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Show Results For
- All HBS Web
(973)
- People (1)
- News (156)
- Research (648)
- Events (13)
- Multimedia (3)
- Faculty Publications (552)
- July 2024
- Technical Note
What Is AI?
By: Michael Parzen and Jo Ellery
This note discusses definitions of artificial intelligence and covers the broad types of learning used in training AI, as well as explaining in detail how neural networks are built, trained, and used. View Details
Keywords: AI and Machine Learning
Parzen, Michael, and Jo Ellery. "What Is AI?" Harvard Business School Technical Note 625-010, July 2024.
- 15 Oct 2001
- Op-Ed
Lessons from the Rubble
Pundits and investors spoke giddily of the end of national borders, of markets that spanned the globe and replaced the hefty weight of machines and plants with ephemeral bits of information. This may be true. We do have global markets and... View Details
Keywords: by Debora L. Spar
- 2024
- Working Paper
Igniting Innovation: Evidence from PyTorch on Technology Control in Open Collaboration
By: Daniel Yue and Frank Nagle
Many companies offer free access to their technology to encourage outside addon
innovation, hoping to later profit by raising prices or harnessing the power of the crowd
while continuing to steer the direction of innovation. They can achieve this balance by
opening... View Details
Keywords: Technological Innovation; Power and Influence; Collaborative Innovation and Invention; Corporate Governance
Yue, Daniel, and Frank Nagle. "Igniting Innovation: Evidence from PyTorch on Technology Control in Open Collaboration." Harvard Business School Working Paper, No. 25-013, September 2024.
Work‐from‐anywhere: The productivity effects of geographic flexibility
An emerging form of remote work allows employees to work‐from‐anywhere, so that the worker can choose to live in a preferred geographic location. While traditional work‐from‐home (WFH) programs offer the worker temporal flexibility,... View Details
- August 2017 (Revised July 2019)
- Case
GROW: Using Artificial Intelligence to Screen Human Intelligence
By: Ethan Bernstein, Paul McKinnon and Paul Yarabe
Over 10% of all 2017 university graduates in Japan used GROW, an artificial intelligence platform and mobile app developed by Tokyo-based people analytics startup IGS, to recruit for a job. This case puts participants in the shoes of IGS founder and CEO Masahiro... View Details
Keywords: Big Data; Artificial Intelligence; Talent and Talent Management; Recruitment; Selection and Staffing; Human Resources; Information Technology; AI and Machine Learning; Analytics and Data Science; Financial Services Industry; Air Transportation Industry; Advertising Industry; Manufacturing Industry; Technology Industry; Japan
Bernstein, Ethan, Paul McKinnon, and Paul Yarabe. "GROW: Using Artificial Intelligence to Screen Human Intelligence." Harvard Business School Case 418-020, August 2017. (Revised July 2019.)
- 2021
- Article
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation
By: Chuang Gan, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin Feigelis, Daniel M. Bear, Dan Gutfreund, David Cox, Antonio Torralba, James J. DiCarlo, Joshua B. Tenenbaum, Josh H. McDermott and Daniel L.K. Yamins
We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation. TDW enables simulation of high-fidelity sensory data and physical interactions between mobile agents and objects in rich 3D environments. Unique properties include: real-time... View Details
Keywords: Artificial Intelligence; Platform; Interactive Physical Simulation; Virtual Environment; Multi-modal; AI and Machine Learning
Gan, Chuang, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin Feigelis, Daniel M. Bear, Dan Gutfreund, David Cox, Antonio Torralba, James J. DiCarlo, Joshua B. Tenenbaum, Josh H. McDermott, and Daniel L.K. Yamins. "ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 35th (2021).
- 2023
- Other Article
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications
By: Mirac Suzgun, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers and Stuart Shieber
Innovation is a major driver of economic and social development, and information about many kinds of innovation is embedded in semi-structured data from patents and patent applications. Though the impact and novelty of innovations expressed in patent data are difficult... View Details
Keywords: USPTO; Natural Language Processing; Classification; Summarization; Patent Novelty; Patent Trolls; Patent Enforceability; Patents; Innovation and Invention; Intellectual Property; AI and Machine Learning; Analytics and Data Science
Suzgun, Mirac, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers, and Stuart Shieber. "The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
- 2021
- Working Paper
An Empirical Study of Time Allotment and Delays in E-commerce Delivery
By: M. Balakrishnan, MoonSoo Choi and Natalie Epstein
Problem definition: We study how having more time allotted to deliver an order affects the speed of the delivery process. Furthermore, we seek to predict orders that are likely to be delayed early in the delivery process so that actions can be taken to avoid delays.... View Details
Keywords: Logistics; E-commerce; Mathematical Methods; AI and Machine Learning; Performance Productivity
Balakrishnan, M., MoonSoo Choi, and Natalie Epstein. "An Empirical Study of Time Allotment and Delays in E-commerce Delivery." Working Paper, December 2021.
- 2020
- Working Paper
Design in the Age of Artificial Intelligence
By: Roberto Verganti, Luca Vendraminelli and Marco Iansiti
Artificial Intelligence (AI) is affecting the scenario in which innovation takes place. What are the implications for our understanding of design? Is AI just another digital technology that, akin to many others, will not significantly question what we know about... View Details
Keywords: Artificial Intelligence; Design Thinking; Technological Innovation; Design; Change; Theory; AI and Machine Learning
Verganti, Roberto, Luca Vendraminelli, and Marco Iansiti. "Design in the Age of Artificial Intelligence." Harvard Business School Working Paper, No. 20-091, February 2020.
- September–October 2023
- Article
Reskilling in the Age of AI
In the coming decades, as the pace of technological change continues to increase, millions of workers may need to be not just upskilled but reskilled—a profoundly complex societal challenge that will sometimes require workers to both acquire new skills and... View Details
Keywords: Competency and Skills; AI and Machine Learning; Training; Adaptation; Employees; Digital Transformation
Tamayo, Jorge, Leila Doumi, Sagar Goel, Orsolya Kovács-Ondrejkovic, and Raffaella Sadun. "Reskilling in the Age of AI." Harvard Business Review 101, no. 5 (September–October 2023): 56–65.
Eliminating unintended bias in personalized policies using Bias Eliminating Adapted Trees (BEAT) - PNAS
An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those... View Details
- Program
Competing in the Age of AI—Virtual
will delve into diverse applications of AI, machine learning, predictive modeling, and data science; explore network effects and platform strategies; and learn how to build an AI factory that enables your... View Details
- 22 Oct 2007
- Research & Ideas
Bringing ‘Lean’ Principles to Service Industries
own." Unfortunately, lean's prevalence has led to some misconceptions. "Some people think lean means 'not fat,' as in laying people off," Upton says, noting that in their paper they propose that the difference in a lean operating system comes from how it... View Details
- 2020
- Book
Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World
By: Marco Iansiti and Karim R. Lakhani
In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very... View Details
Keywords: Artificial Intelligence; Technological Innovation; Change; Competition; Strategy; Leadership; Business Processes; Organizational Change and Adaptation; AI and Machine Learning
Iansiti, Marco, and Karim R. Lakhani. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Boston: Harvard Business Review Press, 2020.
- Winter 2016
- Article
Analytics for an Online Retailer: Demand Forecasting and Price Optimization
By: Kris J. Ferreira, Bin Hong Alex Lee and David Simchi-Levi
We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time... View Details
Ferreira, Kris J., Bin Hong Alex Lee, and David Simchi-Levi. "Analytics for an Online Retailer: Demand Forecasting and Price Optimization." Manufacturing & Service Operations Management 18, no. 1 (Winter 2016): 69–88.
- September 2023 (Revised April 2024)
- Case
Atomwise: Strategic Opportunities in AI for Pharma
By: Satish Tadikonda
Abraham Heifets and his co-founder, Izhar Wallach, had founded Atomwise to develop i) an AI engine to transform drug discovery by creating better medicines faster, and ii) a machine learning-based discovery engine that combined the power of convolutional neural... View Details
Keywords: Business Model; Business Startups; AI and Machine Learning; Science-Based Business; Technological Innovation; Biotechnology Industry; Pharmaceutical Industry
Tadikonda, Satish. "Atomwise: Strategic Opportunities in AI for Pharma." Harvard Business School Case 824-043, September 2023. (Revised April 2024.)
- 08 Mar 2011
- First Look
First Look: March 8
relocate to Japan and compete with other world-class international business schools. Purchase this case:http://cb.hbsp.harvard.edu/cb/product/811061-PDF-ENG The Wright Brothers and Their Flying Machines Tom Nicholas and David ChenHarvard... View Details
Keywords: Sean Silverthorne
- Article
Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)
By: Eva Ascarza and Ayelet Israeli
An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details
Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods
Ascarza, Eva, and Ayelet Israeli. "Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)." e2115126119. Proceedings of the National Academy of Sciences 119, no. 11 (March 8, 2022).
- Web
Publications - Faculty & Research
fail. Marketers must promote their AI products with potential failure in mind. To do that, they must first understand consumers’ unique attitudes toward AI. Marketers who... View Details Keywords: AI and Machine View Details
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.