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Show Results For
-
All HBS Web
(11,757)
- People (75)
- News (2,846)
- Research (3,653)
- Events (31)
- Multimedia (331)
- Faculty Publications (2,321)
- 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,...
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- April 2017
- Case
The Future of Patent Examination at the USPTO
By: Prithwiraj Choudhury, Tarun Khanna and Sarah Mehta
The U.S. Patent and Trademark Office (USPTO) is the federal government agency responsible for evaluating and granting patents and trademarks. In 2015, the USPTO employed approximately 8,000 patent examiners who granted nearly 300,000 patents to inventors. As of April...
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Keywords:
Machine Learning;
Telework;
Collaborating With Unions;
Human Resources;
Recruitment;
Retention;
Intellectual Property;
Copyright;
Patents;
Trademarks;
Knowledge Sharing;
Technology Adoption;
Organizational Change and Adaptation;
Performance Productivity;
Performance Improvement;
District of Columbia
Choudhury, Prithwiraj, Tarun Khanna, and Sarah Mehta. "The Future of Patent Examination at the USPTO." Harvard Business School Case 617-027, April 2017.
- 2021
- Working Paper
Time and the Value of Data
By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details
Keywords:
Economics Of AI;
Machine Learning;
Non-stationarity;
Perishability;
Value Depreciation;
Analytics and Data Science;
Value
Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)
- Working Paper
Diversification as an Adaptive Learning Process: An Empirical Study of General-Purpose and Market-Specific Technological Know-How in New Market Entry
By: Dominika Kinga Randle and Gary P. Pisano
An enduring trait of modern corporations is their propensity to diversify into multiple lines of business. Penrosian theories conceptualize diversification as a strategy to exploit a firm’s fungible, yet “untradeable,” resources and point to redeployment of...
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Keywords:
Growth and Development Strategy;
Technology Adoption;
Diversification;
Market Entry and Exit;
Transformation
Randle, Dominika Kinga, and Gary P. Pisano. "Diversification as an Adaptive Learning Process: An Empirical Study of General-Purpose and Market-Specific Technological Know-How in New Market Entry." Harvard Business School Working Paper, No. 23-032, December 2022.
- Article
Repositioning and Cost-Cutting: The Impact of Competition on Platform Strategies
By: Robert Seamans and Feng Zhu
Organizational structures are increasingly complex. In particular, more firms today operate as multi-sided platforms. In this paper, we study how platform firms use repositioning and cost-cutting in response to competition, elucidate external and internal factors that...
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Keywords:
Platform Strategy;
Repositioning;
Cost-cutting;
Intra-firm Learning;
Multi-Sided Platforms;
Cost Management;
Product Positioning;
Organizational Structure;
Competitive Strategy;
Knowledge Acquisition;
Journalism and News Industry
Seamans, Robert, and Feng Zhu. "Repositioning and Cost-Cutting: The Impact of Competition on Platform Strategies." Strategy Science 2, no. 2 (June 2017): 83–99.
- Research Summary
Paper - Commodity Chains: what can we learn from a business history of the rubber chain? (1870-1910)
The literature on the rubber boom applied a Marxist/Dependendist view of rubber production in the Brazilian Amazon. Even though a sizeable surplus was generated in the rubber chain, it was mostly appropriated by foreigners. This view is in tune with the Global... View Details
- 2022
- Article
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.
By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a...
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Keywords:
Machine Learning Models;
Counterfactual Explanations;
Adversarial Examples;
Mathematical Methods
Pawelczyk, Martin, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, and Himabindu Lakkaraju. "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
- Article
Counterfactual Explanations Can Be Manipulated
By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh
Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate...
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Slack, Dylan, Sophie Hilgard, Himabindu Lakkaraju, and Sameer Singh. "Counterfactual Explanations Can Be Manipulated." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- Research Summary
Overview
I develop machine learning tools and techniques which enable human decision makers to make better decisions. More specifically, my research addresses the following fundamental questions pertaining to human and algorithmic decision-making:
1. How to build... View Details
1. How to build... View Details
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving...
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Keywords:
Autoencoder Networks;
Pattern Detection;
Subset Scanning;
Computer Vision;
Statistical Methods And Machine Learning;
Machine Learning;
Deep Learning;
Data Mining;
Big Data;
Large-scale Systems;
Mathematical Methods;
Analytics and Data Science
Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
- 2002
- Casebook
General Management: Processes and Action: Text and Cases
By: David A. Garvin
Keywords:
General Management;
Learning Organizations;
Implementation;
Management;
Cases;
Strategic Planning;
Decision Making;
Change Management;
Leadership Style;
Organizational Culture
Garvin, David A. General Management: Processes and Action: Text and Cases. Boston: McGraw-Hill, 2002.
- September 10, 2020
- Editorial
Today's Awkward Zoom Classes Could Bring a New Era of Higher Education
By: D. L. Spar
Spar, D. L. "Today's Awkward Zoom Classes Could Bring a New Era of Higher Education." EdSurge (September 10, 2020).
- 2000
- Chapter
Learning New Technical and Interpersonal Routines in Operating Room Teams: The Case of Minimally Invasive Cardiac Surgery
By: Amy C. Edmondson, Richard Bohmer and Gary Pisano
Keywords:
Groups and Teams;
Health Care and Treatment;
Practice;
Competency and Skills;
Training;
Health Industry
Edmondson, Amy C., Richard Bohmer, and Gary Pisano. "Learning New Technical and Interpersonal Routines in Operating Room Teams: The Case of Minimally Invasive Cardiac Surgery." In Research on Managing Groups and Teams: Technology. Vol. 3, edited by B. Mannix, M. Neale, and T. Grifith, 29–51. Stamford: JAI Press, 2000.
- 1999
- Working Paper
Learning New Technical and Interpersonal Routines in Operating Room Teams: The Case of Minimally Invasive Cardiac Surgery
By: Amy C. Edmondson, Richard M.J. Bohmer and Gary Pisano
- 29 Sep 2020
Life at HBS Chat Series: MBA Students in Tech Club and Coding, Analytics, and Machine Learning Club
Hear straight from current HBS students regarding their MBA experience. Students will share their backgrounds and how they have cultivated their personal and professional interests while at HBS.
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- 01 Dec 2013
- News
Recognizing Potential
as cochair. Stevens, managing director of S-Cubed Capital and a former managing partner at Sequoia Capital, has invested in Internet companies for nearly two decades, but it was his own encounter with distance learning 30 years ago that...
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- 2013
- Article
The Strategic Fitness Process: A Collaborative Action Research Method for Developing Organizational Prototypes and Dynamic Capabilities
By: Michael Beer
Organizations underperform and sometimes fail because their leaders are unable to learn the unvarnished truth from relevant stakeholders about how the design and behavior of the organization is misaligned with its goals and strategy. The Strategic Fitness Process (SFP)...
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Keywords:
Organization Alignment;
Dynamic Capabilities;
Organization Design;
Organizational Prototyping;
Organizational Silence;
Organizational Learning;
Organizational Change and Adaptation;
Strategic Planning;
Organizational Design
Beer, Michael. "The Strategic Fitness Process: A Collaborative Action Research Method for Developing Organizational Prototypes and Dynamic Capabilities." Journal of Organization Design 2, no. 1 (2013).
- Article
Towards Robust and Reliable Algorithmic Recourse
By: Sohini Upadhyay, Shalmali Joshi and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision making (e.g., loan
approvals), there has been growing interest in post-hoc techniques which provide recourse to affected
individuals. These techniques generate recourses under the assumption...
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Keywords:
Machine Learning Models;
Algorithmic Recourse;
Decision Making;
Forecasting and Prediction
Upadhyay, Sohini, Shalmali Joshi, and Himabindu Lakkaraju. "Towards Robust and Reliable Algorithmic Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 16 Oct 2002
- Keynote Speech
Value Shift: The Need for a New Corporate Ethic." Speaker. "Harvard Institute for Learning in Retirement
By: Lynn S. Paine
Keywords:
Ethics