Filter Results
:
(49)
Show Results For
-
All HBS Web
(789)
- Faculty Publications (49)
Show Results For
-
All HBS Web
(789)
- Faculty Publications (49)
Page 1 of
49
Results
→
- February 2024
- Article
Conveying and Detecting Listening in Live Conversation
By: Hanne Collins, Julia A. Minson, Ariella S. Kristal and Alison Wood Brooks
Across all domains of human social life, positive perceptions of conversational listening (i.e., feeling heard) predict well-being, professional success, and interpersonal flourishing. But a fundamental question remains: Are perceptions of listening accurate? Prior...
View Details
Collins, Hanne, Julia A. Minson, Ariella S. Kristal, and Alison Wood Brooks. "Conveying and Detecting Listening in Live Conversation." Journal of Experimental Psychology: General 153, no. 2 (February 2024): 473–494.
- 2024
- Working Paper
The Value of Open Source Software
By: Manuel Hoffmann, Frank Nagle and Yanuo Zhou
The value of a non-pecuniary (free) product is inherently difficult to assess. A pervasive
example is open source software (OSS), a global public good that plays a vital role in the economy
and is foundational for most technology we use today. However, it is...
View Details
Hoffmann, Manuel, Frank Nagle, and Yanuo Zhou. "The Value of Open Source Software." Harvard Business School Working Paper, No. 24-038, January 2024.
- 2024
- Conference Paper
Quantifying Uncertainty in Natural Language Explanations of Large Language Models
By: Himabindu Lakkaraju, Sree Harsha Tanneru and Chirag Agarwal
Large Language Models (LLMs) are increasingly used as powerful tools for several
high-stakes natural language processing (NLP) applications. Recent prompting
works claim to elicit intermediate reasoning steps and key tokens that serve as
proxy explanations for LLM...
View Details
Lakkaraju, Himabindu, Sree Harsha Tanneru, and Chirag Agarwal. "Quantifying Uncertainty in Natural Language Explanations of Large Language Models." Paper presented at the Society for Artificial Intelligence and Statistics, 2024.
- 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
Krishna, Satyapriya, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, and Himabindu Lakkaraju. "Post Hoc Explanations of Language Models Can Improve Language Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 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
- Working Paper
Toward a Better Understanding of Open Ecosystems: Implications for Policymakers
By: Feng Zhu and Carmelo Cennamo
The digital realm is undergoing a significant transformation, marked by the emergence of platform
business models and the concept of open ecosystems. This paper delves into the intricate nature of
ecosystem openness, underscoring the point that the openness of...
View Details
Zhu, Feng, and Carmelo Cennamo. "Toward a Better Understanding of Open Ecosystems: Implications for Policymakers." Working Paper, November 2023.
- October 2023
- Case
Fixie and Conversational AI Sidekicks
By: Jeffrey J. Bussgang and Carin-Isabel Knoop
In March 2023, Fixie Co-Founder and Chief Architect Matt Welsh and co-founders had the kind of meeting no founders want to have. The president of leading artificial intelligence (AI) research and deployment firm OpenAI, which had catapulted into fame with its ChatGPT...
View Details
Keywords:
Large Language Model;
Entrepreneurship;
Decision Choices and Conditions;
AI and Machine Learning;
Technological Innovation;
Competitive Strategy;
Technology Industry;
United States
Bussgang, Jeffrey J., and Carin-Isabel Knoop. "Fixie and Conversational AI Sidekicks." Harvard Business School Case 824-037, October 2023.
- October–December 2023
- Article
A Practical Guide to Conversation Research: How to Study What People Say to Each Other
By: Michael Yeomans, Katelynn Boland, Hanne K. Collins, Nicole Abi-Esber and Alison Wood Brooks
Conversation—a verbal interaction between two or more people—is a complex, pervasive, and consequential human behavior. Conversations have been studied across many academic disciplines. However, advances in recording and analysis techniques over the last decade have...
View Details
Yeomans, Michael, Katelynn Boland, Hanne K. Collins, Nicole Abi-Esber, and Alison Wood Brooks. "A Practical Guide to Conversation Research: How to Study What People Say to Each Other." Advances in Methods and Practices in Psychological Science 6, no. 4 (October–December 2023).
- 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.
- 2023
- Working Paper
Operational Consequences of Customer Interaction Design: Evidence From Last-Mile Delivery Services
By: Natalie Epstein, Santiago Gallino and Antonio Moreno
Problem definition: Communication and customer interaction design have been used as elements to improve customer satisfaction and future purchasing behavior, but little is known about how they can be used as levers to improve operational...
View Details
Epstein, Natalie, Santiago Gallino, and Antonio Moreno. "Operational Consequences of Customer Interaction Design: Evidence From Last-Mile Delivery Services." Working Paper, May 2023.
- 2023
- Working Paper
Using GPT for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have quickly become popular 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...
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 GPT for Market Research." Harvard Business School Working Paper, No. 23-062, April 2023. (Revised July 2023.)
- March 2023
- Article
Authentic First Impressions Relate to Interpersonal, Social, and Entrepreneurial Success
By: David M. Markowitz, Maryam Kouchaki, Francesca Gino, Jeffrey T. Hancock and Ryan L. Boyd
This paper examines how verbal authenticity influences person perception. Our work combines human judgments and natural language processing to suggest verbal authenticity is a positive predictor of interpersonal interest (Study 1: 294 dyadic conversations), engagement...
View Details
Keywords:
Authenticity;
Impression Formation;
Natural Language Processing;
First Impressions;
Communication;
Perception;
Success
Markowitz, David M., Maryam Kouchaki, Francesca Gino, Jeffrey T. Hancock, and Ryan L. Boyd. "Authentic First Impressions Relate to Interpersonal, Social, and Entrepreneurial Success." Social Psychological & Personality Science 14, no. 2 (March 2023): 107–116.
- 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.
- 2023
- Working Paper
Summarizing the Mental Customer Journey
By: Julian De Freitas, Ahmet Uğuralp, Zeliha Uğuralp, Pechthida Kim and Tomer Ullman
How do consumers summarize and act on their experiences, as when deciding whether an interaction with a firm was satisfying and whether to buy from it? Previous work on the summary of continuous experiences has tended to focus on a handful of experience patterns and...
View Details
Keywords:
Customer Experience;
Customer Journey;
Natural Language Processing;
Summarization;
Customer Satisfaction;
Outcome or Result;
Decision Choices and Conditions
De Freitas, Julian, Ahmet Uğuralp, Zeliha Uğuralp, Pechthida Kim, and Tomer Ullman. "Summarizing the Mental Customer Journey." Harvard Business School Working Paper, No. 23-038, January 2023.
- 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.
- 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
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.