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  • All HBS Web  (725)
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    • Research  (336)
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Page 1 of 725 Results →
  • 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
Keywords: Natural Language Conversations; Predictive Models; AI and Machine Learning
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Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations." Working Paper, 2022.
  • 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
Keywords: Large Language Model; AI and Machine Learning
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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.
  • 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
Keywords: AI and Machine Learning; Technological Innovation; Technology Adoption
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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.
  • Article

Conversational Receptiveness: Expressing Engagement with Opposing Views

By: M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino
We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then... View Details
Keywords: Receptiveness; Natural Language Processing; Disagreement; Interpersonal Communication; Relationships; Conflict Management
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Yeomans, M., J. Minson, H. Collins, H. Chen, and F. Gino. "Conversational Receptiveness: Expressing Engagement with Opposing Views." Organizational Behavior and Human Decision Processes 160 (September 2020): 131–148.
  • 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
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Lakkaraju, Himabindu, Dylan Slack, Yuxin Chen, Chenhao Tan, and Sameer Singh. "Rethinking Explainability as a Dialogue: A Practitioner's Perspective." Working Paper, 2022.
  • 2020
  • Working Paper

Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation

By: Michael Yeomans and Alison Wood Brooks
Although most humans engage in conversations constantly throughout their lives, conversational mistakes are commonplace— interacting with others is difficult, and conversation re-quires quick, relentless perspective-taking and decision making. For example: during every... View Details
Keywords: Natural Language Processing; Interpersonal Communication; Perspective; Decision Making; Perception
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Yeomans, Michael, and Alison Wood Brooks. "Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation." Harvard Business School Working Paper, No. 20-077, February 2020.
  • August 2017 (Revised December 2018)
  • Case

Tamarin App: Natural Language Processing

By: Srikant M. Datar and Caitlin N. Bowler
In this case, students explore the challenges of using sentiment analysis to monitor and understand public perception around a software application, Tamarin SEO App. Technical topics include building a filtering classifier using naive Bayes and sentiment analysis This... View Details
Keywords: Data Science; Branding; Data Analytics; Analytics and Data Science; Brands and Branding; Analysis; Perception; Planning
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Datar, Srikant M., and Caitlin N. Bowler. "Tamarin App: Natural Language Processing." Harvard Business School Case 118-015, August 2017. (Revised December 2018.)
  • September 2017
  • Article

It Doesn't Hurt to Ask: Question-asking Increases Liking

By: K. Huang, M. Yeomans, A.W. Brooks, J. Minson and F. Gino
Conversation is a fundamental human experience, one that is necessary to pursue intrapersonal and interpersonal goals across myriad contexts, relationships, and modes of communication. In the current research, we isolate the role of an understudied conversational... View Details
Keywords: Question-asking; Liking; Responsiveness; Conversation; Natural Language Processing; Interpersonal Communication; Behavior
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Huang, K., M. Yeomans, A.W. Brooks, J. Minson, and F. Gino. "It Doesn't Hurt to Ask: Question-asking Increases Liking." Journal of Personality and Social Psychology 113, no. 3 (September 2017): 430–452.
  • July 2020
  • Article

Tell It Like It Is: When Politically Incorrect Language Promotes Authenticity

By: J. Schroeder, M. Rosenblum and F. Gino
When a person’s language appears political—such as being politically correct or incorrect—it can influence fundamental impressions of him or her. Political correctness is “using language or behavior to seem sensitive to others’ feelings, especially those others who... View Details
Keywords: Language; Interpersonal Communication; Perception
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Schroeder, J., M. Rosenblum, and F. Gino. "Tell It Like It Is: When Politically Incorrect Language Promotes Authenticity." Journal of Personality and Social Psychology 119, no. 1 (July 2020): 75–103.
  • 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
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Bussgang, Jeffrey J., and Carin-Isabel Knoop. "Fixie and Conversational AI Sidekicks." Harvard Business School Case 824-037, October 2023.
  • 2025
  • Working Paper

Partisan Corporate Speech

By: William Cassidy and Elisabeth Kempf
We construct a novel measure of partisan corporate speech using natural language processing techniques and use it to establish three stylized facts. First, the volume of partisan corporate speech has risen sharply between 2012 and 2022. Second, this increase has... View Details
Keywords: Natural Language Processing; Perspective; Communication; Public Opinion; Business and Shareholder Relations; Trends
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Cassidy, William, and Elisabeth Kempf. "Partisan Corporate Speech." Harvard Business School Working Paper, No. 05-056, May 2025.
  • 20 Jan 2014
  • Research & Ideas

Language Wars Divide Global Companies

"nearly all of them expressed feeling some anxiety about having access to appropriate words," particularly when the work became highly technical, conversations became emotional, or when the workers were tired. View Details
Keywords: by Kim Girard
  • January–February 2025
  • Article

The Double-Edged Sword of Exemplar Similarity

By: Majid Majzoubi, Eric Zhao, Tiona Zuzul and Greg Fisher
We investigate how a firm’s positioning relative to category exemplars shapes security analysts’ evaluations. Using a two-stage model of evaluation (initial screening and subsequent assessment), we propose that exemplar similarity enhances a firm’s recognizability and... View Details
Keywords: Natural Language Processing; Analytics and Data Science; Performance Evaluation
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Majzoubi, Majid, Eric Zhao, Tiona Zuzul, and Greg Fisher. "The Double-Edged Sword of Exemplar Similarity." Organization Science 36, no. 1 (January–February 2025): 121–144.
  • Research Summary

The Psychology of Conversation

By: Alison Wood Brooks

Conversation is a profound part of the human experience. To share our ideas, thoughts, and feelings with each other, we converse face to face and remotely—via phone, email, text message, online comment boards, and in contracts. Conversations form the bedrock of our... 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
Keywords: AI and Machine Learning; Performance Effectiveness
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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).
  • June 2016
  • Article

Understanding Online Hotel Reviews Through Automated Text Analysis

By: Shawn Mankad, Hyunjeong "Spring" Han, Joel Goh and Srinagesh Gavirneni
Customer reviews submitted at Internet travel portals are an important yet underexplored new resource in obtaining feedback on customer experience for the hospitality industry. These data are often voluminous and unstructured, presenting analytical challenges for... View Details
Keywords: Hotel Reviews; Natural Language Processing; Information Technology; Service Operations; Accommodations Industry; Moscow
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Mankad, Shawn, Hyunjeong "Spring" Han, Joel Goh, and Srinagesh Gavirneni. "Understanding Online Hotel Reviews Through Automated Text Analysis." Service Science 8, no. 2 (June 2016): 124–138.
  • Article

The Lives and Deaths of Jobs: Technical Interdependence and Survival in a Job Structure

By: Sharique Hasan, John-Paul Ferguson and Rembrand Koning
Prior work has considered the properties of individual jobs that make them more or less likely to survive in organizations. Yet little research examines how a job’s position within a larger job structure affects its life chances and thus the evolution of the... View Details
Keywords: Jobs; Natural Language Processing; Jobs and Positions; Organizational Structure
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Hasan, Sharique, John-Paul Ferguson, and Rembrand Koning. "The Lives and Deaths of Jobs: Technical Interdependence and Survival in a Job Structure." Organization Science 26, no. 6 (November–December 2015): 1665–1681.
  • February 2021
  • Article

Topic Classification of Electric Vehicle Consumer Experiences with Transformer-Based Deep Learning

By: Sooji Ha, Daniel J Marchetto, Sameer Dharur and Omar Isaac Asensio
The transportation sector is a major contributor to greenhouse gas (GHG) emissions and is a driver of adverse health effects globally. Increasingly, government policies have promoted the adoption of electric vehicles (EVs) as a solution to mitigate GHG emissions.... View Details
Keywords: Natural Language Processing; Analytics and Data Science; Environmental Sustainability; Infrastructure; Transportation; Policy
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Ha, Sooji, Daniel J Marchetto, Sameer Dharur, and Omar Isaac Asensio. "Topic Classification of Electric Vehicle Consumer Experiences with Transformer-Based Deep Learning." Art. 100195. Patterns 2, no. 2 (February 2021).
  • 10 Oct 2021
  • News

Nancy Koehn: The Nature of Leadership

  • 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
Keywords: Natural Language Processing; Reputation; Arts
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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).
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