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- All HBS Web
(1,027)
- People (1)
- News (187)
- Research (617)
- Events (11)
- Multimedia (3)
- Faculty Publications (498)
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- 22 Feb 2024
- Research & Ideas
How to Make AI 'Forget' All the Private Data It Shouldn't Have
There’s a virtual elephant in AI’s room: It’s nearly impossible to make the technology forget. And there are an increasing number of scenarios where consumers and programmers may not only want to remove data from a machine View Details
- May 2022 (Revised July 2022)
- Case
The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022
By: David B. Yoffie and Daniel Fisher
In 2022, after five years of pursuing a new "AI-first" strategy, Google had captured a sizeable share of the American and global markets for voice assistants. Google Assistant was used by hundreds of millions of users around the world, but Amazon retained the largest... View Details
Keywords: Strategy; Artificial Intelligence; Deep Learning; Voice Assistants; Smart Home; Market Share; Globalized Markets and Industries; Competitive Strategy; Digital Platforms; AI and Machine Learning; Technology Industry; United States
Yoffie, David B., and Daniel Fisher. "The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022." Harvard Business School Case 722-462, May 2022. (Revised July 2022.)
- Spring 2021
- Article
Corporate Resilience and Response During COVID-19
By: Alex Cheema-Fox, Bridget LaPerla, George Serafeim and Hui (Stacie) Wang
The coronavirus pandemic caused a sharp market decline while raising heterogeneous responses across companies related to their employees, supply chain, and repurposing of operations to provide needed products and services. We study whether during the 2020 COVID-19... View Details
Keywords: ESG; COVID-19; Coronavirus; Crisis Response Plans; Crisis; ESG (Environmental, Social, Governance) Performance; ESG Ratings; Leadership & Corporate Accountability; Big Data; Machine Learning; Investor Behavior; Institutional Investors; Corporate Performance; Health Pandemics; Crisis Management; Corporate Social Responsibility and Impact; Human Capital; Supply Chain; Operations; Leadership; Corporate Accountability; Institutional Investing; Performance
Cheema-Fox, Alex, Bridget LaPerla, George Serafeim, and Hui (Stacie) Wang. "Corporate Resilience and Response During COVID-19." Journal of Applied Corporate Finance 33, no. 2 (Spring 2021): 24–40.
- Research Summary
Overview
Paul is primarily interested in studying explainable machine learning (ML), digital transformation, and data science operations. He works on research that explores how stakeholders within organizations can use machine learning to make better decisions. In particular,... View Details
- 26 Mar 2024
- Research & Ideas
How Humans Outshine AI in Adapting to Change
begin a task, pivoting your perspective of where you are and what you can do as your environment changes. Artificial intelligence can’t do that yet—and the machines may have a long way to go before they can truly replicate this... View Details
- Teaching Interest
Empirical Technology and Operations Management Course
I taught a set of lectures on "Introduction to Machine Learning for Social Scientists" as part of this required course for first year PhD students. This module familiarizes students with all the basic concepts in machine learning, their implementations, as well as the... View Details
- 23 May 2023
- Research & Ideas
Face Value: Do Certain Physical Features Help People Get Ahead?
empirically predicted with a machine learning model, suggests work by Shunyuan Zhang, an assistant professor at Harvard Business School, and collaborators. “Our research represents the first empirical... View Details
Keywords: by Kara Baskin
- 12 Apr 2022
- Research & Ideas
Swiping Right: How Data Helped This Online Dating Site Make More Matches
some estimates, with players such as Bumble, Tinder, and OKCupid vying to help people find love. While McFowland is not a dating expert, his work in machine learning and social sciences examines the efficacy... View Details
Keywords: by Kara Baskin
- November 2024 (Revised January 2025)
- Case
MiDAS: Automating Unemployment Benefits
By: Shikhar Ghosh and Shweta Bagai
In 2015, the state of Michigan considered whether to nominate its Michigan Integrated Data Automated System (MiDAS) for a prestigious state technology award. Launched in 2013 amid severe budget pressures, the $47 million automated fraud detection system was designed to... View Details
Keywords: Artificial Intelligence; AI; Machine Learning Models; Algorithmic Data; Decision Making; Automation; Benefits; Compensation; Cost Reduction; Digital Transformation; Employment; Government; Fraud; Government Technology; Public Sector; Systems; Systems Integration; Unemployment Insurance; Waste Heat Recovery; AI and Machine Learning; Government Administration; Information Technology; Insurance; United States
- 11 Feb 2020
- Sharpening Your Skills
10 Rules Entrepreneurs Need to Know Before Adopting AI
Although adoption of artificial intelligence (AI) and machine learning (ML) for the enterprise is still in the early days, the technology has matured enough for entrepreneurs to start gathering inspiration... View Details
Keywords: by Rocio Wu
- 11 Apr 2023
- Research & Ideas
Is Amazon a Retailer, a Tech Firm, or a Media Company? How AI Can Help Investors Decide
industry lines as companies increasingly bring seemingly unrelated business lines together in unconventional ways. New research by Awada, Harvard Business School Professor Suraj Srinivasan, and doctoral student Paul J. Hamilton harnesses View Details
- 26 Jul 2022
- Research & Ideas
Burgers with Bugs? What Happens When Restaurants Ignore Online Reviews
reviews helps consumers choose cleaner restaurants, which is a pretty robust finding." Harvard Business School Assistant Professor Chiara Farronato and Georgios Zervas, an associate professor at Boston University, used machine View Details
- February 2018
- Case
Amazon, Google, and Apple: Smart Speakers and the Battle for the Connected Home
By: Rajiv Lal and Scott Johnson
Amazon, Google, and Apple all offer their own smart speaker. The devices represent each firm's entry point into the connected home market. All three companies come into the space with their own strengths and weaknesses. Who will win? View Details
Keywords: Apple; Apple Inc.; Google; Amazon; Amazon.com; Google Home; Homepod; Echo; Smart Home; Connected Home; Voice; Artificial Intelligence; Machine Learning; Internet Of Things; Smart Speaker; Connected Speaker; Intelligent Assistants; Virtual Assistants; Voice Assistants; Alexa; Google Assistant; Siri; Technological Innovation; Disruptive Innovation; Competitive Strategy; Business Strategy; Adoption; Information Infrastructure; Information Technology; Internet and the Web; Mobile and Wireless Technology; Applications and Software; Technology Adoption; Digital Platforms; Household; AI and Machine Learning; Electronics Industry; Technology Industry; United States
Lal, Rajiv, and Scott Johnson. "Amazon, Google, and Apple: Smart Speakers and the Battle for the Connected Home." Harvard Business School Case 518-035, February 2018.
- Article
The Pitfalls of Pricing Algorithms: Be Mindful of How They Can Hurt Your Brand
By: Marco Bertini and Oded Koenigsberg
More and more companies are relying on pricing algorithms to maximize profits. The use of artificial intelligence and machine learning enables real-time price adjustments based on supply and demand, competitors’ activities, delivery schedules, and so forth. But... View Details
Keywords: Algorithmic Pricing; Dynamic Pricing; Price; Change; Information Technology; Brands and Branding; Perception; Consumer Behavior
Bertini, Marco, and Oded Koenigsberg. "The Pitfalls of Pricing Algorithms: Be Mindful of How They Can Hurt Your Brand." Harvard Business Review 99, no. 5 (September–October 2021): 74–83.
- 05 Oct 2015
- Working Paper Summaries
Online Network Revenue Management Using Thompson Sampling
- 16 Oct 2019
- Research & Ideas
Read Our Most Popular Stories of the Quarter
What stories were readers like you diving into this summer on HBS Working Knowledge? Your interests varied dramatically, everything from how researchers use machine learning technology to predict CEO... View Details
Keywords: by Sean Silverthorne
- 12 May 2022
- Book
Why Digital Is a State of Mind, Not Just a Skill Set
Keywords: by Sean Silverthorne
- December 1984
- Case
Expense Tracking System at Tiger Creek
By: Shoshana Zuboff
Mill manager Carl Adelman learns that a group of senior managers is soon to visit the Tiger Creek mill to learn more about the success of the newly implemented Expense Tracking System. The System had been installed on two paper machines to give workers real time cost... View Details
Zuboff, Shoshana. "Expense Tracking System at Tiger Creek." Harvard Business School Case 485-057, December 1984.
- Teaching Interest
Overview
Paul is primarily interested in teaching data science to management students through the case method. This includes technical topics (programming and statistics) as well as higher-level management issues (digital transformation, data governance, etc.) As a research... View Details
Keywords: A/B Testing; AI; AI Algorithms; AI Creativity; Algorithm; Algorithm Bias; Algorithmic Bias; Algorithmic Fairness; Algorithms; Analytics; Application Program Interface; Artificial Intelligence; Causality; Causal Inference; Computing; Computers; Data Analysis; Data Analytics; Data Architecture; Data As A Service; Data Centers; Data Governance; Data Labeling; Data Management; Data Manipulation; Data Mining; Data Ownership; Data Privacy; Data Protection; Data Science; Data Science And Analytics Management; Data Scientists; Data Security; Data Sharing; Data Strategy; Data Visualization; Database; Data-driven Decision-making; Data-driven Management; Data-driven Operations; Datathon; Economics Of AI; Economics Of Innovation; Economics Of Information System; Economics Of Science; Forecast; Forecast Accuracy; Forecasting; Forecasting And Prediction; Information Technology; Machine Learning; Machine Learning Models; Prediction; Prediction Error; Predictive Analytics; Predictive Models; Analysis; AI and Machine Learning; Analytics and Data Science; Applications and Software; Digital Transformation; Information Management; Digital Strategy; Technology Adoption
- Research Summary
Understanding the Limitations of Model Explanations
The goal of this research is to understand how adversaries can exploit various algorithms used for explaining complex machine learning models with an intention to mislead end users. For instance, can adversaries trick these algorithms into masking their racial and... View Details