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  • 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 marketing researchers and...  View Details
Keywords: Research; AI and Machine Learning; Analysis; Customers; Technology Industry; Information Technology Industry
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  • 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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  • 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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  • 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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  • 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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  • 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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  • 2022
  • 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 importance to modern businesses. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms) as the primary driver of model quality, the value of tools...  View Details
Keywords: Analytics and Data Science
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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 2022
  • Working Paper

The Evolution of ESG Reports and the Role of Voluntary Standards
By: Ethan Rouen, Kunal Sachdeva and Aaron Yoon
We examine the evolution of ESG reports of S&P 500 firms from 2010 to 2021. The percentage of firms releasing these voluntary disclosures increased from 35% to 86% during this period, although the length of these documents experienced more modest growth. Using a...  View Details
Keywords: Voluntary Disclosure; Textual Analysis; Modeling And Analysis; Corporate Social Responsibility and Impact; AI and Machine Learning; Accounting
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  • 2022
  • Working Paper

When Less Is More: Using Short-term Signals to Overcome Systematic Bias in Long-run Targeting
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response. Doing so requires firms to identify differences in customer sensitivity, which they often obtain using uplift modeling (i.e., heterogeneous treatment effect...  View Details
Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing
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  • October 2022 (Revised December 2022)
  • Case

SMART: AI and Machine Learning for Wildlife Conservation
By: Brian Trelstad and Bonnie Yining Cao
Spatial Monitoring and Reporting Tool (SMART), a set of software and analytical tools designed for the purpose of wildlife conservation, had demonstrated significant improvements in patrol coverage, with some observed reductions in poaching and contributing to wildlife...  View Details
Keywords: Business and Government Relations; Emerging Markets; Technology Adoption; Strategy; Management; Ethics; Social Enterprise; AI and Machine Learning; Analytics and Data Science; Natural Environment; Technology Industry; Cambodia; United States; Africa
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  • 2022
  • Working Paper

Communicating Corporate Culture in Labor Markets: Evidence from Job Postings
By: Joseph Pacelli, Tianshuo Shi and Yuan Zou
A company’s culture represents one of the most important factors that job seekers consider. In this study, we examine how firms craft their job postings to convey their cultures and whether doing so helps attract employees. We utilize state-of-the art machine learning...  View Details
Keywords: Corporate Culture Significance; Labor Markets; Disclosure; Organizational Culture; Recruitment; Talent and Talent Management
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  • October–December 2022
  • Article

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed...  View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
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