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- September 2025
- Article
Using Satellites and Phones to Evaluate and Promote Agricultural Technology Adoption: Evidence from Smallholder Farms in India
By: Shawn Cole, Tomoko Harigaya, Grady Killeen and Aparna Krishna
This paper evaluates a low-cost, customized soil nutrient management advisory service in India. As a methodological contribution, we examine whether and in which settings satellite measurements may be effective at estimating both agricultural yields and treatment... View Details
- 2025
- Working Paper
Using Satellites and Phones to Evaluate and Promote Agricultural Technology Adoption: Evidence from Smallholder Farms in India
By: Shawn Cole, Grady Killeen, Tomoko Harigaya and Aparna Krishna
This paper evaluates a low-cost, customized soil nutrient management advisory service in India. As a methodological contribution, we examine whether and in which settings satellite measurements may be effective at estimating both agricultural yields and treatment... View Details
- January 2025
- Module Note
Understanding and Addressing Gender Gaps
This module provides a framework for students to analyze how gender stereotypes, through their impact on beliefs about others and beliefs about ourselves, contribute to gender gaps in the workplace. The module proceeds in three parts. First, through a case and an... View Details
- January 2025
- Case
AI Meets VC: The Data-Driven Revolution at Quantum Light Capital
By: Lauren Cohen, Grace Headinger and Sophia Pan
Ilya Kondrashov, CEO of Quantum Light Capital, was driven to harness AI for identifying high-potential scale-ups. Collaborating with Nik Storonsky, founder of Revolut, the duo observed that most venture capital (VC) decisions were heavily influenced by emotion, with... View Details
Keywords: Artificial Intelligence; Business Finance; Data Analysis; Angel Investors; Cognitive Biases; Scale; Venture Capital; Investment; Business Model; Forecasting and Prediction; Technological Innovation; Innovation Strategy; Behavior; Cognition and Thinking; Public Opinion; Private Sector; Business Strategy; Competitive Advantage; Business Earnings; Behavioral Finance; AI and Machine Learning; Analytics and Data Science; Business Startups; Financial Services Industry; London; United Kingdom
- 2024
- Working Paper
Charting (and Updating) the Path: A Bayesian Perspective on Entrepreneurial Learning
This chapter explores two distinct modes of entrepreneurial learning: assessing
venture viability and choosing between alternative development paths. It introduces
a framework for decomposing venture viability into technological feasibility, commercial
potential and... View Details
- October 2024
- Article
Sampling Bias in Entrepreneurial Experiments
By: Ruiqing Cao, Rembrand Koning and Ramana Nanda
Using data from a prominent online platform for launching new digital products, we document that ‘sampling bias’—defined as the difference between a startup’s target customer base and the actual sample on which early ‘beta tests’ are conducted—has a systematic and... View Details
- August 2024
- Article
Heuristics on Call: The Impact of Mobile-Phone-Based Business-Management Advice
By: Shawn Cole, Mukta Joshi and Antoinette Schoar
There is growing evidence that business training for micro-entrepreneurs can be effective. However, in-person training can be expensive and imposes costs on the target beneficiaries. This paper presents the results of a two-site randomized evaluation of a light-touch,... View Details
- July 2024
- Article
Acceptance of Automated Vehicles Is Lower for Self than Others
By: Stuti Agarwal, Julian De Freitas, Anya Ragnhildstveit and Carey K. Morewedge
Road traffic accidents are the leading cause of death worldwide for people aged 2–59. Nearly all deaths are due to human error. Automated vehicles could reduce mortality risks, traffic congestion, and air pollution of human-driven vehicles. However, their adoption... View Details
- 2024
- Working Paper
Demographically Biased Technological Change
By: Victor Manuel Bennett, John-Paul Ferguson, Masoomeh Kalantari and Rembrand Koning
Who gets the jobs that automation creates? A consensus has begun to emerge that said technologies complement rather than substitute for labor. However, they also shift the demand for specific types of skills and other worker competencies. Such shifts imply unequal... View Details
- May–June 2024
- Article
Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs
By: Jacqueline N. Lane, Karim R. Lakhani and Roberto Fernandez
Competence development in digital technologies, analytics, and artificial intelligence is increasingly important to all types of organizations and their workforce. Universities and corporations are investing heavily in developing training programs, at all tenure... View Details
- April 3, 2024
- Article
How Automakers Can Address Resistance to Self-Driving Cars
By: Stuti Agarwal, Julian De Freitas and Carey K. Morewedge
Research involving multiple experiments found that consumers have biased views of their driving abilities relative to those of other drivers and automated vehicles. These findings have implications for the adoption of partly or fully automated vehicles, which one day... View Details
- March 2024
- Case
Unintended Consequences of Algorithmic Personalization
By: Eva Ascarza and Ayelet Israeli
“Unintended Consequences of Algorithmic Personalization” (HBS No. 524-052) investigates algorithmic bias in marketing through four case studies featuring Apple, Uber, Facebook, and Amazon. Each study presents scenarios where these companies faced public criticism for... View Details
- 2024
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift
By: Matthew DosSantos DiSorbo and Kris Ferreira
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). These outliers often originate from covariate shift,... 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
- 2023
- Working Paper
Words Can Hurt: How Political Communication Can Change the Pace of an Epidemic
By: Jessica Gagete-Miranda, Lucas Argentieri Mariani and Paula Rettl
While elite-cue effects on public opinion are well-documented, questions remain as
to when and why voters use elite cues to inform their opinions and behaviors. Using
experimental and observational data from Brazil during the COVID-19 pandemic, we
study how leader... View Details
Keywords: Elites; Public Engagement; Politics; Political Affiliation; Political Campaigns; Political Influence; Political Leadership; Political Economy; Survey Research; COVID-19; COVID-19 Pandemic; COVID; Cognitive Psychology; Cognitive Biases; Political Elections; Voting; Power and Influence; Identity; Behavior; Latin America; Brazil
- September 2023
- Exercise
Irrationality in Action: Decision-Making Exercise
By: Alison Wood Brooks, Michael I. Norton and Oliver Hauser
This teaching exercise highlights the obstacle of biases in decision-making, allowing students to generate examples of potentially poor decision-making rooted in abundant and unwanted bias. This exercise has two parts: a pre-class, online survey in which students... View Details
- August 2023
- Article
Can Security Design Foster Household Risk-Taking?
By: Laurent Calvet, Claire Célérier, Paolo Sodini and Boris Vallée
This paper shows that securities with a non-linear payoff design can foster household risk-taking. We demonstrate this effect empirically by exploiting the introduction of capital guarantee products in Sweden from 2002 to 2007. The fast and broad adoption of these... View Details
- 2023
- Working Paper
How People Use Statistics
By: Pedro Bordalo, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer
We document two new facts about the distributions of answers in famous statistical problems: they are i) multi-modal and ii) unstable with respect to irrelevant changes in the problem. We offer a model in which, when solving a problem, people represent each hypothesis... View Details
- June 2023
- Article
Amplification of Emotion on Social Media
By: Amit Goldenberg and Robb Willer
Why do expressions of emotion seem so heightened on social media? Brady et al. argue that extreme moral outrage on social media is not only driven by the producers and sharers of emotional expressions, but also by systematic biases in the way people that perceive moral... View Details
- 2023
- Working Paper
Auditing Predictive Models for Intersectional Biases
By: Kate S. Boxer, Edward McFowland III and Daniel B. Neill
Predictive models that satisfy group fairness criteria in aggregate for members of a protected class, but do not guarantee subgroup fairness, could produce biased predictions for individuals at the intersection of two or more protected classes. To address this risk, we... View Details