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29 May 2013
Blog Post

Reflections and learnings

So, without further ado, the 7* lessons that made this all worthwhile for me: Winning is not easy: It’s easy to look at an industry leader like Sephora and imagine a seamlessly polished machine cranking out... View Details

Keywords: Consumer Products / Retail

2023
Book

Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow

By: Ken Huang, Yang Wang, Feng Zhu, Xi Chen and Chunxiao Xing

This book explores the transformative potential of ChatGPT, Web3, and their impact on productivity and various industries. It delves into Generative AI (GenAI) and its representative platform ChatGPT, their synergy with Web3, and how they can revolutionize business... View Details

Keywords: Generative Ai; AI and Machine Learning; Ethics; Technology Adoption

August 2021 (Revised November 2024)
Case

Intenseye: Powering Workplace Health and Safety with AI (A)

By: Michael W. Toffel and Youssef Abdel Aal

Intenseye was a Turkey-based technology startup that deployed machine learning algorithms to workplace camera feeds in order to identify unsafe worker actions and unsafe working conditions, in order to help improve worker safety. The case describes how Intenseye’s... View Details

Keywords: Privacy; Product Development; Operations; Technological Innovation; Value Creation; Production; Distribution; Safety; Risk and Uncertainty; Technology Industry; Manufacturing Industry; Distribution Industry; Turkey; Middle East; United States

December 2024
Case

Blue Cross Blue Shield of Michigan (BCBSM): The AI Journey

By: Shikhar Ghosh

In early 2024, Bill Fandrich, Executive VP and CIO of Blue Cross Blue Shield of Michigan (BCBSM), faced a critical decision about AI adoption within the organization. Fandrich had championed AI implementation at BCBSM. After successfully developing three AI... View Details

January 2024
Case

The Financial Times (FT) and Generative AI

By: Andrew Rashbass, Ramon Casadesus-Masanell and Jordan Mitchell

In September 2023, John Ridding, CEO of the Financial Times, was considering the possible impact of Generative AI on the industry and his business. Having navigated successfully the seismic shift from print to digital, and reporting record results, the company... View Details

Keywords: AI and Machine Learning; Technology Adoption; Change Management; Journalism and News Industry

April 2024 (Revised December 2024)
Case

Anthropic: Building Safe AI

By: Shikhar Ghosh and Shweta Bagai

In late 2024, Anthropic, a leading AI safety and research company, achieved a significant breakthrough with computer use capabilities that allowed AI to interact with computers like humans. Co-founded by former OpenAI employees and known for its generative AI... View Details

Keywords: AI and Machine Learning; Corporate Accountability; Corporate Social Responsibility and Impact; Business Growth and Maturation; Corporate Strategy; Technology Industry; United States

Article

Faithful and Customizable Explanations of Black Box Models

By: Himabindu Lakkaraju, Ece Kamar, Rich Caruana and Jure Leskovec

As predictive models increasingly assist human experts (e.g., doctors) in day-to-day decision making, it is crucial for experts to be able to explore and understand how such models behave in different feature subspaces in order to know if and when to trust them. To... View Details

Keywords: Interpretable Machine Learning; Black Box Models; Decision Making; Framework

March 2024 (Revised August 2024)
Case

Darktrace: Scaling Cybersecurity and AI (A)

By: Jeffrey F. Rayport and Alexis Lefort

In 2023, Darktrace CEO Poppy Gustafsson was contemplating her growth strategy at a leading U.K.-based cybersecurity venture, launched in 2013 by a group of anti-terror cyber specialists, University of Cambridge mathematicians, and artificial intelligence (AI) experts.... View Details

Keywords: Technology; Talent; Scaling; Entrepreneurship; Cybersecurity; Leadership; Business Growth and Maturation; Recruitment; Resignation and Termination; AI and Machine Learning; Growth and Development Strategy; Organizational Culture; Going Public; Technology Industry; United Kingdom; Europe; United States

June 2024
Teaching Note

Beamery: Using Skills and AI to Modernize HR

By: Boris Groysberg, David Lane, Susan Pinckney and Alexis Lefort

Teaching Note for HBS Case No. 424-004. Unicorn human relationships startup Beamery evaluates it growth versus depth strategy as its strategic partners and customers could become future competitors in a quickly changing AI based human resources and talent management... View Details

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)—software... View Details

Keywords: Mergers and Acquisitions; AI and Machine Learning; Applications and Software; Technological Innovation; Product Launch; Open Source Distribution; Product Development; Commercialization; Competition; Resource Allocation; Technology Industry

2024
Working Paper

AI Companions Reduce Loneliness

By: Julian De Freitas, Ahmet K. Uğuralp, Zeliha O. Uğuralp and Stefano Puntoni

Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications are... View Details

Keywords: AI and Machine Learning; Technological Innovation; Behavior; Well-being

February 2019
Case

Miroglio Fashion (A)

By: Sunil Gupta and David Lane

Francesco Cavarero, chief information officer of Miroglio Fashion, Italy’s third-largest retailer of women’s apparel, was trying to bring analytical rigor to the company’s forecasting and inventory management decisions. But fashion is inherently hard to predict. Can... View Details

Keywords: Inventory Management; Demand Forecasting; Artificial Intelligence; Machine Learning; Forecasting and Prediction; Operations; Management; Decision Making; AI and Machine Learning; Apparel and Accessories Industry; Apparel and Accessories Industry

2021
Conference Presentation

An Algorithmic Framework for Fairness Elicitation

By: Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Leon Roth, Logan Stapleton and Zhiwei Steven Wu

We consider settings in which the right notion of fairness is not captured by simple mathematical definitions (such as equality of error rates across groups), but might be more complex and nuanced and thus require elicitation from individual or collective stakeholders.... View Details

Keywords: Algorithmic Fairness; Machine Learning; Fairness; Framework; Mathematical Methods

2024
Working Paper

The Value of AI Innovations

By: Wilbur Xinyuan Chen, Terrence Tianshuo Shi and Suraj Srinivasan

We study the value of AI innovations as it diffuses across general and application sectors, using the United States Patent and Trademark Office’s (USPTO) AI patent dataset. Investors value these innovations more than others, as AI patents exhibit a 9% value premium,... View Details

Keywords: AI and Machine Learning; Valuation; Technological Innovation; Open Source Distribution; Patents; Policy; Knowledge Sharing; Technology Industry

January–February 2025
Article

Why People Resist Embracing AI

By: Julian De Freitas

The success of AI depends not only on its capabilities, which are becoming more advanced each day, but on people’s willingness to harness them. Unfortunately, many people view AI negatively, fearing it will cause job losses, increase the likelihood that their personal... View Details

Keywords: AI and Machine Learning; Technology Adoption; Perception

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October 20, 2020
Article

Expanding AI's Impact with Organizational Learning

By: Sam Ransbotham, Shervin Khodabandeh, David Kiron, François Candelon, Michael Chu and Burt LaFountain

Most companies developing AI capabilities have yet to gain significant financial benefits from their efforts. Only when organizations add the ability to learn with AI do significant benefits become likely. View Details

Keywords: AI and Machine Learning; Learning; Adoption

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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... View Details

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

January 2025
Article

Reducing Prejudice with Counter-stereotypical AI

By: Erik Hermann, Julian De Freitas and Stefano Puntoni

Based on a review of relevant literature, we propose that the proliferation of AI with human-like and social features presents an unprecedented opportunity to address the underlying cognitive and affective drivers of prejudice. An approach informed by the psychology of... View Details

Keywords: Prejudice and Bias; AI and Machine Learning; Interpersonal Communication; Social and Collaborative Networks

March 2019
Teaching Note

Numenta: Inventing and (or) Commercializing AI

By: David B. Yoffie

This teaching notes accompanies the Numenta case, HBS No. 716-469. The focus is how to scale a new artificial intelligence technology, how to build a platform and overcome chicken-or-the-egg problems, and how to utilize open source software and licensing. View Details

Keywords: Artificial Intelligence; Strategy; Information Technology; Technological Innovation; Commercialization; AI and Machine Learning

March 2024
Teaching Note

'Storrowed': A Generative AI Exercise

By: Mitchell Weiss

Teaching Note for HBS Exercise No. 824-188. “Storrowed” is an exercise to help participants raise their proficiency with generative AI. It begins by highlighting a problem: trucks getting wedged underneath bridges in Boston, Massachusetts on the city’s Storrow Drive.... View Details

Keywords: AI and Machine Learning; Entrepreneurship; Innovation and Invention; Government Administration; Transportation Industry; Public Administration Industry

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