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(963)
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Show Results For
- All HBS Web
(963)
- People (1)
- News (156)
- Research (645)
- Events (13)
- Multimedia (3)
- Faculty Publications (544)
- January 2019 (Revised October 2019)
- Case
Liulishuo: AI English Teacher
By: John J-H Kim and Shu Lin
Educators and entrepreneurs alike are excited about the potential for artificial intelligence (AI) and machine learning to change the way learning will look like in the future. There is a confluence of factors such as the availability of large sources of rich,... View Details
Keywords: AI; Artificial Intelligence; Education Technology; Information Technology; Education; Entrepreneurship; AI and Machine Learning; Education Industry; China
Kim, John J-H, and Shu Lin. "Liulishuo: AI English Teacher." Harvard Business School Case 319-090, January 2019. (Revised October 2019.)
- 19 Jan 2023
- Research & Ideas
What Makes Employees Trust (vs. Second-Guess) AI?
products were grouped in 241 “style-colors'' and sizes. When the allocators received a recommendation from an interpretable algorithm, they often overruled it based on their own intuition. But when the same allocators had a recommendation from a similarly accurate... View Details
Keywords: by Rachel Layne
- 19 Oct 2021
- HBS Seminar
Cynthia Rudin, Duke University
- 17 Jun 2021
- News
Too Few Women Get to Invent – That’s a Problem for Women’s Health
- 2022
- Working Paper
Rethinking Explainability as a Dialogue: A Practitioner's Perspective
By: Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan and Sameer Singh
As practitioners increasingly deploy machine learning models in critical domains such as healthcare, finance, and policy, it becomes vital to ensure that domain experts function effectively alongside these models. Explainability is one way to bridge the gap between... View Details
Keywords: Natural Language Conversations; AI and Machine Learning; Experience and Expertise; Interactive Communication; Business and Stakeholder Relations
Lakkaraju, Himabindu, Dylan Slack, Yuxin Chen, Chenhao Tan, and Sameer Singh. "Rethinking Explainability as a Dialogue: A Practitioner's Perspective." Working Paper, 2022.
- 08 Mar 2017
- HBS Seminar
Fernanda Viégas and Martin Wattenberg, Google
- 2023
- Article
Provable Detection of Propagating Sampling Bias in Prediction Models
By: Pavan Ravishankar, Qingyu Mo, Edward McFowland III and Daniel B. Neill
With an increased focus on incorporating fairness in machine learning models, it becomes imperative not only to assess and mitigate bias at each stage of the machine learning pipeline but also to understand the downstream impacts of bias across stages. Here we consider... View Details
Ravishankar, Pavan, Qingyu Mo, Edward McFowland III, and Daniel B. Neill. "Provable Detection of Propagating Sampling Bias in Prediction Models." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 8 (2023): 9562–9569. (Presented at the 37th AAAI Conference on Artificial Intelligence (2/7/23-2/14/23) in Washington, DC.)
- 20 Sep 2014
- News
Making Big Data Think Bigger
- June 2019
- Teaching Note
Zebra Medical Vision
By: Shane Greenstein and Sarah Gulick
Teaching note is meant to accompany Zebra Medical Vision case, which offers a look at a company’s decisions as a small startup competing with other startups and major technology companies. It also demonstrates the challenges faced by a machine learning company working... View Details
Himabindu Lakkaraju
Himabindu "Hima" Lakkaraju is an Assistant Professor of Business Administration at Harvard Business School. She is also a faculty affiliate in the Department of Computer Science at Harvard University, the Harvard Data Science Initiative, Center for Research on... View Details
- March–April 2023
- Article
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in... View Details
Keywords: Price; Demand and Consumers; AI and Machine Learning; Investment Return; Entertainment and Recreation Industry; Sports Industry
Alley, Michael, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li, and Georgia Perakis. "Pricing for Heterogeneous Products: Analytics for Ticket Reselling." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 409–426.
- 05 Jul 2023
- Cold Call Podcast
How Unilever Is Preparing for the Future of Work
Siyu Zhang
Siyu Zhang is a second-year doctoral student at HBS. Zhang joined Harvard Business School in 2020 as a Research Associate and has been working on macroeconomic forecasting projects. Prior to joining HBS, he was a Data Scientist at John Hancock, where he utilized... View Details
- July 2016
- Case
Spotify
By: Anita Elberse and Alexandre de Pfyffer
In November 2014, Spotify's chief content officer Ken Parks learns that record label Big Machine Records has requested the immediate removal of superstar artist Taylor Swift's entire catalogue from Spotify's music streaming service. Is it time for Spotify to reconsider... View Details
Keywords: Entertainment; Marketing; Superstar; Music; Entertainment Marketing; Media; Digital Technology; Creative Industries; Product Portfolio Management; General Management; Management; Strategy; Internet and the Web; Open Source Distribution; Creativity; Music Entertainment; Product Marketing; Music Industry
Elberse, Anita, and Alexandre de Pfyffer. "Spotify." Harvard Business School Case 516-046, July 2016.
Eva Ascarza
Eva Ascarza is the Jakurski Family Associate Professor of Business Administration in the Marketing Unit. She is the co-founder of the Customer Intelligence Lab at the D^3 institute at Harvard Business School. She teaches the Marketing core in the MBA required... View Details
- 2023
- Working Paper
Translating Information into Action: A Public Health Experiment in Bangladesh
By: Reshmaan Hussam, Kailash Pandey, Abu Shonchoy and Chikako Yamauchi
While models of technology adoption posit learning as the basis of behavior change, information campaigns in public health frequently fail to change behavior. We design an information campaign embedding hand-hygiene edutainment within popular dramas using mobile... View Details
Hussam, Reshmaan, Kailash Pandey, Abu Shonchoy, and Chikako Yamauchi. "Translating Information into Action: A Public Health Experiment in Bangladesh." Working Paper, February 2023.
- 2023
- Working Paper
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
By: Daniel Yue, Paul Hamilton and Iavor Bojinov
Predictive model development is understudied despite its centrality in modern artificial
intelligence and machine learning business applications. Although prior discussions
highlight advances in methods (along the dimensions of data, computing power, and
algorithms)... View Details
Keywords: Analytics and Data Science
Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. (Revised April 2023.)
- 10 Sep 2020
- Blog Post
Founding a Company at the Intersection of Medicine and Technology
surgical robotics to treat lung cancer, the intersection of medicine and technology was a deep interest of his prior to HBS. He is now the Founder and CEO of Alife Health, which uses machine learning to help... View Details