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- 2024
- Working Paper
Lessons from an App Update at Replika AI: Identity Discontinuity in Human-AI Relationships
By: Julian De Freitas, Noah Castelo, Ahmet Uğuralp and Zeliha Uğuralp
Can consumers form deep emotional bonds with AI and be vested in AI identities over time? We
leverage a natural app-update event at Replika AI, a popular US-based AI companion, to shed
light on these questions. We find that customers feel closer to their AI companion... View Details
De Freitas, Julian, Noah Castelo, Ahmet Uğuralp, and Zeliha Uğuralp. "Lessons from an App Update at Replika AI: Identity Discontinuity in Human-AI Relationships." Harvard Business School Working Paper, No. 25-018, October 2024.
- September 2024
- Case
Xendit: Hiring for Growth
By: Jeffrey F. Rayport, Steve Castano, Quoc Anh Nguyen and Claire Wu
In 2019, Xendit, a growth-stage Southeast Asia (SEA) fintech venture based in Jakarta, was looking to hire a Head of Sales and Head of Product to lead its next phase of growth. Founded by Moses Lo and Tessa Wijaya, Xendit provided payment infrastructure, modeling... View Details
Keywords: Finance; Entrepreneurship; Jobs and Positions; Sales; Product; Financial Services Industry; Technology Industry; Southeast Asia; Indonesia; Philippines
Rayport, Jeffrey F., Steve Castano, Quoc Anh Nguyen, and Claire Wu. "Xendit: Hiring for Growth." Harvard Business School Case 825-046, September 2024.
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.
- 2024
- Working Paper
Don’t Expect Juniors to Teach Senior Professionals to Use Generative AI: Emerging Technology Risks and Novice AI Risk Mitigation Tactics
By: Katherine C. Kellogg, Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Fabrizio Dell'Acqua, Edward McFowland III, François Candelon and Karim R. Lakhani
The literature on communities of practice demonstrates that a proven way for senior professionals to upskill
themselves in the use of new technologies that undermine existing expertise is to learn from junior
professionals. It notes that juniors may be better able... View Details
Kellogg, Katherine C., Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Fabrizio Dell'Acqua, Edward McFowland III, François Candelon, and Karim R. Lakhani. "Don’t Expect Juniors to Teach Senior Professionals to Use Generative AI: Emerging Technology Risks and Novice AI Risk Mitigation Tactics." Harvard Business School Working Paper, No. 24-074, June 2024.
- 2023
- Article
M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models
By: Himabindu Lakkaraju, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai and Haoyi Xiong
While Explainable Artificial Intelligence (XAI) techniques have been widely studied to explain predictions made by deep neural networks, the way to evaluate the faithfulness of explanation results remains challenging, due to the heterogeneity of explanations for... View Details
Keywords: AI and Machine Learning
Lakkaraju, Himabindu, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai, and Haoyi Xiong. "M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 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
De Freitas, Julian, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum, and T. Ullman. "Self-Orienting in Human and Machine Learning." Nature Human Behaviour 7, no. 12 (December 2023): 2126–2139.
- 2023
- Working Paper
The Impact of Unionization on Consumer Perceptions of Service Quality: Evidence from Starbucks
By: Isamar Troncoso, Minkyung Kim, Ishita Chakraborty and SooHyun Kim
The US has seen a rise in union movements, but their effects on service industry marketing outcomes like customer satisfaction and perceptions of service quality remain understudied. In this paper, we empirically study the impact on customer satisfaction and... View Details
Keywords: Labor Unions; Customer Satisfaction; Perception; Public Opinion; Employees; Food and Beverage Industry
Troncoso, Isamar, Minkyung Kim, Ishita Chakraborty, and SooHyun Kim. "The Impact of Unionization on Consumer Perceptions of Service Quality: Evidence from Starbucks." Working Paper, 2023.
- 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
Feng, Flora, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan, and Cait Lamberton. "An AI Method to Score Celebrity Visual Potential from Human Faces." SSRN Working Paper Series, No. 4071188, November 2023.
- 18 Jul 2023
- Interview
Jeffrey Rayport on Product Market Fit, Profit Market Fit and Whiplash, and More
By: Jeffrey F. Rayport and Doug Levin
This episode of "Lessons from Startup Life" podcast features Jeffrey Rayport, Senior Lecturer of Business Administration at the Harvard Business School. Jeffrey specializes in teaching and researching growth-stage technology ventures and their scalability. Prior to... View Details
Keywords: Scaling And Growth; Start-up; Diversity; Equity; Inclusion; Technology; Business Startups; Product Marketing; Business Growth and Maturation
"Jeffrey Rayport on Product Market Fit, Profit Market Fit and Whiplash, and More." Lessons from a Startup Life (podcast), July 18, 2023.
- March 2023 (Revised January 2024)
- Case
Nigeria: Africa's Giant
"Nigeria: Africa’s Giant" delves into the economic development and state building record of Africa’s most populous country. Despite being one of the continent’s largest oil-exporters, Nigeria’s economy has been struggling, and poverty is widespread. The country’s... View Details
Keywords: Crime and Corruption; Developing Countries and Economies; Government Administration; Poverty; Africa; Nigeria
van Waijenburg, Marlous. "Nigeria: Africa's Giant." Harvard Business School Case 723-056, March 2023. (Revised January 2024.)
- 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–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.
- August 2022
- Article
What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features
By: Shunyuan Zhang, Dokyun Lee, Param Vir Singh and Kannan Srinivasan
We study how Airbnb property demand changed after the acquisition of verified images (taken by Airbnb’s photographers) and explore what makes a good image for an Airbnb property. Using deep learning and difference-in-difference analyses on an Airbnb panel dataset... View Details
Keywords: Sharing Economy; Airbnb; Property Demand; Computer Vision; Deep Learning; Image Feature Extraction; Content Engineering; Property; Marketing; Demand and Consumers
Zhang, Shunyuan, Dokyun Lee, Param Vir Singh, and Kannan Srinivasan. "What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features." Management Science 68, no. 8 (August 2022): 5644–5666.
- 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.)
- February 2022 (Revised September 2022)
- Case
InstaDeep: AI Innovation Born in Africa (A)
By: Shikhar Ghosh and Esel Çekin
Karim Beguir and Zohra Slim were the co-founders of InstaDeep, a deep tech startup focusing on artificial intelligence (AI) solutions. Instadeep was one of the few companies globally that were partnering with DeepMind, an AI subsidiary of Google [Alphabet Inc.].... View Details
Keywords: AI; Artificial Intelligence; Entrepreneurship; Operations; Business Subsidiaries; Brands and Branding; Innovation and Invention; Growth and Development Strategy; AI and Machine Learning; Technology Industry; Africa
Ghosh, Shikhar, and Esel Çekin. "InstaDeep: AI Innovation Born in Africa (A)." Harvard Business School Case 822-104, February 2022. (Revised September 2022.)
- February 2022 (Revised July 2022)
- Supplement
InstaDeep: AI Innovation Born in Africa (B)
By: Shikhar Ghosh and Esel Çekin
Karim Beguir and Zohra Slim were the co-founders of InstaDeep, a deep tech startup focusing on artificial intelligence (AI) solutions. Instadeep was one of the few companies globally that were partnering with DeepMind, an AI subsidiary of Google [Alphabet Inc.].... View Details
Keywords: AI; Artificial Intelligence; Entrepreneurship; Operations; Business Subsidiaries; Brands and Branding; Innovation and Invention; Growth and Development Strategy; AI and Machine Learning; Technology Industry; Africa
Ghosh, Shikhar, and Esel Çekin. "InstaDeep: AI Innovation Born in Africa (B)." Harvard Business School Supplement 822-105, February 2022. (Revised July 2022.)
- Article
Health Equity, Schooling Hesitancy, and the Social Determinants of Learning
By: Meira Levinson, Alan C. Geller, Joseph G. Allen and John D. Macomber
At least 62 million K-12 students in North America—disproportionately low-income children of color— have been physically out of school for over a year due to the COVID-19 pandemic. These children are at risk of significant academic, social, mental, and physical harm... View Details
Keywords: COVID-19; Public Health; Air Quality; Social Determinants Of Health; Schooling Hesitancy; Vaccine Hesitancy; Racial Injustice; Inequity; Inequality; Health Pandemics; Education; Health Care and Treatment; Policy; Race; Equality and Inequality
Levinson, Meira, Alan C. Geller, Joseph G. Allen, and John D. Macomber. "Health Equity, Schooling Hesitancy, and the Social Determinants of Learning." Art. 100032. Lancet Regional Health – Americas 2 (October 2021).
- October 2021
- Article
Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
By: Nicolas Padilla and Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details
Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Programs; Consumer Behavior; Analysis
Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Journal of Marketing Research (JMR) 58, no. 5 (October 2021): 981–1006.
- 2021
- Working Paper
Deep Learning for Two-Sided Matching
By: Sai Srivatsa Ravindranatha, Zhe Feng, Shira Li, Jonathan Ma, Scott Duke Kominers and David Parkes
We initiate the use of a multi-layer neural network to model two-sided matching and to explore the design space between strategy-proofness and stability. It is well known that both properties cannot be achieved simultaneously but the efficient frontier in this design... View Details
Keywords: Strategy-proofness; Deep Learning; Two-Sided Platforms; Marketplace Matching; Balance and Stability
Srivatsa Ravindranatha, Sai, Zhe Feng, Shira Li, Jonathan Ma, Scott Duke Kominers, and David Parkes. "Deep Learning for Two-Sided Matching." Working Paper, July 2021.
- June 2021
- Case
Bozoma Saint John: Leading with Authenticity and Urgency
By: Francesca Gino and Frances X. Frei
In this multimedia case, Bozoma Saint John recounts numerous defining moments from her childhood and work experiences. We learn what empowered and inspired her to be her authentic self, to be vulnerable and open to new experiences, to find commonality with others, to... View Details
Keywords: Biases; Personal Development and Career; Identity; Interests; Ethics; Values and Beliefs; Opportunities; Leadership Style; Diversity
Gino, Francesca, and Frances X. Frei. "Bozoma Saint John: Leading with Authenticity and Urgency." Harvard Business School Multimedia/Video Case 921-708, June 2021.