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- 2024
- Working Paper
The Cram Method for Efficient Simultaneous Learning and Evaluation
By: Zeyang Jia, Kosuke Imai and Michael Lingzhi Li
We introduce the "cram" method, a general and efficient approach to simultaneous learning and evaluation using a generic machine learning (ML) algorithm. In a single pass of batched data, the proposed method repeatedly trains an ML algorithm and tests its empirical... View Details
Keywords: AI and Machine Learning
Jia, Zeyang, Kosuke Imai, and Michael Lingzhi Li. "The Cram Method for Efficient Simultaneous Learning and Evaluation." Working Paper, March 2024.
- 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
- March 2024
- Article
Investigation of Divergent Thinking among Surgeons and Surgeon Trainees in Canada (IDEAS): A Mixed-methods Study
By: Alex Thabane, Tyler McKechnie, Vikram Arora, Goran Calic, Jason W Busse, Ranil Sonnadara and Mohit Bhandari
Objective: To assess the creative potential of surgeons and surgeon trainees, as measured by divergent thinking. The secondary objectives were to identify factors associated with divergent thinking, assess confidence in creative problem-solving and the perceived effect... View Details
Thabane, Alex, Tyler McKechnie, Vikram Arora, Goran Calic, Jason W Busse, Ranil Sonnadara, and Mohit Bhandari. "Investigation of Divergent Thinking among Surgeons and Surgeon Trainees in Canada (IDEAS): A Mixed-methods Study." BMJ Open 14, no. 3 (March 2024).
- 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.
- January 2024
- Case
National Football League and Private 5G
By: Andy Wu, Grant Son and Shuoyu Chen
On September 9, 2021, the National Football League (NFL) designated Verizon as its official 5G partner in a 10-year deal, committed to enhance the experience for NFL teams, players, and fans in stadiums. NFL Commissioner Roger Goodell said, “Verizon will help us... View Details
Keywords: Football; National Football League; 5G; Verizon; Communication Technology; Mobile and Wireless Technology; Technology Adoption; Risk and Uncertainty; Business Strategy; Collaborative Innovation and Invention; Sports Industry; Telecommunications Industry
Wu, Andy, Grant Son, and Shuoyu Chen. "National Football League and Private 5G." Harvard Business School Case 724-433, January 2024.
- December 2023
- Case
Davivienda Bank's Upskilling and Reskilling Strategy in Colombia
By: Jorge Tamayo, Raffaella Sadun and Jenyfeer Martinez Buitrago
Set in 2022, this case describes the digital transformation strategy of Davivienda— a leading player in Colombia’s commercial banking and one of the companies belonging to Grupo Bolívar, a major Colombian financial conglomerate—and the bank’s upskilling and reskilling... View Details
Keywords: Change Management; Transformation; Decision Choices and Conditions; Digital Strategy; Digital Transformation; Internet and the Web; Mobile and Wireless Technology; Innovation and Management; Innovation Strategy; Growth and Development Strategy; Business Strategy; Corporate Strategy; Organizational Culture; Talent and Talent Management; Training; Banking Industry; Latin America; Central America; South America; Colombia
Tamayo, Jorge, Raffaella Sadun, and Jenyfeer Martinez Buitrago. "Davivienda Bank's Upskilling and Reskilling Strategy in Colombia." Harvard Business School Case 724-425, December 2023.
- 2023
- Working Paper
Rapport in Organizations: Evidence from Fast Food
By: Achyuta Adhvaryu, Parker Howell, Anant Nyshadham and Jorge Tamayo
Common identity often provides a foundation for workplace rapport. Though gender is perhaps the most frequently studied dimension of identity among workers, little is known about how gender match between managers and their workers might affect team performance. Using... View Details
Keywords: Management; Relationships; Gender; Labor and Management Relations; Organizational Change and Adaptation; Employees; Food and Beverage Industry; Colombia
Adhvaryu, Achyuta, Parker Howell, Anant Nyshadham, and Jorge Tamayo. "Rapport in Organizations: Evidence from Fast Food." Harvard Business School Working Paper, No. 24-032, November 2023.
- December 8, 2023
- Article
What Makes a Company Great at Producing Leaders?
By: Sarah Abbott, Robin Abrahams and Boris Groysberg
GE is well known as an “academy company”—a talent incubator that exports effective leaders to other organizations and even industries. To better understand which companies are top talent incubators today, the authors worked with the Official Board, a firm that provides... View Details
Keywords: Personal Development and Career; Talent and Talent Management; Training; Organizational Culture
Abbott, Sarah, Robin Abrahams, and Boris Groysberg. "What Makes a Company Great at Producing Leaders?" Harvard Business Review (website) (December 8, 2023).
- 2023
- Article
MoPe: Model Perturbation-based Privacy Attacks on Language Models
By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training... View Details
Li, Marvin, Jason Wang, Jeffrey Wang, and Seth Neel. "MoPe: Model Perturbation-based Privacy Attacks on Language Models." Proceedings of the Conference on Empirical Methods in Natural Language Processing (2023): 13647–13660.
- 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).
- 2023
- Article
Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability
By: Usha Bhalla, Suraj Srinivas and Himabindu Lakkaraju
With the increased deployment of machine learning models in various real-world applications, researchers and practitioners alike have emphasized the need for explanations of model behaviour. To this end, two broad strategies have been outlined in prior literature to... View Details
Bhalla, Usha, Suraj Srinivas, and Himabindu Lakkaraju. "Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 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).
- October 2023 (Revised January 2025)
- Case
Ӧzyeğin Social Investments: A Legacy of Giving
By: Christina R. Wing, Zeshan Gondal and Brittany L. Logan
This case explores the work of Özyeğin Social Investments, founded by Hüsnü Özyeğin, one of Turkey's most successful entrepreneurs. With a focus on education, health, gender equality, rural development, and disaster relief in Turkey, Özyeğin Social Investments and the... View Details
Keywords: Philanthropy and Charitable Giving; Family Business; Business Model; Social Entrepreneurship; Social Enterprise; Turkey
Wing, Christina R., Zeshan Gondal, and Brittany L. Logan. "Ӧzyeğin Social Investments: A Legacy of Giving." Harvard Business School Case 624-054, October 2023. (Revised January 2025.)
- October 2023
- Case
Social Finance: Driving Accountability
By: Robin Greenwood, Richard S. Ruback and Robert Ialenti
Social Finance is a Boston-based nonprofit that works at the intersection of finance and policy. It raises, allocates, and manages capital to fund projects in the areas of education, early childhood development, criminal justice, and health. The case explores how... View Details
Greenwood, Robin, Richard S. Ruback, and Robert Ialenti. "Social Finance: Driving Accountability." Harvard Business School Case 224-043, October 2023.
- 2023
- Working Paper
Black-box Training Data Identification in GANs via Detector Networks
By: Lukman Olagoke, Salil Vadhan and Seth Neel
Since their inception Generative Adversarial Networks (GANs) have been popular generative models across images, audio, video, and tabular data. In this paper we study whether given access to a trained GAN, as well as fresh samples from the underlying distribution, if... View Details
Olagoke, Lukman, Salil Vadhan, and Seth Neel. "Black-box Training Data Identification in GANs via Detector Networks." Working Paper, October 2023.
- 2023
- Working Paper
In-Context Unlearning: Language Models as Few Shot Unlearners
By: Martin Pawelczyk, Seth Neel and Himabindu Lakkaraju
Machine unlearning, the study of efficiently removing the impact of specific training points on the
trained model, has garnered increased attention of late, driven by the need to comply with privacy
regulations like the Right to be Forgotten. Although unlearning is... View Details
Pawelczyk, Martin, Seth Neel, and Himabindu Lakkaraju. "In-Context Unlearning: Language Models as Few Shot Unlearners." Working Paper, October 2023.
- September 2023
- Case
Trilling Foods: Managing People with Data
Trilling Foods, a regional bricks-and-mortar grocery chain, has recently provided its frontline managers with new tools for using data. Allison Andersen, Trilling’s VP of Data Science, has spearheaded these efforts. Yet, as she works with Kent Wade, the general manager... View Details
Keywords: Digital Transformation; Management Practices and Processes; Training; Organizational Change and Adaptation; Food and Beverage Industry; Retail Industry
Feldberg, Alexandra C., and Jeffrey T. Polzer. "Trilling Foods: Managing People with Data." Harvard Business School Case 424-025, September 2023.
- 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.
- August 2023
- Case
Constellation Pharmaceuticals: Corporate Development at a Novel Therapeutic Company
By: Satish Tadikonda and Brad Prosek
Constellation Pharmaceuticals was a company focused on epigenetic therapies for cancer patients. Despite a promising start and an early deal with a leading biopharma company, the company weathered twin setbacks in the end of a major research collaboration and the... View Details
Keywords: Mergers and Acquisitions; Health Care and Treatment; Organizational Change and Adaptation; Research and Development; Business Strategy; Partners and Partnerships; Goals and Objectives; Pharmaceutical Industry; United States
Tadikonda, Satish, and Brad Prosek. "Constellation Pharmaceuticals: Corporate Development at a Novel Therapeutic Company." Harvard Business School Case 824-032, August 2023.
- August 2023
- Case
Salma Qarnain: Spaceships to Broadway
By: Leslie Perlow, Mel Martin and Hannah Weisman
Salma Qarnain, daughter of Pakistani Muslim immigrants, is an engineer trained at Stanford and MIT. She began her career building spacecrafts but 30 years later finds herself pursuing her calling, acting on Broadway. The case explores Qarnain’s career path, family... View Details
Keywords: Personal Development and Career; Job Search; Job Design and Levels; Happiness; Identity; Well-being; Work-Life Balance; Family and Family Relationships; Theater Entertainment; Film Entertainment; Talent and Talent Management; Entertainment and Recreation Industry; Motion Pictures and Video Industry; Aerospace Industry; United States; New York (city, NY); Boston; California