Publications
Publications
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(15,133)
- Faculty Publications (4,926)
- 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
- 2023
- Article
Post Hoc Explanations of Language Models Can Improve Language Models
By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance... View Details
- December 2023
- Article
Self-Orienting in Human and Machine Learning
By: Julian De Freitas, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum and T. Ullman
A current proposal for a computational notion of self is a representation of one’s body in a specific time and place, which includes the recognition of that representation as the agent. This turns self-representation into a process of self-orientation, a challenging... View Details
- 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
- 2024
- Working Paper
The Uneven Impact of Generative AI on Entrepreneurial Performance
By: Nicholas G. Otis, Rowan Clarke, Solène Delecourt, David Holtz and Rembrand Koning
Scalable and low-cost AI assistance has the potential to improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it difficult to know whether recent AI advances can help business owners make... View Details
- 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
- December 2023
- Article
When Should the Off-Grid Sun Shine at Night? Optimum Renewable Generation and Energy Storage Investments
By: Christian Kaps, Simone Marinesi and Serguei Netessine
Globally, 1.5 billion people live off the grid, their only access to electricity often limited to operationally-expensive fossil fuel generators. Solar power has risen as a sustainable and less costly option, but its generation is variable during the day and... View Details
- 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
- November 2023 (Revised October 2024)
- Supplement
Accounting Outages at Plug Power? (C)
By: Jonas Heese, Joseph Pacelli and James Barnett
Set in June 2023, the C case explores Plug Power’s recovery from its financial restatements, how it benefited from government subsidies, and new strategic alliances. View Details
- November 2023
- Case
Open Source Machine Learning at Google
Set in early 2023, the case exposes students to the challenges of managing open source software at Google. The case focuses on the challenges for Alex Spinelli, Vice President of Product Management for Core Machine Learning. He must set priorities for Google’s efforts... View Details
- November 2023
- Case
Riiid: Scaling AI Educational Services Globally
By: John Jong-Hyun Kim, Nancy Dai and Ruru Hoong
This article explores the definition and evolution of AI, its applications in education, and the role of AI, particularly in K-12 education. It discusses the founding of Riiid, an AI-driven educational technology company, and its journey in the education sector, with a... View Details
- 2023
- Working Paper
Coordinated R&D Programs and the Creation of New Industries
By: Daniel P. Gross and Maria P. Roche
Government R&D programs have a long history in supporting industry development, yet their impacts are often overlooked in strategy research. We examine how a large, coordinated, government-funded effort to develop radar in World War II spawned a new high-tech industry.... View Details
- November 2023
- Case
Copilot(s): Generative AI at Microsoft and GitHub
This case tells the story of Microsoft’s 2018 acquisition of GitHub and the subsequent launch of GitHub Copilot, a tool that uses generative artificial intelligence to suggest snippets of code to software developers in real time. Set in late 2021, when Copilot was... View Details
- November 2023 (Revised March 2024)
- Technical Note
Customer Data Privacy
By: Eva Ascarza and Ta-Wei Huang
This note provides an overview of the evolving landscape of customer data privacy in 2023. It highlights two pivotal aspects that make privacy a central concern for businesses: building and maintaining customer trust and navigating the intricate regulatory... View Details
- November 2023
- Case
Will Fintechs and Central Banks Play in Emtech's Sandbox?
By: Daniel Isenberg and William R. Kerr
In February 2023, Emtech’s founder Carmelle Cadet is facing a dilemma. Rapidly running out of cash, Cadet has a term sheet from a leading VC but has a choice of how to structure the investment. The decision will have significant implications for Cadet’s own stake, as... View Details
- November 2023
- Case
Apple Inc. in 2023
By: David B. Yoffie and Sarah von Bargen
Under CEO Tim Cook, Apple became the first trillion dollar market cap company, the first two trillion dollar company, and the first three trillion dollar company. Since the COVID pandemic, Apple gained over 20% of the world smartphone market and 50% of the U.S. market,... View Details
- November 2023 (Revised January 2024)
- Case
Bridgit: Persevere or Pivot?
By: Reza Satchu and Patrick Sanguineti
In late 2012, Mallorie Brodie and Lauren Lake, two young women in their final year of college, founded Bridgit, a technology startup that developed solutions to simplify vital but laborious processes within the construction industry. In the Fall of 2013, after months... View Details
- November 2023 (Revised April 2024)
- Case
Khanmigo: Revolutionizing Learning with GenAI
By: William A. Sahlman, Allison M. Ciechanover and Emily Grandjean
Already a leader in the edtech space since its 2008 launch, Khan Academy was now one of the first edtech organizations to embrace generative artificial intelligence ("genAI"). In March 2023, Khan Academy began beta testing Khanmigo, a genAI “guide” and tutor built with... View Details
- November 2023
- Case
Chai Point
By: Rembrand Koning, Daniel W. Elfenbein and Kanika Jain
Chai Point was an Indian food and beverage company focused on chai. It started in 2010 as a retail store network but soon expanded to corporate offices by developing an IoT-enabled automatic tea and filter coffee machine. By 2023, Chai Point had 170 stores and 5000... View Details
- Working Paper
An AI Method to Score Celebrity Visual Potential from Human Faces
By: Flora Feng, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan and Cait Lamberton
Celebrities have extraordinary abilities to attract and influence others. Predicting celebrity visual potential is important in the domains of business, politics, media, and entertainment. Can we use human faces to predict celebrity visual potential? If so, which... View Details