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Show Results For

  • All HBS Web  (986)
    • People  (1)
    • News  (155)
    • Research  (662)
    • Events  (13)
    • Multimedia  (3)
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← Page 28 of 986 Results →
  • 2024
  • Case

EPCorp: Convincing the C-Suite

By: Jacob M. Cook
In EPCorp: Convincing the C-Suite, Shivani Bahl is attempting to sell EPCorp's CEO, Debbie Sullivan, on her ideas for not only a new website upgrade but also a more expansive vision on how data and Generative AI can be used to grow the company. Debbie is understandably... View Details
Keywords: AI and Machine Learning; E-commerce; Growth and Development Strategy
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Cook, Jacob M. "EPCorp: Convincing the C-Suite." Harvard Business Publishing Case, 2024. (Quick Case.)
  • September 2024
  • Background Note

Copyright and Fair Use

By: David B. Yoffie
The U.S. Copyright Office defines a copyright as “a type of intellectual property that protects original works of authorship as soon as an author fixes the work in a tangible form of expression.” Two core principles of copyright are originality and fixation. A work is... View Details
Keywords: AI and Machine Learning; Copyright; Lawsuits and Litigation; United States
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Yoffie, David B. "Copyright and Fair Use." Harvard Business School Background Note 725-394, September 2024.
  • 2022
  • Working Paper

The Evolution of ESG Reports and the Role of Voluntary Standards

By: Ethan Rouen, Kunal Sachdeva and Aaron Yoon
We examine the evolution of ESG reports of S&P 500 firms from 2010 to 2021. The percentage of firms releasing these voluntary disclosures increased from 35% to 86% during this period, although the length of these documents experienced more modest growth. Using a... View Details
Keywords: Voluntary Disclosure; Textual Analysis; Modeling And Analysis; Corporate Social Responsibility and Impact; AI and Machine Learning; Accounting
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Rouen, Ethan, Kunal Sachdeva, and Aaron Yoon. "The Evolution of ESG Reports and the Role of Voluntary Standards." Harvard Business School Working Paper, No. 23-024, October 2022.
  • August 25, 2022
  • Article

Find the Right Pace for Your AI Rollout

By: Rebecca Karp and Aticus Peterson
Implementing AI can introduce disruptive change and disfranchise staff and employees. When members are reluctant to adopt a new technology, they might hesitate to use it, push back against its deployment, or use it in limited capacity — which affects the benefits an... View Details
Keywords: AI and Machine Learning; Technology Adoption; Change Management
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Karp, Rebecca, and Aticus Peterson. "Find the Right Pace for Your AI Rollout." Harvard Business Review Digital Articles (August 25, 2022).
  • Article

Fake AI People Won't Fix Online Dating

By: Scott Duke Kominers
Computer-generated images may inspire even more distrust and surely won’t lead to the love of a lifetime. View Details
Keywords: Artificial Intelligence; Dating Services; Internet and the Web; Ethics; AI and Machine Learning
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Kominers, Scott Duke. "Fake AI People Won't Fix Online Dating." Bloomberg Opinion (January 16, 2020).
  • Working Paper

Shifting Work Patterns with Generative AI

By: Eleanor W. Dillon, Sonia Jaffe, Nicole Immorlica and Christopher T. Stanton
We present evidence on how generative AI changes the work patterns of knowledge workers using data from a 6-month-long, cross-industry, randomized field experiment. Half of the 7,137 workers in the study received access to a generative AI tool integrated into the... View Details
Keywords: AI and Machine Learning; Behavior; Time Management
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Dillon, Eleanor W., Sonia Jaffe, Nicole Immorlica, and Christopher T. Stanton. "Shifting Work Patterns with Generative AI." NBER Working Paper Series, No. 33795, May 2025. (Conditionally Accepted at American Economic Review: Insights .)
  • January 2025
  • Technical Note

AI vs Human: Analyzing Acceptable Error Rates Using the Confusion Matrix

By: Tsedal Neeley and Tim Englehart
This technical note introduces the confusion matrix as a foundational tool in artificial intelligence (AI) and large language models (LLMs) for assessing the performance of classification models, focusing on their reliability for decision-making. A confusion matrix... View Details
Keywords: Reliability; Confusion Matrix; AI and Machine Learning; Decision Making; Measurement and Metrics; Performance
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Neeley, Tsedal, and Tim Englehart. "AI vs Human: Analyzing Acceptable Error Rates Using the Confusion Matrix." Harvard Business School Technical Note 425-049, January 2025.
  • September 2024
  • Exercise

Finding Your 'Jagged Frontier': A Generative AI Exercise

By: Mitchell Weiss
In 2023 a set of scholars set out to study the effect of artificial intelligence (AI) on the quality and productivity of knowledge workers—in this specific instance, management consultants. They wanted to know across a range of tasks in a workflow, which, if any, would... View Details
Keywords: AI and Machine Learning; Performance Productivity; Performance Evaluation; Consulting Industry
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Weiss, Mitchell. "Finding Your 'Jagged Frontier': A Generative AI Exercise." Harvard Business School Exercise 825-070, September 2024.
  • November 2, 2021
  • Article

The Cultural Benefits of Artificial Intelligence in the Enterprise

By: Sam Ransbotham, François Candelon, David Kiron, Burt LaFountain and Shervin Khodabandeh
The 2021 MIT SMR-BCG report identifies a wide range of AI-related cultural benefits at both the team and organizational levels. Whether it’s reconsidering business assumptions or empowering teams, managing the dynamics across culture, AI use, and organizational... View Details
Keywords: AI and Machine Learning; Organizational Culture; Performance Effectiveness
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Ransbotham, Sam, François Candelon, David Kiron, Burt LaFountain, and Shervin Khodabandeh. "The Cultural Benefits of Artificial Intelligence in the Enterprise." MIT Sloan Management Review, Big Ideas Artificial Intelligence and Business Strategy Initiative (website) (November 2, 2021). (Findings from the 2021 Artificial Intelligence and Business Strategy Global Executive Study and Research Project.)
  • 20 Oct 2022 - 22 Oct 2022
  • Talk

Stigma Against AI Companion Applications

By: Julian De Freitas, A. Ragnhildstveit and A.K. Uğuralp
Keywords: AI and Machine Learning; Attitudes; Perception
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De Freitas, Julian, A. Ragnhildstveit, and A.K. Uğuralp. "Stigma Against AI Companion Applications." 53rd Association for Consumer Research Annual Conference, Denver, CO, October 20–22, 2022.
  • 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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De Freitas, Julian. "Why People Resist Embracing AI." Harvard Business Review 103, no. 1 (January–February 2025): 52–56.
  • July 2024
  • Case

The Voice Wars Continues 2024: Hey Google vs. Alexa vs. Siri vs. ChatGPT

By: David B. Yoffie and Sarah von Bargen
In 2024, the Voice War was transforming from a relatively simple index-based technology system, which relied on a list of commands and answers, to a generative AI system, which offered the promise to enable free flowing conversations between people and machines. The... View Details
Keywords: AI and Machine Learning; Competition; Technological Innovation; Technology Industry
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Yoffie, David B., and Sarah von Bargen. "The Voice Wars Continues 2024: Hey Google vs. Alexa vs. Siri vs. ChatGPT." Harvard Business School Case 725-352, July 2024.
  • 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
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Rashbass, Andrew, Ramon Casadesus-Masanell, and Jordan Mitchell. "The Financial Times (FT) and Generative AI." Harvard Business School Case 724-410, January 2024.
  • 11 Oct 2024
  • Research & Ideas

How AI Could Ease the Refugee Crisis and Bring New Talent to Businesses

says. “What we’re asking is, can we build algorithms that will help find better matches that will allow people to integrate more easily?” The paper presents data from Switzerland and the United States that showed promise in using machine... View Details
Keywords: by Ben Rand; Technology; Information Technology
  • October 31, 2022
  • Article

Achieving Individual—and Organizational—Value with AI

By: Sam Ransbotham, David Kiron, François Candelon, Shervin Khodabandeh and Michael Chu
New research shows that employees derive individual value from AI when using the technology improves their sense of competency, autonomy, and relatedness. Likewise, organizations are far more likely to obtain value from AI when their workers do. This report offers key... View Details
Keywords: AI and Machine Learning; Value; Competency and Skills
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Ransbotham, Sam, David Kiron, François Candelon, Shervin Khodabandeh, and Michael Chu. "Achieving Individual—and Organizational—Value with AI." MIT Sloan Management Review, Big Ideas Artificial Intelligence and Business Strategy Initiative (website) (October 31, 2022). (Findings from the 2022 Artificial Intelligence and Business Strategy Global Executive Study and Research Project.)
  • June 2025
  • Article

Ideation with Generative AI—In Consumer Research and Beyond

By: Julian De Freitas, G. Nave and Stefano Puntoni
The use of large language models (LLMs) in consumer research is rapidly evolving, with applications including synthetic data generation, data analysis, and more. However, their role in creative ideation—a cornerstone of consumer research—remains underexplored. Drawing... View Details
Keywords: Large Language Model; AI and Machine Learning; Creativity; Innovation Strategy
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De Freitas, Julian, G. Nave, and Stefano Puntoni. "Ideation with Generative AI—In Consumer Research and Beyond." Journal of Consumer Research 51, no. 1 (June 2025): 18–31.
  • June 2024
  • Teaching Note

Numenta in 2020: The Future of AI

By: David B. Yoffie
In 2020, Numenta’s co-founder, Jeff Hawkins, completed his pathbreaking research on artificial intelligence. His co-founder and CEO, Donna Dubinsky, had to find a business model to monetize the technology. This teaching note explores the challenges of building a... View Details
Keywords: Artificial Intelligence; Monetization; Strategy; Intellectual Property; AI and Machine Learning; Business Model; Entrepreneurship; Technology Industry
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Yoffie, David B. "Numenta in 2020: The Future of AI." Harvard Business School Teaching Note 724-496, June 2024.
  • July 2024
  • Case

Replika AI: Alleviating Loneliness (A)

By: Shikhar Ghosh and Shweta Bagai
Eugenia Kuyda launched Replika AI in 2017 as an empathetic digital companion to combat loneliness and provide emotional support. The platform surged in popularity during the COVID-19 pandemic, offering non-judgmental support to isolated users. By 2023, Replika boasted... View Details
Keywords: Entrepreneurship; Ethics; Health Pandemics; AI and Machine Learning; Well-being; Technology Industry
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Ghosh, Shikhar, and Shweta Bagai. "Replika AI: Alleviating Loneliness (A)." Harvard Business School Case 824-088, July 2024.
  • 2023
  • Article

On the Impact of Actionable Explanations on Social Segregation

By: Ruijiang Gao and Himabindu Lakkaraju
As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research... View Details
Keywords: Forecasting and Prediction; AI and Machine Learning; Outcome or Result
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Gao, Ruijiang, and Himabindu Lakkaraju. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.
  • October 14, 2023
  • Article

Will Consumers Buy Selfish Self-Driving Cars?

By: Julian De Freitas
Keywords: AI and Machine Learning; Ethics; Technological Innovation; Safety; Auto Industry
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De Freitas, Julian. "Will Consumers Buy Selfish Self-Driving Cars?" Wall Street Journal (October 14, 2023), C5.
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