Filter Results
:
(245)
Show Results For
-
All HBS Web
(1,152)
- Faculty Publications (245)
Show Results For
-
All HBS Web
(1,152)
- Faculty Publications (245)
Ai →
Page 1 of
245
Results
→
- March 2024
- Exercise
"Storrowed": A Generative AI Exercise
By: Mitchell Weiss
"Storrowed" is an exercise to help participants raise their capacity and curiosity for generative AI. It focuses on generative AI for problem understanding and ideation, but can be adapted for use more broadly. Participants use generative AI tools to understand a...
View Details
Keywords:
AI and Machine Learning
- March 2024
- Teaching Note
CoPilot(s): Generative AI at Microsoft and GitHub
By: Frank Nagle and Maria P. Roche
This teaching note is the companion to case N9-624-010 CoPilot(s): Generative AI at Microsoft and GitHub, which takes place in late 2021. The case briefly describes the history of both GitHub and Microsoft with a particular focus on open source software (OSS) –...
View Details
- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I. Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the...
View Details
Liang, Biyonka, and Iavor I. Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
- March 2024
- Case
Governing OpenAI
By: Lynn S. Paine, Suraj Srinivasan and Will Hurwitz
In late November 2023, OpenAI’s new board of directors took stock of the situation. The company, which sought to develop artificial general intelligence (AGI)—computer systems with capabilities exceeding human abilities—was looking to regain its footing after a chaotic...
View Details
Keywords:
Artificial Intelligence;
Board Of Directors;
Board Decisions;
Board Dynamics;
Business Ethics;
Corporate Boards;
Governance Changes;
Governance Structure;
Leadership Change;
Legal Aspects Of Business;
Nonprofit;
Nonprofit Governance;
Open Source;
Partnerships;
Regulation;
Strategy And Execution;
Technological Change;
AI and Machine Learning;
Corporate Governance;
Leadership;
Management;
Mission and Purpose;
Technological Innovation;
Technology Industry;
San Francisco;
United States
- February 26, 2024
- Article
Making Workplaces Safer Through Machine Learning
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
Machine learning algorithms can dramatically improve regulatory effectiveness. This short article describes the authors' scholarly work that shows how the U.S. Occupational Safety and Health Administration (OSHA) could have reduced nearly twice as many occupational...
View Details
Keywords:
Government Experimentation;
Auditing;
Inspection;
Evaluation;
Process Improvement;
Government Administration;
AI and Machine Learning;
Safety;
Governing Rules, Regulations, and Reforms
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Making Workplaces Safer Through Machine Learning." Regulatory Review (February 26, 2024).
- February 2024
- Case
Taffi: Entrepreneurship in Saudi Arabia
By: Paul A. Gompers and Fares Khrais
Taffi was a tech-enabled fashion styling startup founded by Shahad Geoffrey in Saudi Arabia in 2020. Within three years of operating, Geoferry had pivoted the business multiple times. In 2023, Geoferry was attempting the business’s most ambitious pivot yet, shifting...
View Details
- February 6, 2024
- Article
Find the AI Approach That Fits the Problem You’re Trying to Solve
By: George Westerman, Sam Ransbotham and Chiara Farronato
AI moves quickly, but organizations change much more slowly. What works in a lab may be wrong for your company right now. If you know the right questions to ask, you can make better decisions, regardless of how fast technology changes. You can work with your technical...
View Details
Westerman, George, Sam Ransbotham, and Chiara Farronato. "Find the AI Approach That Fits the Problem You’re Trying to Solve." Harvard Business Review Digital Articles (February 6, 2024).
- February 2024
- Case
Continuity & Change at Boston Consulting Group
By: David G. Fubini, Suraj Srinivasan and David Lane
As the new CEO of Boston Consulting Group (BCG) since autumn 2021, Christoph Schweizer had big shoes to fill—his predecessor, Rich Lesser, had tripled the partnership’s total revenues and created digital initiatives that contributed 40+% of 2021 revenues, more than...
View Details
Keywords:
Business Growth and Maturation;
Business Organization;
Change Management;
Talent and Talent Management;
Governance;
AI and Machine Learning;
Environmental Sustainability;
Leading Change;
Risk Management;
Organizational Culture;
Organizational Design;
Partners and Partnerships;
Consulting Industry
Fubini, David G., Suraj Srinivasan, and David Lane. "Continuity & Change at Boston Consulting Group." Harvard Business School Case 124-011, February 2024.
- February 2024
- Case
ReSpo.Vision: The Kickstart of an AI Sports Revolution
By: Paul A. Gompers, Elena Corsi and Nikolina Jonsson
This case study explores the growth journey of Polish computer vision sports start-up ReSpo.Vision in an emerging entrepreneurial ecosystem. By providing 3D data and analysis to soccer clubs, ReSpo.Vision achieved significant milestones with a €1 million seed round, an...
View Details
Keywords:
Business Startups;
Business Plan;
Experience and Expertise;
Talent and Talent Management;
Decisions;
Decision Choices and Conditions;
Forecasting and Prediction;
Entrepreneurship;
Venture Capital;
AI and Machine Learning;
Analytics and Data Science;
Applications and Software;
Sports Industry;
Technology Industry;
Poland;
Europe
- February 2024
- 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 Ventures;
Business Growth and Maturation;
Business Model;
Business Startups;
Small Business;
Change;
Transformation;
Customers;
Customer Focus and Relationships;
Decision Making;
Decisions;
Entrepreneurship;
Finance;
Venture Capital;
Financial Strategy;
Information Technology;
AI and Machine Learning;
Digital Platforms;
Technological Innovation;
Intellectual Property;
Copyright;
Management;
Growth and Development;
Markets;
Market Timing;
Ownership;
Risk and Uncertainty;
Strategy;
Competition;
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.
- February 2024
- Technical Note
AI Product Development Lifecycle
By: Michael Parzen, Jessie Li and Marily Nika
In this article, we will discuss the concept of AI Products, how they are changing our daily lives, how the field of AI & Product Management is evolving, and the AI Product Development Lifecycle.
View Details
Parzen, Michael, Jessie Li, and Marily Nika. "AI Product Development Lifecycle." Harvard Business School Technical Note 624-070, February 2024.
- Working Paper
Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application
By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely...
View Details
Keywords:
Peer-to-peer Markets;
Marketplace Matching;
AI and Machine Learning;
Demand and Consumers;
Digital Platforms;
Marketing
Feng, Flora, Charis Li, and Shunyuan Zhang. "Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application." SSRN Working Paper Series, No. 4665286, February 2024.
- 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
- January 2024
- Background Note
Note on Generative AI for Business Students
By: Andrew Rashbass, Ramon Casadesus-Masanell and Jordan Mitchell
- 2024
- Working Paper
Contributing to Growth? The Role of Open Source Software for Global Startups
By: Nataliya Langburd Wright, Frank Nagle and Shane Greenstein
Does participating in open source software (OSS) communities spur entrepreneurial growth? More
efficiently developing shared code, learning from what the OSS community has developed, and
shaping the direction of massive projects, such as those linked to frameworks...
View Details
Keywords:
Applications and Software;
Open Source Distribution;
Entrepreneurship;
Business Growth and Maturation;
Human Capital;
Valuation;
Corporate Strategy
Wright, Nataliya Langburd, Frank Nagle, and Shane Greenstein. "Contributing to Growth? The Role of Open Source Software for Global Startups." Harvard Business School Working Paper, No. 24-040, January 2024.
- January 2024
- Case
The Financial Times (FT) and Generative AI
By: Andrew Rashbass, Ramon Casadesus-Masanell and Jordan Mitchell
- January 2024 (Revised February 2024)
- Case
OpenAI: Idealism Meets Capitalism
By: Shikhar Ghosh and Shweta Bagai
In November 2023, the board of OpenAI, one of the most successful companies in the history of technology, decided to fire Sam Altman, its charismatic and influential CEO. Their decision shocked the corporate world and had people wondering why OpenAI had designed a...
View Details
Ghosh, Shikhar, and Shweta Bagai. "OpenAI: Idealism Meets Capitalism." Harvard Business School Case 824-134, January 2024. (Revised February 2024.)
- January 2024 (Revised February 2024)
- Case
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
The case examines Levi Strauss’ journey in implementing machine learning and AI into its financial forecasting process. The apparel company partnered with the IT company Wipro in 2017 to develop a machine learning algorithm that could help Levi Strauss forecast its...
View Details
Keywords:
Investor Relations;
Forecasting;
Machine Learning;
Artificial Intelligence;
Apparel;
Corporate Finance;
Forecasting and Prediction;
AI and Machine Learning;
Apparel and Accessories Industry;
United States
Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Case 224-029, January 2024. (Revised February 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.
- December 2023 (Revised February 2024)
- Case
Generative AI and the Future of Work
By: Christopher Stanton and Matt Higgins
Generative AI seemed poised to reshape the world of work, including the higher-wage, white-collar jobs typically pursued by MBA graduates. Informed by the latest research, this case explores generative AI's potential impacts on work, productivity, value creation, and...
View Details
Keywords:
AI;
Future Of Work;
Labor Market;
AI and Machine Learning;
Labor;
Technology Industry;
United States
Stanton, Christopher, and Matt Higgins. "Generative AI and the Future of Work." Harvard Business School Case 824-130, December 2023. (Revised February 2024.)