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- All HBS Web
(1,038)
- People (1)
- News (155)
- Research (664)
- Events (13)
- Multimedia (3)
- Faculty Publications (573)
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- 15 May 2017
- Sharpening Your Skills
The Promises and Limitations of Big Data
services firms are using digital information about their customers to offer them a whole new range of customized products under the category of fintech. Cities are using data from Google Street View to guide economic development. And companies are finding that in some... View Details
- May 2024
- Case
A New Aiera for Equity Research
By: Joseph Pacelli, Charles CY Wang and James Barnett
Aiera (pronounced “era”) co-founder and CEO Ken Sena considers strategic pathways to growth for the artificial intelligence (AI)-powered platform used to source, verify, and transcribe earnings calls, company presentations, and other corporate events. View Details
- 18 Jul 2019
- Lessons from the Classroom
The Internet of Things Needs a Business Model. Here It Is
'I’ll bring it down to 3 percent,' but without any proof, the customer will say, 'why don’t you try it out on someone else first,'” Lal says. For that reason, instead of just selling connected products to business customers, companies must View Details
- June 2023 (Revised July 2023)
- Case
Social Media Background Screening at Fama Technologies
By: Joseph Pacelli, Jillian Grennan and Alexis Lefort
Fama Technologies is an online screening company that uses AI to analyze job applicants' publicly available online content for signs of risk and culture fit. The case opens with Ben Mones, founder and CEO, looking to secure funding from venture firms. He is running... View Details
Keywords: Human Resources; Recruitment; Retention; Selection and Staffing; Organizational Culture; Talent and Talent Management; AI and Machine Learning; Social Media; Venture Capital; Entrepreneurship; United States
Pacelli, Joseph, Jillian Grennan, and Alexis Lefort. "Social Media Background Screening at Fama Technologies." Harvard Business School Case 123-010, June 2023. (Revised July 2023.)
- 28 Apr 2022
- Research & Ideas
Can You Buy Creativity in the Gig Economy?
gauged by monitoring nearly 1 million reader reviews using, in part, supervised machine learning in addition to searching for keywords such as “original,” “creative,” “surprisingly clever,” “innovative,” and... View Details
Keywords: by Pamela Reynolds
- February 2024 (Revised January 2025)
- Case
AGENTS.inc: Pathways to Growth at an AI Startup
By: Frank Nagle, Manuel Hoffmann, Karoline Ströhlein and Susan Pinckney
The case describes the history of AGENTS.inc. Despite being a small startup, with only four employees, that had never had a funding round, the company boasted an impressive client portfolio including multiple Fortune 500 companies. While AGENTS.inc had been an early... View Details
Keywords: Business Growth and Maturation; Business Model; Business Startups; Small Business; Transformation; Customer Focus and Relationships; Decisions; Entrepreneurship; Venture Capital; Financial Strategy; AI and Machine Learning; Digital Platforms; Technological Innovation; Copyright; Management; Growth and Development; Market Timing; Ownership; Risk and Uncertainty; Competition; Open Source Distribution; Entrepreneurial Finance; Computer Industry; Europe; Germany
Nagle, Frank, Manuel Hoffmann, Karoline Ströhlein, and Susan Pinckney. "AGENTS.inc: Pathways to Growth at an AI Startup." Harvard Business School Case 724-444, February 2024. (Revised January 2025.)
- January 2017 (Revised March 2017)
- Case
IBM Transforming, 2012–2016: Ginni Rometty Steers Watson
By: Rosabeth Moss Kanter and Jonathan Cohen
To transform IBM for the next technology wave, Ginni Rometty, who became CEO in 2012, led divestment of declining businesses, made acquisitions in digital innovation and cloud computing, formed partnerships with former competitors such as Apple and tech startups, and... View Details
Keywords: Digital; Technological Change; Artificial Intelligence; Data; IBM; Watson; Internet Of Things; Innovation and Invention; Management; Sales; Information Technology; Technological Innovation; Transformation; AI and Machine Learning
Kanter, Rosabeth Moss, and Jonathan Cohen. "IBM Transforming, 2012–2016: Ginni Rometty Steers Watson." Harvard Business School Case 317-046, January 2017. (Revised March 2017.)
- October 2021 (Revised June 2022)
- Case
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli
PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once... View Details
Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; AI; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
Israeli, Ayelet. "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion." Harvard Business School Case 522-046, October 2021. (Revised June 2022.)
- November 2023
- Case
Copilot(s): Generative AI at Microsoft and GitHub
By: Frank Nagle, Shane Greenstein, Maria P. Roche, Nataliya Langburd Wright and Sarah Mehta
This case tells the story of Microsoft’s 2018 acquisition of GitHub and the subsequent launch of GitHub Copilot, a tool that uses generative artificial intelligence to suggest snippets of code to software developers in real time. Set in late 2021, when Copilot was... View Details
Keywords: Business Ventures; Strategy; AI and Machine Learning; Applications and Software; Product Launch; Information Technology Industry; Technology Industry; Web Services Industry; United States; California
Nagle, Frank, Shane Greenstein, Maria P. Roche, Nataliya Langburd Wright, and Sarah Mehta. "Copilot(s): Generative AI at Microsoft and GitHub." Harvard Business School Case 624-010, November 2023.
- October 2019
- Case
Leading Bank Leumi into the Future
By: Joshua D. Margolis, Allison M. Ciechanover, Nicole Keller and Danielle Golan
An unlikely but highly effective leader of a traditional bank, Rakefet Russak-Aminoach, simultaneously leads a classic change effort and an unconventional effort to innovate. She focuses her initial energy on making the bank more efficient in the face of industry... View Details
Keywords: Mobile Banking; Digital Banking; Fintech; Startup; Financial Services; Artificial Intelligence; Innovation; Efficiency; Organizational Change; Personal Development; Female Ceo; Banks and Banking; Mobile and Wireless Technology; Leadership; Organizational Change and Adaptation; Innovation and Invention; Disruption; Information Technology; Opportunities; Performance Effectiveness; Personal Development and Career; AI and Machine Learning; Financial Services Industry; Banking Industry; Israel
Margolis, Joshua D., Allison M. Ciechanover, Nicole Keller, and Danielle Golan. "Leading Bank Leumi into the Future." Harvard Business School Case 420-063, October 2019.
- Research Summary
Overview
Engaged with field work in East Africa, South Asia, and in several large hybrid organizations in the United States, Professor Whillans places a focus on exploring questions with strong theoretical motivation in the social psychological literature and relevant... View Details
- 25 May 2021
- Research & Ideas
White Airbnb Hosts Earn More. Can AI Shrink the Racial Gap?
Airbnb began offering a free tool to help all hosts set reasonable rates. The real-time, “smart pricing” program uses machine learning to automatically adjust the property’s nightly fees by considering a... View Details
- January 2024 (Revised January 2025)
- Case
Huawei: Resilience amid Autarky and Adversity
By: William C. Kirby and Daniel Fu
In September 2023, Huawei made a dramatic return to the global smartphone space with the launch of its Mate 60 Pro smartphone, equipped with an indigenously designed, 7nm chip. This came despite a myriad of export controls and restrictions imposed against the company... View Details
Keywords: International Strategy; Semiconductors; Smartphone; Government And Politics; Government And Business; Digital Infrastructure; 5G; Political Risk; Business and Government Relations; Global Strategy; Multinational Firms and Management; Governing Rules, Regulations, and Reforms; AI and Machine Learning; Mobile and Wireless Technology; Leadership; Retirement; Corporate Strategy; Technology Industry; China; United States; Europe; Asia; Middle East
- October 2024
- Technical Note
Prompt Engineering
By: Michael Parzen and Jo Ellery
This note covers the basics of prompt engineering, a key tool for making use of modern generative AI. We discuss the principles of prompt engineering and illustrate these principles with techniques for asking questions. We further list the types of prompts that can be... View Details
Parzen, Michael, and Jo Ellery. "Prompt Engineering." Harvard Business School Technical Note 625-056, October 2024.
- 2024
- Conference Paper
Quantifying Uncertainty in Natural Language Explanations of Large Language Models
By: Himabindu Lakkaraju, Sree Harsha Tanneru and Chirag Agarwal
Large Language Models (LLMs) are increasingly used as powerful tools for several
high-stakes natural language processing (NLP) applications. Recent prompting
works claim to elicit intermediate reasoning steps and key tokens that serve as
proxy explanations for LLM... View Details
Lakkaraju, Himabindu, Sree Harsha Tanneru, and Chirag Agarwal. "Quantifying Uncertainty in Natural Language Explanations of Large Language Models." Paper presented at the Society for Artificial Intelligence and Statistics, 2024.
- 2022
- Article
Efficiently Training Low-Curvature Neural Networks
By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret
Standard deep neural networks often have excess non-linearity, making them susceptible to issues such as low adversarial robustness and gradient instability. Common methods to address these downstream issues, such as adversarial training, are expensive and often... View Details
Keywords: AI and Machine Learning
Srinivas, Suraj, Kyle Matoba, Himabindu Lakkaraju, and Francois Fleuret. "Efficiently Training Low-Curvature Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) (2022).
- April 2023
- Article
On the Privacy Risks of Algorithmic Recourse
By: Martin Pawelczyk, Himabindu Lakkaraju and Seth Neel
As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely beneficial to affected... View Details
Pawelczyk, Martin, Himabindu Lakkaraju, and Seth Neel. "On the Privacy Risks of Algorithmic Recourse." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 206 (April 2023).
- 2023
- Article
MoPe: Model Perturbation-based Privacy Attacks on Language Models
By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training... View Details
Li, Marvin, Jason Wang, Jeffrey Wang, and Seth Neel. "MoPe: Model Perturbation-based Privacy Attacks on Language Models." Proceedings of the Conference on Empirical Methods in Natural Language Processing (2023): 13647–13660.
- 2023
- Article
Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details
Srinivas, Suraj, Sebastian Bordt, and Himabindu Lakkaraju. "Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 8 Sep 2023
- Conference Presentation
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, K. Uguralp, Z. Uguralp and Stefano Puntoni
De Freitas, Julian, K. Uguralp, Z. Uguralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Paper presented at the Business & Generative AI Workshop, Wharton School, AI at Wharton, San Francisco, CA, United States, September 8, 2023.