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- September 2023 (Revised January 2024)
- Case
AI21 Labs in 2023: Strategy for Generative AI
By: David Yoffie, Orna Dan and Elena Corsi
Israeli generative artificial intelligence company AI21 Labs was founded in 2017 to realize the vision of true machine intelligence. It sought to reinvent writing and reading and in 2020 it launched Wordtune, an app using GenAI software to offer alternate text... View Details
Keywords: Decision Making; AI and Machine Learning; Innovation Strategy; Growth and Development Strategy; Applications and Software; Competitive Strategy; Technology Industry; Israel
Yoffie, David, Orna Dan, and Elena Corsi. "AI21 Labs in 2023: Strategy for Generative AI." Harvard Business School Case 724-383, September 2023. (Revised January 2024.)
- 2024
- Working Paper
The Crowdless Future? Generative AI and Creative Problem Solving
The rapid advances in generative artificial intelligence (AI) open up attractive opportunities for creative problem-solving through human-guided AI partnerships. To explore this potential, we initiated a crowdsourcing challenge focused on sustainable, circular economy... View Details
Keywords: Large Language Models; Crowdsourcing; Generative Ai; Creative Problem-solving; Organizational Search; AI-in-the-loop; Prompt Engineering; AI and Machine Learning; Innovation and Invention
Boussioux, Léonard, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim R. Lakhani. "The Crowdless Future? Generative AI and Creative Problem Solving." Harvard Business School Working Paper, No. 24-005, July 2023. (Revised July 2024.)
- August 2023
- Article
Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel
By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use... View Details
Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel." Nature Machine Intelligence 5, no. 8 (August 2023): 873–883.
- August 29, 2023
- Article
The Fragility of Artists’ Reputations from 1795 to 2020
By: Letian Zhang, Mitali Banerjee, Shinan Wang and Zhuoqiao Hong
This study explores the longevity of artistic reputation. We empirically examine whether artists are more- or less-venerated after their death. We construct a massive historical corpus spanning 1795 to 2020 and build separate word-embedding models for each five-year... View Details
Zhang, Letian, Mitali Banerjee, Shinan Wang, and Zhuoqiao Hong. "The Fragility of Artists’ Reputations from 1795 to 2020." Proceedings of the National Academy of Sciences 120, no. 35 (August 29, 2023).
- 2023
- Working Paper
Beyond the Hype: Unveiling the Marginal Benefits of 3D Virtual Tours in Real Estate
By: Mengxia Zhang and Isamar Troncoso
3D virtual tours (VTs) have become a popular digital tool in real estate platforms, enabling potential buyers to virtually walk through the houses they search for online. In this paper, we study home sellers’ adoption of VTs and the VTs’ relative benefits compared to... View Details
Zhang, Mengxia, and Isamar Troncoso. "Beyond the Hype: Unveiling the Marginal Benefits of 3D Virtual Tours in Real Estate." Harvard Business School Working Paper, No. 24-003, July 2023.
- July 2023
- Article
Negative Expressions Are Shared More on Twitter for Public Figures Than for Ordinary Users
By: Jonas P. Schöne, David Garcia, Brian Parkinson and Amit Goldenberg
Social media users tend to produce content that contains more positive than negative emotional language. However, negative emotional language is more likely to be shared. To understand why, research has thus far focused on psychological processes associated with... View Details
Schöne, Jonas P., David Garcia, Brian Parkinson, and Amit Goldenberg. "Negative Expressions Are Shared More on Twitter for Public Figures Than for Ordinary Users." PNAS Nexus 2, no. 7 (July 2023).
- 2024
- Working Paper
Operational Impact of Communication Channels: Evidence from Last-Mile Delivery Services
By: Natalie Epstein, Santiago Gallino and Antonio Moreno
Communication channels are often used to improve customer satisfaction and behavior. This paper studies
how they can be used to enhance operational performance.
We partner with a last-mile delivery company and, through natural and field experiments, explore... View Details
We partner with a last-mile delivery company and, through natural and field experiments, explore... View Details
Epstein, Natalie, Santiago Gallino, and Antonio Moreno. "Operational Impact of Communication Channels: Evidence from Last-Mile Delivery Services." Working Paper, August 2024.
- 2024
- Working Paper
Using LLMs for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have rapidly gained popularity as labor-augmenting
tools for programming, writing, and many other processes that benefit from quick text
generation. In this paper we explore the uses and benefits of LLMs for researchers and
practitioners... View Details
Keywords: Large Language Model; Research; AI and Machine Learning; Analysis; Customers; Consumer Behavior; Technology Industry; Information Technology Industry
Brand, James, Ayelet Israeli, and Donald Ngwe. "Using LLMs for Market Research." Harvard Business School Working Paper, No. 23-062, April 2023. (Revised July 2024.)
- 2023
- Working Paper
Sending Signals: Strategic Displays of Warmth and Competence
By: Bushra S. Guenoun and Julian J. Zlatev
Using a combination of exploratory and confirmatory approaches, this research examines how
people signal important information about themselves to others. We first train machine learning
models to assess the use of warmth and competence impression management... View Details
Keywords: AI and Machine Learning; Personal Characteristics; Perception; Interpersonal Communication
Guenoun, Bushra S., and Julian J. Zlatev. "Sending Signals: Strategic Displays of Warmth and Competence." Harvard Business School Working Paper, No. 23-051, February 2023.
- January 2023
- Teaching Note
Duolingo: Teaching Languages to the Masses
By: Youngme Moon
Teaching Note for HBS Case 323-016. At the time the case is written, Duolingo is the most popular language learning service in the world. The company has more than 40 million monthly active users, and the company’s total annual revenue has reached $250 million a year.... View Details
- January 2023 (Revised November 2024)
- Case
ELCA's Series A
Vu Phong and Xavier Silva co-founded ELCA to build proprietary software for their technology-enabled language learning tool. Since winning a prestigious venture contest in 2021, their number of registered users grew rapidly, as did the demand for new features like... View Details
Becker, Anke, Raymond Kluender, and William R. Kerr. "ELCA's Series A." Harvard Business School Case 823-079, January 2023. (Revised November 2024.)
- November 2022
- Article
A Language-Based Method for Assessing Symbolic Boundary Maintenance between Social Groups
By: Anjali M. Bhatt, Amir Goldberg and Sameer B. Srivastava
When the social boundaries between groups are breached, the tendency for people to erect and maintain symbolic boundaries intensifies. Drawing on extant perspectives on boundary maintenance, we distinguish between two strategies that people pursue in maintaining... View Details
Keywords: Culture; Machine Learning; Natural Language Processing; Symbolic Boundaries; Organizations; Boundaries; Social Psychology; Interpersonal Communication; Organizational Culture
Bhatt, Anjali M., Amir Goldberg, and Sameer B. Srivastava. "A Language-Based Method for Assessing Symbolic Boundary Maintenance between Social Groups." Sociological Methods & Research 51, no. 4 (November 2022): 1681–1720.
- July 2022 (Revised February 2023)
- Case
Duolingo: Teaching Languages to the Masses
By: Youngme Moon
In early 2022, the CEO of Duolingo—the world's most popular language learning app—is faced with a number of questions involving the company's monetization and growth strategy. View Details
Moon, Youngme. "Duolingo: Teaching Languages to the Masses." Harvard Business School Case 323-016, July 2022. (Revised February 2023.)
- 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.
- 2022
- Working Paper
Rethinking Explainability as a Dialogue: A Practitioner's Perspective
By: Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan and Sameer Singh
As practitioners increasingly deploy machine learning models in critical domains such as healthcare, finance, and policy, it becomes vital to ensure that domain experts function effectively alongside these models. Explainability is one way to bridge the gap between... View Details
Keywords: Natural Language Conversations; AI and Machine Learning; Experience and Expertise; Interactive Communication; Business and Stakeholder Relations
Lakkaraju, Himabindu, Dylan Slack, Yuxin Chen, Chenhao Tan, and Sameer Singh. "Rethinking Explainability as a Dialogue: A Practitioner's Perspective." Working Paper, 2022.
- 2022
- Working Paper
TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations
By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet they have become more complex and harder to understand. To address this issue, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use explainability... View Details
Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations." Working Paper, 2022.
- December 2021
- Article
Left- and Right-Leaning News Organizations Use Negative Emotional Content and Elicit User Engagement Similarly
By: Andrea Bellovary, Nathaniel Young and Amit Goldenberg
Negativity has historically dominated news content; however, little research has examined how news organizations use affect on social media, where content is generally positive. In the current project we ask a few questions: Do news organizations on Twitter use... View Details
Keywords: Negative Press; Twitter; Political Affiliation; Affect; News; Media; Internet and the Web; Emotions; Perspective; Social Media
Bellovary, Andrea, Nathaniel Young, and Amit Goldenberg. "Left- and Right-Leaning News Organizations Use Negative Emotional Content and Elicit User Engagement Similarly." Affective Science 2, no. 4 (December 2021): 391–396.
- December 2021
- Article
Negativity Spreads More Than Positivity on Twitter after Both Positive and Negative Political Situations
By: Jonas Paul Schöne, Brian Parkinson and Amit Goldenberg
What type of emotional language spreads further in political discourses on social media? Previous research has focused on situations that primarily elicited negative emotions, showing that negative language tended to spread further. The current project extends existing... View Details
Keywords: Negative Emotions; Emotional Influence; Emotional Resonance; Political Discourse; Emotion Contagion; Intergroup; Interactive Communication; Emotions; Government and Politics; Social Media
Schöne, Jonas Paul, Brian Parkinson, and Amit Goldenberg. "Negativity Spreads More Than Positivity on Twitter after Both Positive and Negative Political Situations." Affective Science 2, no. 4 (December 2021): 379–390.
- Article
Sizing Up Entrepreneurial Potential: Gender Differences in Communication and Investor Perceptions of Long-Term Growth and Scalability
By: Laura Huang, Priyanka D. Joshi, Cheryl J. Wakslak and Andy Wu
Female entrepreneurs have been found to face disadvantages as compared with male entrepreneurs, especially in acquiring the financial resources they need to sustain and grow their ventures. Across three studies, we examine how disparities in funding outcomes may be due... View Details
Huang, Laura, Priyanka D. Joshi, Cheryl J. Wakslak, and Andy Wu. "Sizing Up Entrepreneurial Potential: Gender Differences in Communication and Investor Perceptions of Long-Term Growth and Scalability." Academy of Management Journal 64, no. 3 (June 2021): 716–740.
- Article
Emotional Acknowledgment: How Verbalizing Others' Emotions Fosters Interpersonal Trust
By: Alisa Yu, Justin M. Berg and Julian Zlatev
People often respond to others’ emotions using verbal acknowledgment (e.g., “You seem upset”). Yet, little is known about the relational benefits and risks of acknowledging others’ emotions in the workplace. We draw upon Costly Signaling Theory to posit how emotional... View Details
Keywords: Emotion; Costly Signaling; Interpersonal Trust; Emotional Valence; Interpersonal Relationships; Empathic Accuracy; Emotions; Relationships; Trust; Interpersonal Communication
Yu, Alisa, Justin M. Berg, and Julian Zlatev. "Emotional Acknowledgment: How Verbalizing Others' Emotions Fosters Interpersonal Trust." Organizational Behavior and Human Decision Processes 164 (May 2021): 116–135.