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    • Research  (256)
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  • All HBS Web  (381)
    • News  (71)
    • Research  (256)
    • Events  (9)
    • Multimedia  (1)
  • Faculty Publications  (150)
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  • September 2019 (Revised September 2019)
  • Case

Facebook Fake News in the Post-Truth World

By: John R. Wells, Carole A. Winkler and Benjamin Weinstock
In August 2019, Mark Zuckerberg, founder and CEO of Facebook, was surrounded by controversy. The first major storm of protest followed the surprise election of Donald Trump as President of the United States on November 8, 2016; many put the blame at the door of fake... View Details
Keywords: Facebook; Fake News; Mark Zuckerberg; Donald Trump; Algorithms; Social Networks; Partisanship; Social Media; App Development; Instagram; WhatsApp; Smartphone; Silicon Valley; Office Space; Digital Strategy; Democracy; Entry Barriers; Online Platforms; Controversy; Tencent; Agility; Social Networking; Gaming; Gaming Industry; Computer Games; Mobile Gaming; Messaging; Monetization Strategy; Advertising; Digital Marketing; Business Ventures; Acquisition; Mergers and Acquisitions; Business Growth and Maturation; Business Headquarters; Business Organization; For-Profit Firms; Trends; Communication; Communication Technology; Forms of Communication; Interactive Communication; Interpersonal Communication; Talent and Talent Management; Crime and Corruption; Voting; Demographics; Entertainment; Games, Gaming, and Gambling; Moral Sensibility; Values and Beliefs; Initial Public Offering; Profit; Revenue; Geography; Geographic Location; Global Range; Local Range; Country; Cross-Cultural and Cross-Border Issues; Globalized Firms and Management; Globalized Markets and Industries; Governing Rules, Regulations, and Reforms; Government and Politics; International Relations; National Security; Political Elections; Business History; Recruitment; Selection and Staffing; Information Management; Information Publishing; News; Newspapers; Innovation and Management; Innovation Strategy; Technological Innovation; Knowledge Dissemination; Human Capital; Law; Leadership Development; Leadership Style; Leading Change; Business or Company Management; Crisis Management; Goals and Objectives; Growth and Development Strategy; Growth Management; Management Practices and Processes; Management Style; Management Systems; Management Teams; Managerial Roles; Marketing Channels; Social Marketing; Network Effects; Market Entry and Exit; Digital Platforms; Marketplace Matching; Industry Growth; Industry Structures; Monopoly; Media; Product Development; Service Delivery; Corporate Social Responsibility and Impact; Mission and Purpose; Organizational Change and Adaptation; Organizational Culture; Organizational Structure; Public Ownership; Problems and Challenges; Business and Community Relations; Business and Government Relations; Groups and Teams; Networks; Rank and Position; Opportunities; Behavior; Emotions; Identity; Power and Influence; Prejudice and Bias; Reputation; Social and Collaborative Networks; Status and Position; Trust; Society; Civil Society or Community; Culture; Public Opinion; Social Issues; Societal Protocols; Strategy; Adaptation; Business Strategy; Commercialization; Competition; Competitive Advantage; Competitive Strategy; Corporate Strategy; Customization and Personalization; Diversification; Expansion; Horizontal Integration; Segmentation; Information Technology; Internet and the Web; Mobile and Wireless Technology; Applications and Software; Information Infrastructure; Valuation; Advertising Industry; Communications Industry; Entertainment and Recreation Industry; Information Industry; Information Technology Industry; Journalism and News Industry; Media and Broadcasting Industry; Service Industry; Technology Industry; Telecommunications Industry; Video Game Industry; United States; California; Sunnyvale; Russia
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Wells, John R., Carole A. Winkler, and Benjamin Weinstock. "Facebook Fake News in the Post-Truth World." Harvard Business School Case 720-373, September 2019. (Revised September 2019.)
  • 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.)
  • January 2024 (Revised February 2024)
  • Course Overview Note

Managing Customers for Growth: Course Overview for Students

By: Eva Ascarza
Managing Customers for Growth (MCG) is a 14-session elective course for second-year MBA students at Harvard Business School. It is designed for business professionals engaged in roles centered on customer-driven growth activities. The course explores the dynamics of... View Details
Keywords: Customer Relationship Management; Decision Making; Analytics and Data Science; Growth Management; Telecommunications Industry; Technology Industry; Financial Services Industry; Education Industry; Travel Industry
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Ascarza, Eva. "Managing Customers for Growth: Course Overview for Students." Harvard Business School Course Overview Note 524-032, January 2024. (Revised February 2024.)
  • October 2022
  • Exercise

Shanty Real Estate: Confidential Information for Homebuyer 3

By: Michael Luca, Jesse M. Shapiro and Nathan Sun
Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
Keywords: Decision Choices and Conditions; Decision Making; Measurement and Metrics; Market Timing
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Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Confidential Information for Homebuyer 3." Harvard Business School Exercise 923-018, October 2022.
  • October 2022
  • Exercise

Shanty Real Estate: Confidential Information for iBuyer 2

By: Michael Luca, Jesse M. Shapiro and Nathan Sun
Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
Keywords: Decision Choices and Conditions; Decision Making; Market Timing; Measurement and Metrics
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Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Confidential Information for iBuyer 2." Harvard Business School Exercise 923-020, October 2022.
  • October 2022
  • Exercise

Shanty Real Estate: Confidential Information for Homebuyer 1

By: Michael Luca, Jesse M. Shapiro and Nathan Sun
Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
Keywords: Data-driven Decision-making; Decisions; Negotiation; Bids and Bidding; Valuation; Consumer Behavior; Real Estate Industry
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Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Confidential Information for Homebuyer 1." Harvard Business School Exercise 923-016, October 2022.
  • 2023
  • Working Paper

In-Context Unlearning: Language Models as Few Shot Unlearners

By: Martin Pawelczyk, Seth Neel and Himabindu Lakkaraju
Machine unlearning, the study of efficiently removing the impact of specific training points on the trained model, has garnered increased attention of late, driven by the need to comply with privacy regulations like the Right to be Forgotten. Although unlearning is... View Details
Keywords: AI and Machine Learning; Copyright; Information
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Pawelczyk, Martin, Seth Neel, and Himabindu Lakkaraju. "In-Context Unlearning: Language Models as Few Shot Unlearners." Working Paper, October 2023.
  • 2024
  • Article

Learning Under Random Distributional Shifts

By: Kirk Bansak, Elisabeth Paulson and Dominik Rothenhäusler
Algorithmic assignment of refugees and asylum seekers to locations within host countries has gained attention in recent years, with implementations in the U.S. and Switzerland. These approaches use data on past arrivals to generate machine learning models that can... View Details
Keywords: AI and Machine Learning; Refugees; Employment
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Bansak, Kirk, Elisabeth Paulson, and Dominik Rothenhäusler. "Learning Under Random Distributional Shifts." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 27th (2024).
  • October 2022
  • Exercise

Shanty Real Estate: Confidential Information for Homebuyer 2

By: Michael Luca, Jesse M. Shapiro and Nathan Sun
Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
Keywords: Decision Choices and Conditions; Decision Making; Measurement and Metrics; Market Timing
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Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Confidential Information for Homebuyer 2." Harvard Business School Exercise 923-017, October 2022.
  • 10 Feb 2020
  • In Practice

6 Ways That Emerging Technology Is Disrupting Business Strategy

involving artificial intelligence (AI), data analytics, and the Internet of Things are changing the way business leaders think about strategy. Here’s what they said: 1. Talent and data are more critical than... View Details
Keywords: by Danielle Kost
  • October 2017 (Revised April 2018)
  • Case

Improving Worker Safety in the Era of Machine Learning (A)

By: Michael W. Toffel, Dan Levy, Jose Ramon Morales Arilla and Matthew S. Johnson
Managers make predictions all the time: How fast will my markets grow? How much inventory do I need? How intensively should I monitor my suppliers? Which potential customers will be most responsive to a particular marketing campaign? Which job candidates should I... View Details
Keywords: Machine Learning; Policy Implementation; Empirical Research; Inspection; Occupational Safety; Occupational Health; Regulation; Analysis; Forecasting and Prediction; Policy; Operations; Supply Chain Management; Safety; Manufacturing Industry; Construction Industry; United States
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Toffel, Michael W., Dan Levy, Jose Ramon Morales Arilla, and Matthew S. Johnson. "Improving Worker Safety in the Era of Machine Learning (A)." Harvard Business School Case 618-019, October 2017. (Revised April 2018.)
  • Winter 2016
  • Article

Analytics for an Online Retailer: Demand Forecasting and Price Optimization

By: Kris J. Ferreira, Bin Hong Alex Lee and David Simchi-Levi
We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time... View Details
Keywords: Internet and the Web; Price; Forecasting and Prediction; Revenue; Sales; Retail Industry
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Ferreira, Kris J., Bin Hong Alex Lee, and David Simchi-Levi. "Analytics for an Online Retailer: Demand Forecasting and Price Optimization." Manufacturing & Service Operations Management 18, no. 1 (Winter 2016): 69–88.
  • 09 Dec 2019
  • Research & Ideas

Identify Great Customers from Their First Purchase

School. By incorporating data most companies discard, Ascarza and her co-researcher devised an algorithm capable of quickly analyzing more than 40 variables to create a “first impression” of the customer... View Details
Keywords: by Kristen Senz; Retail; Service
  • March 2021
  • Case

VideaHealth: Building the AI Factory

By: Karim R. Lakhani and Amy Klopfenstein
Florian Hillen, co-founder and CEO of VideaHealth, a startup that used artificial intelligence (AI) to detect dental conditions on x-rays, spent the early years of his company laying the groundwork for an AI factory. A process for quickly building and iterating on new... View Details
Keywords: Artificial Intelligence; Innovation and Invention; Disruptive Innovation; Technological Innovation; Information Technology; Applications and Software; Technology Adoption; Digital Platforms; Entrepreneurship; AI and Machine Learning; Technology Industry; Medical Devices and Supplies Industry; North and Central America; United States; Massachusetts; Cambridge
Citation
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Lakhani, Karim R., and Amy Klopfenstein. "VideaHealth: Building the AI Factory." Harvard Business School Case 621-021, March 2021.
  • Article

Counterfactual Explanations Can Be Manipulated

By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh
Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate... View Details
Keywords: Machine Learning Models; Counterfactual Explanations
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Slack, Dylan, Sophie Hilgard, Himabindu Lakkaraju, and Sameer Singh. "Counterfactual Explanations Can Be Manipulated." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
  • 2024
  • Book

Fintech, Small Business & the American Dream: How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity

By: Karen G. Mills
The second edition of Fintech, Small Business & the American Dream, builds on the groundbreaking 2019 book with new insights on how technology and artificial intelligence are transforming small business lending. This ambitious view covers the significance of... View Details
Keywords: Fintech; AI; AI and Machine Learning; Small Business; Economy; Technology Adoption; Credit; Financing and Loans; Analytics and Data Science
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Mills, Karen G. Fintech, Small Business & the American Dream: How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity. 2nd Edition, NY: Palgrave Macmillan, 2024.
  • 2024
  • Working Paper

The Cram Method for Efficient Simultaneous Learning and Evaluation

By: Zeyang Jia, Kosuke Imai and Michael Lingzhi Li
We introduce the "cram" method, a general and efficient approach to simultaneous learning and evaluation using a generic machine learning (ML) algorithm. In a single pass of batched data, the proposed method repeatedly trains an ML algorithm and tests its empirical... View Details
Keywords: AI and Machine Learning
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Jia, Zeyang, Kosuke Imai, and Michael Lingzhi Li. "The Cram Method for Efficient Simultaneous Learning and Evaluation." Working Paper, March 2024.
  • 08 Nov 2016
  • First Look

November 8, 2016

quantifies immigrant contributions to new firm creation in a wide variety of fields and using multiple definitions. While significant research effort has gone into understanding the economic impact of immigration into the United States, comprehensive View Details
Keywords: Sean Silverthorne
  • 05 Jul 2006
  • Working Paper Summaries

Time-Driven Activity-Based Costing

Keywords: by Robert S. Kaplan & Steven R. Anderson; Financial Services
  • Article

Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM

By: Katrina Ligett, Seth Neel, Aaron Leon Roth, Bo Waggoner and Steven Wu
Traditional approaches to differential privacy assume a fixed privacy requirement ϵ for a computation, and attempt to maximize the accuracy of the computation subject to the privacy constraint. As differential privacy is increasingly deployed in practical settings, it... View Details
Keywords: Differential Privacy; Empirical Risk Minimization; Accuracy First
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Ligett, Katrina, Seth Neel, Aaron Leon Roth, Bo Waggoner, and Steven Wu. "Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM." Journal of Privacy and Confidentiality 9, no. 2 (2019).
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