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      • Faculty Publications  (222)

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      • April 12, 2023
      • Article

      Using AI to Adjust Your Marketing and Sales in a Volatile World

      By: Das Narayandas and Arijit Sengupta
      Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer...  View Details
      Keywords: Forecasting and Prediction; AI and Machine Learning; Consumer Behavior; Technology Adoption; Competitive Advantage
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      Narayandas, Das, and Arijit Sengupta. "Using AI to Adjust Your Marketing and Sales in a Volatile World." Harvard Business Review Digital Articles (April 12, 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 practitioners who...  View Details
      Keywords: Large Language Model; Research; AI and Machine Learning; Analysis; Customers; Consumer Behavior; Technology Industry; Information Technology Industry
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      Brand, James, Ayelet Israeli, and Donald Ngwe. "Using GPT for Market Research." Harvard Business School Working Paper, No. 23-062, April 2023.
      • April 2023
      • Case

      Fizzy Fusion: When Data-Driven Decision Making Failed

      By: Michael Parzen, Eddie Lin, Douglas Ng and Jessie Li
      This is a case about a fictional New York beverage company called Fizzy Fusion. The business is facing supply chain and inventory management challenges with its new product, SparklingSip. Despite seeking help from a data science consulting firm, the machine learning...  View Details
      Keywords: Supply Chain Management; Production; Risk and Uncertainty; Analytics and Data Science; Food and Beverage Industry
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      Parzen, Michael, Eddie Lin, Douglas Ng, and Jessie Li. "Fizzy Fusion: When Data-Driven Decision Making Failed." Harvard Business School Case 623-071, April 2023.
      • March 2023
      • Teaching Note

      VideaHealth: Building the AI Factory

      By: Karim R. Lakhani
      Teaching Note for HBS Case No. 621-021. The case “VideaHealth: Building the AI Factory” examines the creation of dental startup VideaHealth (Videa) and the development of its artificial intelligence (AI)-led business strategy through the eyes of founder and CEO Florian...  View Details
      Keywords: AI and Machine Learning; Applications and Software; Business Model; Marketing Strategy; Product Development; Health Industry; Technology Industry
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      Lakhani, Karim R. "VideaHealth: Building the AI Factory." Harvard Business School Teaching Note 623-073, March 2023.
      • 2023
      • Working Paper

      Translating Information into Action: A Public Health Experiment in Bangladesh

      By: Reshmaan Hussam, Kailash Pandey, Abu Shonchoy and Chikako Yamauchi
      While models of technology adoption posit learning as the basis of behavior change, information campaigns in public health frequently fail to change behavior. We design an information campaign embedding hand-hygiene edutainment within popular dramas using mobile...  View Details
      Keywords: Handwashing; Public Health; Health; Information; Behavior; Change
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      Hussam, Reshmaan, Kailash Pandey, Abu Shonchoy, and Chikako Yamauchi. "Translating Information into Action: A Public Health Experiment in Bangladesh." Working Paper, February 2023.
      • 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
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      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.
      • 2022
      • Working Paper

      Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing

      By: Kirk Bansak and Elisabeth Paulson
      This study proposes two new dynamic assignment algorithms to match refugees and asylum seekers to geographic localities within a host country. The first, currently implemented in a multi-year pilot in Switzerland, seeks to maximize the average predicted employment...  View Details
      Keywords: AI and Machine Learning; Refugees; Mathematical Methods
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      Bansak, Kirk, and Elisabeth Paulson. "Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing." Harvard Business School Working Paper, No. 23-048, January 2022.
      • January 2023 (Revised April 2023)
      • Case

      Cobalt Robotics: Scaling Workplace Robotics

      By: Jeffrey F. Rayport, Nicole Tempest Keller and Kyung Keun Park
      Founded in 2016, Cobalt Robotics, based in Fremont, California, was a Robot-as-a-Service (RaaS) company that built autonomous workplace robots that were designed to replace or supplement human security guards. Outfitted with over 60 sensors, Cobalt robots patrolled...  View Details
      Keywords: Information Infrastructure; Disruptive Innovation; Innovation and Invention; Marketing Strategy; Marketing Channels; Customers; Technology Industry; United States; California
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      Rayport, Jeffrey F., Nicole Tempest Keller, and Kyung Keun Park. "Cobalt Robotics: Scaling Workplace Robotics." Harvard Business School Case 823-096, January 2023. (Revised April 2023.)
      • January 2023
      • Case

      Replika: Embodying AI

      By: Shikhar Ghosh, Shweta Bagai and Marilyn Morgan Westner
      Replika was a virtual AI companion that provided a way for people to process their emotions, build connections in a safe environment, and get through periods of loneliness. The chatbot fulfilled a user's need for a friend, romantic partner, or purely an emotional...  View Details
      Keywords: AI; AI and Machine Learning; Applications and Software; Human Needs; California
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      Ghosh, Shikhar, Shweta Bagai, and Marilyn Morgan Westner. "Replika: Embodying AI." Harvard Business School Case 823-090, January 2023.
      • 2023
      • Article

      Experimental Evaluation of Individualized Treatment Rules

      By: Kosuke Imai and Michael Lingzhi Li
      The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a...  View Details
      Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning
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      Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
      • December 2022 (Revised February 2023)
      • Case

      Akooda: Charging Toward Operational Intelligence

      By: Christopher T. Stanton and Mel Martin
      The Akooda case describes the challenges confronting founder and CEO Yuval Gonczarowski (MBA ‘17) in 2022 as he attempts to boost sales. Launched in November 2020, Akooda was an AI company that mined 20 different sources of digital data, from tools like Slack, Google...  View Details
      Keywords: Data Mining; Productivity; Monitoring; Data Analysis; AI and Machine Learning; Knowledge Management; Operations; Problems and Challenges; Employee Relationship Management; Information Technology Industry; Technology Industry; Information Industry; Boston; Israel
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      Stanton, Christopher T., and Mel Martin. "Akooda: Charging Toward Operational Intelligence." Harvard Business School Case 823-018, December 2022. (Revised February 2023.)
      • 2023
      • Working Paper

      Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development

      By: Daniel Yue, Paul Hamilton and Iavor Bojinov
      Predictive model development is understudied despite its centrality in modern artificial intelligence and machine learning business applications. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms)...  View Details
      Keywords: Analytics and Data Science
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      Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. (Revised April 2023.)
      • 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
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      Srinivas, Suraj, Kyle Matoba, Himabindu Lakkaraju, and Francois Fleuret. "Efficiently Training Low-Curvature Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) (2022).
      • 2022
      • Working Paper

      Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence

      By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
      Even if algorithms make better predictions than humans on average, humans may sometimes have “private” information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by...  View Details
      Keywords: Cognitive Biases; Algorithm Transparency; Forecasting and Prediction; Behavior; AI and Machine Learning; Analytics and Data Science; Cognition and Thinking
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      Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence." Working Paper, December 2022.
      • 2022
      • Working Paper

      The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives

      By: Ariel Dora Stern
      For those who follow health and technology news, it is difficult to go more than a few days without reading about a compelling new application of Artificial Intelligence (AI) to health care. AI has myriad applications in medicine and its adjacent industries, with...  View Details
      Keywords: AI and Machine Learning; Health Care and Treatment; Governing Rules, Regulations, and Reforms; Technological Innovation; Medical Devices and Supplies Industry
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      Stern, Ariel Dora. "The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives." NBER Working Paper Series, No. 30639, December 2022.
      • November 2022 (Revised December 2022)
      • 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
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      De Freitas, Julian, and Nicole Tempest Keller. "Replika AI: Monetizing a Chatbot." Harvard Business School Case 523-016, November 2022. (Revised December 2022.)
      • November 2022 (Revised January 2023)
      • Case

      Hugging Face: Serving AI on a Platform

      By: Shane Greenstein, Daniel Yue, Kerry Herman and Sarah Gulick
      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
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      Greenstein, Shane, Daniel Yue, Kerry Herman, and Sarah Gulick. "Hugging Face: Serving AI on a Platform." Harvard Business School Case 623-026, November 2022. (Revised January 2023.)
      • 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
      Keywords: AI and Machine Learning; Research and Development; Demand and Consumers
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      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 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
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      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.
      • November–December 2022
      • Article

      Can AI Really Help You Sell?

      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
      Keywords: Sales; AI and Machine Learning; Customers
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      Dickie, Jim, Boris Groysberg, Benson P. Shapiro, and Barry Trailer. "Can AI Really Help You Sell?" Harvard Business Review (November–December 2022): 120–129.
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