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- 2022
- Article
Efficiently Training Low-Curvature Neural Networks
By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret
Standard deep neural networks often have excess non-linearity, making them susceptible to issues such as low adversarial robustness and gradient instability. Common methods to address these downstream issues, such as adversarial training, are expensive and often... View Details
Keywords: AI and Machine Learning
Srinivas, Suraj, Kyle Matoba, Himabindu Lakkaraju, and Francois Fleuret. "Efficiently Training Low-Curvature Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) (2022).
- November 2022 (Revised March 2024)
- Case
Replika AI: Monetizing a Chatbot
By: Julian De Freitas and Nicole Tempest Keller
In early 2018, Eugenia Kuyda, co-founder and CEO of San Francisco-based chatbot Replika AI, was deciding how to monetize the app she had built. Launched in 2017, Replika was a consumer AI “companion app” developed by a team of AI software engineers originally based in... View Details
Keywords: Mental Health; Subscriber Models; TAM; Monetization Strategy; Marketing Strategy; Product Marketing; AI and Machine Learning; Applications and Software; Product Positioning; Health Disorders; Technology Industry
De Freitas, Julian, and Nicole Tempest Keller. "Replika AI: Monetizing a Chatbot." Harvard Business School Case 523-016, November 2022. (Revised March 2024.)
- November 2022 (Revised December 2024)
- Case
Hugging Face (A): Serving AI on a Platform
By: Shane Greenstein, Daniel Yue, Sarah Gulick and Kerry Herman
It is fall 2022, and open-source AI model company Hugging Face is considering its three areas of priorities: platform development, supporting the open-source community, and pursuing cutting-edge scientific research. As it expands services for enterprise clients, which... View Details
Keywords: Community; Open-source; AI and Machine Learning; Product Development; Networks; Service Delivery; Research; Governance; Business and Stakeholder Relations; Information Industry; Technology Industry; United States
Greenstein, Shane, Daniel Yue, Sarah Gulick, and Kerry Herman. "Hugging Face (A): Serving AI on a Platform." Harvard Business School Case 623-026, November 2022. (Revised December 2024.)
- 2022
- Article
A Human-Centric Take on Model Monitoring
By: Murtuza Shergadwala, Himabindu Lakkaraju and Krishnaram Kenthapadi
Predictive models are increasingly used to make various consequential decisions in high-stakes domains such as healthcare, finance, and policy. It becomes critical to ensure that these models make accurate predictions, are robust to shifts in the data, do not rely on... View Details
Shergadwala, Murtuza, Himabindu Lakkaraju, and Krishnaram Kenthapadi. "A Human-Centric Take on Model Monitoring." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (HCOMP) 10 (2022): 173–183.
- November–December 2022
- Article
Can AI Really Help You Sell?: It Can, Depending on When and How You Implement It
By: Jim Dickie, Boris Groysberg, Benson P. Shapiro and Barry Trailer
Many salespeople today are struggling; only 57% of them make their annual quotas, surveys show. One problem is that buying processes have evolved faster than selling processes, and buyers today can access a wide range of online resources that let them evaluate products... View Details
Dickie, Jim, Boris Groysberg, Benson P. Shapiro, and Barry Trailer. "Can AI Really Help You Sell? It Can, Depending on When and How You Implement It." Harvard Business Review 100, no. 6 (November–December 2022): 120–129.
- 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.
- October 2022 (Revised December 2022)
- Case
SMART: AI and Machine Learning for Wildlife Conservation
By: Brian Trelstad and Bonnie Yining Cao
Spatial Monitoring and Reporting Tool (SMART), a set of software and analytical tools designed for the purpose of wildlife conservation, had demonstrated significant improvements in patrol coverage, with some observed reductions in poaching and contributing to wildlife... View Details
Keywords: Business and Government Relations; Emerging Markets; Technology Adoption; Strategy; Management; Ethics; Social Enterprise; AI and Machine Learning; Analytics and Data Science; Natural Environment; Technology Industry; Cambodia; United States; Africa
Trelstad, Brian, and Bonnie Yining Cao. "SMART: AI and Machine Learning for Wildlife Conservation." Harvard Business School Case 323-036, October 2022. (Revised December 2022.)
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
- September 2022 (Revised November 2022)
- Teaching Note
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli
Teaching Note for HBS Case No. 522-046. View Details
Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
- 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).
- 20 Oct 2022 - 22 Oct 2022
- Talk
Stigma Against AI Companion Applications
By: Julian De Freitas, A. Ragnhildstveit and A.K. Uğuralp
- 2022
- Conference Presentation
Towards the Unification and Robustness of Post hoc Explanation Methods
By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two... View Details
Keywords: AI and Machine Learning
Agarwal, Sushant, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, and Himabindu Lakkaraju. "Towards the Unification and Robustness of Post hoc Explanation Methods." Paper presented at the 3rd Symposium on Foundations of Responsible Computing (FORC), 2022.
- May 2022 (Revised July 2023)
- Case
Altibbi: Revolutionizing Telehealth Using AI
Lakkaraju, Himabindu. "Altibbi: Revolutionizing Telehealth Using AI." Harvard Business School Case 622-088, May 2022. (Revised July 2023.)
- May 2022 (Revised June 2024)
- Case
LOOP: Driving Change in Auto Insurance Pricing
By: Elie Ofek and Alicia Dadlani
John Henry and Carey Anne Nadeau, co-founders and co-CEOs of LOOP, an insurtech startup based in Austin, Texas, were on a mission to modernize the archaic $250 billion automobile insurance market. They sought to create equitably priced insurance by eliminating pricing... View Details
Keywords: AI and Machine Learning; Technological Innovation; Equality and Inequality; Prejudice and Bias; Growth and Development Strategy; Customer Relationship Management; Price; Insurance Industry; Financial Services Industry
Ofek, Elie, and Alicia Dadlani. "LOOP: Driving Change in Auto Insurance Pricing." Harvard Business School Case 522-073, May 2022. (Revised June 2024.)
- May 2022
- Case
Timnit Gebru: 'SILENCED No More' on AI Bias and The Harms of Large Language Models
By: Tsedal Neeley and Stefani Ruper
Dr. Timnit Gebru—a leading artificial intelligence (AI) computer scientist and co-lead of Google’s Ethical AI team—was messaging with one of her colleagues when she saw the words: “Did you resign?? Megan sent an email saying that she accepted your resignation.” Heart... View Details
Neeley, Tsedal, and Stefani Ruper. "Timnit Gebru: 'SILENCED No More' on AI Bias and The Harms of Large Language Models." Harvard Business School Case 422-085, May 2022.
- May 2022 (Revised July 2022)
- Case
The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022
By: David B. Yoffie and Daniel Fisher
In 2022, after five years of pursuing a new "AI-first" strategy, Google had captured a sizeable share of the American and global markets for voice assistants. Google Assistant was used by hundreds of millions of users around the world, but Amazon retained the largest... View Details
Keywords: Strategy; Artificial Intelligence; Deep Learning; Voice Assistants; Smart Home; Market Share; Globalized Markets and Industries; Competitive Strategy; Digital Platforms; AI and Machine Learning; Technology Industry; United States
Yoffie, David B., and Daniel Fisher. "The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022." Harvard Business School Case 722-462, May 2022. (Revised July 2022.)
- May 2022
- Article
Coins for Bombs: The Predictive Ability of On-Chain Transfers for Terrorist Attacks
By: Dan Amiram, Evgeny Lyandres and Daniel Rabetti
This study examines whether we can learn from the behavior of blockchain-based transfers to predict the financing of terrorist attacks. We exploit blockchain transaction transparency to map millions of transfers for hundreds of large on-chain service providers. The... View Details
Keywords: Blockchain; Bitcoin; Accounting; AI and Machine Learning; National Security; Governing Rules, Regulations, and Reforms
Amiram, Dan, Evgeny Lyandres, and Daniel Rabetti. "Coins for Bombs: The Predictive Ability of On-Chain Transfers for Terrorist Attacks." Journal of Accounting Research 60, no. 2 (May 2022): 427–466.
- Article
Developing a Digital Mindset: How to Lead Your Organization into the Age of Data, Algorithms, and AI
By: Tsedal Neeley and Paul Leonardi
Learning new technological skills is essential for digital transformation. But it is not enough. Employees must be motivated to use their skills to create new opportunities. They need a digital mindset: a set of attitudes and behaviors that enable people and... View Details
Keywords: Machine Learning; AI; Information Technology; Transformation; Competency and Skills; Employees; Technology Adoption; Leading Change; Digital Transformation
Neeley, Tsedal, and Paul Leonardi. "Developing a Digital Mindset: How to Lead Your Organization into the Age of Data, Algorithms, and AI." S22032. Harvard Business Review 100, no. 3 (May–June 2022): 50–55.
- 2022
- Book
The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI
By: Paul Leonardi and Tsedal Neeley
The pressure to "be digital" has never been greater, but you can meet the challenge.
The digital revolution is here, changing how work gets done, how industries are structured, and how people from all walks of life work, behave, and relate to each other. To thrive... View Details
Keywords: Digital; Artificial Intelligence; Big Data; Digital Transformation; Technological Innovation; Transformation; Learning; Competency and Skills
Leonardi, Paul, and Tsedal Neeley. The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI. Boston, MA: Harvard Business Review Press, 2022.
- March 2022 (Revised January 2025)
- Technical Note
Prediction & Machine Learning
By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation; AI and Machine Learning
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Technical Note 622-101, March 2022. (Revised January 2025.)