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(889)
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- Faculty Publications (468)
Show Results For
- All HBS Web
(889)
- People (1)
- News (160)
- Research (567)
- Events (10)
- Multimedia (3)
- Faculty Publications (468)
- 2023
- Article
Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details
Srinivas, Suraj, Sebastian Bordt, and Himabindu Lakkaraju. "Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 8 Sep 2023
- Conference Presentation
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, K. Uguralp, Z. Uguralp and Stefano Puntoni
De Freitas, Julian, K. Uguralp, Z. Uguralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Paper presented at the Business & Generative AI Workshop, Wharton School, AI at Wharton, San Francisco, CA, United States, September 8, 2023.
- Article
Why Boards Aren't Dealing with Cyberthreats
By: J. Yo-Jud Cheng and Boris Groysberg
Cheng, J. Yo-Jud, and Boris Groysberg. "Why Boards Aren't Dealing with Cyberthreats." Harvard Business Review (website) (February 22, 2017). (Excerpt featured in the Harvard Business Review. May–June 2017 "Idea Watch" section.)
- February 2024
- Technical Note
AI Product Development Lifecycle
By: Michael Parzen, Jessie Li and Marily Nika
In this article, we will discuss the concept of AI Products, how they are changing our daily lives, how the field of AI & Product Management is evolving, and the AI Product Development Lifecycle. View Details
Keywords: Artificial Intelligence; Product Management; Product Life Cycle; Technology; AI and Machine Learning; Product Development
Parzen, Michael, Jessie Li, and Marily Nika. "AI Product Development Lifecycle." Harvard Business School Technical Note 624-070, February 2024.
- 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
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.)
- July–August 2021
- Article
Why You Aren't Getting More from Your Marketing AI
By: Eva Ascarza, Michael Ross and Bruce G.S. Hardie
Fewer than 40% of companies that invest in AI see gains from it, usually because of one or more of these errors: (1) They don’t ask the right question, and end up directing AI to solve the wrong problem. (2) They don’t recognize the differences between the value of... View Details
Keywords: Artificial Intelligence; Marketing; Decision Making; Communication; Framework; AI and Machine Learning
Ascarza, Eva, Michael Ross, and Bruce G.S. Hardie. "Why You Aren't Getting More from Your Marketing AI." Harvard Business Review 99, no. 4 (July–August 2021): 48–54.
- July 2024
- Article
AI, ROI, and Sales Productivity
Artificial intelligence (AI) is now a loose term for many different things and at the peak of its hype curve. So managers hitch-their-pitch to the term in arguing for resources. But like any technology, its business value depends upon actionable use cases embraced by... View Details
Cespedes, Frank V. "AI, ROI, and Sales Productivity." Top Sales Magazine (July 2024), 12–13.
- March 16, 2021
- Article
From Driverless Dilemmas to More Practical Commonsense Tests for Automated Vehicles
By: Julian De Freitas, Andrea Censi, Bryant Walker Smith, Luigi Di Lillo, Sam E. Anthony and Emilio Frazzoli
For the first time in history, automated vehicles (AVs) are being deployed in populated environments. This unprecedented transformation of our everyday lives demands a significant undertaking: endowing
complex autonomous systems with ethically acceptable behavior. We... View Details
Keywords: Automated Driving; Public Health; Artificial Intelligence; Transportation; Health; Ethics; Policy; AI and Machine Learning
De Freitas, Julian, Andrea Censi, Bryant Walker Smith, Luigi Di Lillo, Sam E. Anthony, and Emilio Frazzoli. "From Driverless Dilemmas to More Practical Commonsense Tests for Automated Vehicles." Proceedings of the National Academy of Sciences 118, no. 11 (March 16, 2021).
- 2024
- Working Paper
The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations
By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang
The rise of generative artificial intelligence (AI) is transforming creative problem-solving, necessitating new approaches for evaluating innovative solutions. This study explores how human-AI collaboration can enhance early-stage evaluations, focusing on the interplay... View Details
Lane, Jacqueline N., Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh, and Pei-Hsin Wang. "The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations." Harvard Business School Working Paper, No. 25-001, August 2024. (Revised August 2024.)
- 2023
- Article
Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset
By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,... View Details
Keywords: Large Language Model; AI and Machine Learning; Analytics and Data Science; Health Industry
Liu, Junling, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, and Michael Lingzhi Li. "Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
- 2023
- Working Paper
The Impact of Input Inaccuracy on Leveraging AI Tools: Evidence from Algorithmic Labor Scheduling
By: Caleb Kwon, Antonio Moreno and Ananth Raman
Are the inputs used by your AI tool correct and up to date? In this paper, we show that the answer to this question: (i) is frequently a “no” in real business contexts, and (ii) has significant implications on the performance of AI tools. In the context of algorithmic... View Details
Kwon, Caleb, Antonio Moreno, and Ananth Raman. "The Impact of Input Inaccuracy on Leveraging AI Tools: Evidence from Algorithmic Labor Scheduling." Working Paper, October 2023.
- June 20, 2023
- Article
Cautious Adoption of AI Can Create Positive Company Culture
By: Joseph Pacelli and Jonas Heese
Pacelli, Joseph, and Jonas Heese. "Cautious Adoption of AI Can Create Positive Company Culture." CMR Insights (June 20, 2023).
- 2024
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift
By: Matthew DosSantos DiSorbo and Kris Ferreira
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). These outliers often originate from covariate shift,... View Details
DosSantos DiSorbo, Matthew, and Kris Ferreira. "Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift." Working Paper, February 2024.
- 2023
- Article
Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators
By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details
Jakubowski, Benjamin, Siram Somanchi, Edward McFowland III, and Daniel B. Neill. "Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators." Journal of Machine Learning Research 24, no. 133 (2023): 1–57.
- 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.
- 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
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
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
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
Kominers, Scott Duke. "Fake AI People Won't Fix Online Dating." Bloomberg Opinion (January 16, 2020).
- August 2022 (Revised January 2023)
- Case
Icario Health: AI to Drive Health Engagement
By: David C. Edelman
Icario Health has built a market-leading artificial intelligence (AI) engine to help health insurers drive better health behaviors for their members, enabling the insurers to improve their Medicare performance. View Details
Keywords: Marketing; Health Care and Treatment; AI and Machine Learning; Health Industry; United States
Edelman, David C. "Icario Health: AI to Drive Health Engagement." Harvard Business School Case 523-025, August 2022. (Revised January 2023.)
- 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
Rashbass, Andrew, Ramon Casadesus-Masanell, and Jordan Mitchell. "The Financial Times (FT) and Generative AI." Harvard Business School Case 724-410, January 2024.