Filter Results
:
(1,035)
Show Results For
-
All HBS Web
(1,035)
- People (1)
- News (209)
- Research (557)
- Events (8)
- Multimedia (7)
- Faculty Publications (446)
Show Results For
-
All HBS Web
(1,035)
- People (1)
- News (209)
- Research (557)
- Events (8)
- Multimedia (7)
- Faculty Publications (446)
- 2020
- Working Paper
Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion
By: Ryan Allen and Prithwiraj Choudhury
Past research offers mixed perspectives on whether domain experience helps or hurts algorithm-augmented work performance. To reconcile these perspectives, we theorize that domain experience affects algorithm-augmented performance via two distinct countervailing...
View Details
Keywords:
Automation;
Domain Experience;
Algorithmic Aversion;
Experts;
Algorithms;
Machine Learning;
Decision-making;
Future Of Work;
Employees;
Experience and Expertise;
Decision Making;
Performance
Allen, Ryan, and Prithwiraj Choudhury. "Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion." Harvard Business School Working Paper, No. 21-073, October 2020. (Revised September 2021.)
- December 2020
- Case
VIA Science (A)
By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the...
View Details
Keywords:
Data Analytics;
Machine Learning;
Artificial Intelligence;
Strategy;
Business Startups;
Markets;
AI and Machine Learning;
Telecommunications Industry;
Utilities Industry;
United States;
Japan
Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (A)." Harvard Business School Case 721-367, December 2020.
- 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 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.
- Web
Lifelong Learning - Alumni
Administration Chair, MBA Elective Curriculum); By: Jennifer Gillespie 360 01 Jun 2024 HBS Alumni Bulletin Leveraging Generative AI HBS navigates the use of these transformative tools for teaching and View Details
- 2017
- Working Paper
The Need for Speed: Effects of Uncertainty Reduction in Patenting
By: Mike Horia Teodorescu
Patents are essential in commerce to establish property rights for ideas and to give equal protection to firms that develop new technologies. Young firms especially depend on the protection of intellectual property to bring a product from concept to market. However,...
View Details
- May 2022
- Supplement
Borusan CAT: Monetizing Prediction in the Age of AI (B)
By: Navid Mojir and Gamze Yucaoglu
Borusan Cat is an international distributor of Caterpillar heavy machines. In 2021, it had been three years since Ozgur Gunaydin (CEO) and Esra Durgun (Director of Strategy, Digitization, and Innovation) started working on Muneccim, the company’s predictive AI tool....
View Details
Keywords:
AI and Machine Learning;
Commercialization;
Technology Adoption;
Industrial Products Industry;
Turkey;
Middle East
Mojir, Navid, and Gamze Yucaoglu. "Borusan CAT: Monetizing Prediction in the Age of AI (B)." Harvard Business School Supplement 522-045, May 2022.
- 13 Nov 2019
- Research & Ideas
Don't Turn Your Marketing Function Over to AI Just Yet
Imagine a future in which a smart marketing machine can predict the needs and habits of individual consumers and the dynamics of competitors across industries and markets. This device would collect data to answer strategic questions, guide managerial decisions, and...
View Details
Keywords:
by Kristen Senz
- 20 Oct 2022 - 22 Oct 2022
- Talk
Stigma Against AI Companion Applications
By: Julian De Freitas, A. Ragnhildstveit and A.K. Uğuralp
- December 2023
- Case
Monsters in the Machine? Tackling the Challenge of Responsible AI
By: Paul M. Healy and Debora L. Spar
In November of 2022, the small tech company OpenAI released ChatGPT, an artificial intelligence chatbot which quickly captured the public’s imagination—becoming the world’s fastest-growing consumer application within months of its release. Though observers from across...
View Details
Keywords:
Technological Innovation;
AI and Machine Learning;
Ethics;
Governing Rules, Regulations, and Reforms;
Technology Adoption;
Corporate Social Responsibility and Impact;
Technology Industry;
United States;
European Union;
China
Healy, Paul M., and Debora L. Spar. "Monsters in the Machine? Tackling the Challenge of Responsible AI." Harvard Business School Case 324-062, December 2023.
- October 2015 (Revised October 2016)
- Case
Building Watson: Not So Elementary, My Dear! (Abridged)
By: Willy C. Shih
This case is set inside IBM Research's efforts to build a computer that can successfully take on human challengers playing the game show Jeopardy! It opens with the machine named Watson offering the incorrect answer "Toronto" to a seemingly simple question during the...
View Details
Keywords:
Analytics;
Big Data;
Business Analytics;
Product Development Strategy;
Machine Learning;
Machine Intelligence;
Artificial Intelligence;
Product Development;
AI and Machine Learning;
Information Technology;
Analytics and Data Science;
Information Technology Industry;
United States
Shih, Willy C. "Building Watson: Not So Elementary, My Dear! (Abridged)." Harvard Business School Case 616-025, October 2015. (Revised October 2016.)
- 15 Nov 2018
- News
Don’t Be Afraid of AI
Dubinsky: And we get example after example, I just used that one 'cause it's so visual, of ways in which there are things we cannot do today, or it's very dangerous for humans today, that if we had a machine...
View Details
- 2020
- Book
Work, Mate, Marry, Love: How Machines Shape Our Human Destiny
By: Debora L. Spar
Covering a time frame that ranges from 8000 BC to the present, and drawing upon both Marxist and feminist theories, the book argues that nearly all the decisions we make in our most intimate lives—whom to marry, how to have children, how to have sex, how to think about...
View Details
Keywords:
Innovation;
Family;
Women;
Reproduction;
Artificial Intelligence;
Robots;
Gender;
Demography;
History;
Innovation and Invention;
Relationships;
Society;
Information Technology;
AI and Machine Learning;
Biotechnology Industry;
Computer Industry;
Health Industry;
Information Technology Industry;
Manufacturing Industry;
Technology Industry;
Africa;
Asia;
Europe;
Latin America;
North and Central America
Spar, Debora L. Work, Mate, Marry, Love: How Machines Shape Our Human Destiny. New York: Farrar, Straus and Giroux, 2020.
- January 2018 (Revised February 2023)
- Teaching Note
The Future of Patent Examination at the USPTO
This teaching note pairs with the case entitled: “The Future of Patent Examination at the USPTO” (case no. 617-027).
View Details
- Web
Online AI Course | HBS Online
culture. Recognize how AI is transforming business across industries and geographies and why it’s vital to accelerate your AI journey now....
View Details
- September 2020 (Revised March 2022)
- Case
JOANN: Joannalytics Inventory Allocation Tool
By: Kris Ferreira and Srikanth Jagabathula
Michael Joyce, Vice President of Inventory Management at JOANN, championed an effort to develop and implement an inventory allocation analytics tool that used advanced analytics to predict in-season demand of seasonal items for each of JOANN’s nearly 900 stores and...
View Details
Keywords:
Analytics;
Machine Learning;
Optimization;
Inventory Management;
Mathematical Methods;
Decision Making;
Operations;
Supply Chain Management;
Resource Allocation;
Distribution;
Technology Adoption;
Applications and Software;
Change Management;
Fashion Industry;
Consumer Products Industry;
Retail Industry;
United States;
Ohio
Ferreira, Kris, and Srikanth Jagabathula. "JOANN: Joannalytics Inventory Allocation Tool." Harvard Business School Case 621-055, September 2020. (Revised March 2022.)
- Web
Marketing AI Guidelines | About
Using AI Less expensive than commissioning custom illustrations and data visualizations. Easier to learn and faster than standard image editing...
View Details
- 01 Jun 2024
- News
Competing in the Age of AI
Dorothy and Michael Hintze Professor of Business Administration. He views AI in the same way—a widely available invention that enables people to go farther and faster,...
View Details
Keywords:
April White
- November 2023
- Case
Riiid: Scaling AI Educational Services Globally
By: John Jong-Hyun Kim, Nancy Dai and Ruru Hoong
This article explores the definition and evolution of AI, its applications in education, and the role of AI, particularly in K-12 education. It discusses the founding of Riiid, an AI-driven educational technology company, and its journey in the education sector, with a...
View Details
Keywords:
AI and Machine Learning;
Economic Sectors;
Technological Innovation;
Education Industry;
South Korea;
Asia
Kim, John Jong-Hyun, Nancy Dai, and Ruru Hoong. "Riiid: Scaling AI Educational Services Globally." Harvard Business School Case 324-030, November 2023.
- 2021
- Chapter
Towards a Unified Framework for Fair and Stable Graph Representation Learning
By: Chirag Agarwal, Himabindu Lakkaraju and Marinka Zitnik
As the representations output by Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes important to ensure that these representations are fair and stable. In this work, we establish a key connection between counterfactual...
View Details
Agarwal, Chirag, Himabindu Lakkaraju, and Marinka Zitnik. "Towards a Unified Framework for Fair and Stable Graph Representation Learning." In Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence, edited by Cassio de Campos and Marloes H. Maathuis, 2114–2124. AUAI Press, 2021.