 2.6% of individuals provided feedback to survey administrators that the administrators had food or marker on their faces.... View Details
- 2022
- Working Paper
Machine Learning Models for Prediction of Scope 3 Carbon Emissions
By: George Serafeim and Gladys Vélez Caicedo
For most organizations, the vast amount of carbon emissions occur in their supply chain and in the post-sale processing, usage, and end of life treatment of a product, collectively labelled scope 3 emissions. In this paper, we train machine learning algorithms on 15... View Details
- April 12, 2022
- Article
Evaluation of Individual and Ensemble Probabilistic Forecasts of COVID-19 Mortality in the United States
By: Estee Y. Cramer, Evan L. Ray, Velma K. Lopez, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Michael Lingzhi Li and et al.
Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models... View Details
- December 2021
- Article
Entrepreneurial Learning and Strategic Foresight
By: Aticus Peterson and Andy Wu
We study how learning by experience across projects affects an entrepreneur's strategic foresight. In a quantitative study of 314 entrepreneurs across 722 crowdfunded projects supplemented with a program of qualitative interviews, we counterintuitively find that... View Details
- 2021
- Working Paper
'Just Letting You Know…': Underestimating Others' Desire for Constructive Feedback
By: Nicole Abi-Esber, Jennifer Abel, Juliana Schroeder and Francesca Gino
People often avoid giving feedback to others even when it would help fix a problem immediately. Indeed, in a pilot field study (N=155), only 2.6% of individuals provided feedback to survey administrators that the administrators had food or marker on their faces.... View Details
Keywords: Feedback; Helping; Prosocial Behavior; Relationships; Social Psychology; Theory; Perception
- Article
Emotional Acknowledgment: How Verbalizing Others' Emotions Fosters Interpersonal Trust
By: Alisa Yu, Justin M. Berg and Julian Zlatev
People often respond to others’ emotions using verbal acknowledgment (e.g., “You seem upset”). Yet, little is known about the relational benefits and risks of acknowledging others’ emotions in the workplace. We draw upon Costly Signaling Theory to posit how emotional... View Details