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All HBS Web
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- Faculty Publications (156)
- 2023
- Article
On the Impact of Actionable Explanations on Social Segregation
By: Ruijiang Gao and Himabindu Lakkaraju
As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research...
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Gao, Ruijiang, and Himabindu Lakkaraju. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.
- August 2023
- Case
Kariyer.net: Recruiting AI
By: Shunyuan Zhang, Fares Khrais and Namrata Arora
In 2017, Fatih Uysal (AMP 2021) became CEO of Kariyer.net. By then, the business was already the industry leading online job board in Turkey. However, faced with stalling growth, a turbulent macroenvironment, and growing competition from international players, Uysal...
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Keywords:
Online Technology;
Marketing;
Websites;
Artificial Intelligence;
Innovation;
Two-sided Platforms;
Internet and the Web;
Product Launch;
Product Positioning;
Job Search;
Employment;
Transformation;
Volatility;
Innovation and Invention;
Disruptive Innovation;
Management Practices and Processes;
Business Growth and Maturation;
Competitive Strategy;
Business Startups;
Talent and Talent Management;
Cost vs Benefits;
Macroeconomics;
Corporate Entrepreneurship;
Emerging Markets;
Digital Platforms;
Employment Industry;
Information Technology Industry;
Technology Industry;
Middle East;
Turkey
Zhang, Shunyuan, Fares Khrais, and Namrata Arora. "Kariyer.net: Recruiting AI." Harvard Business School Case 524-014, August 2023.
- 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...
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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...
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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.
- 2023
- Article
Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten
By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an...
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Keywords:
Analytics and Data Science;
AI and Machine Learning;
Decision Making;
Governing Rules, Regulations, and Reforms
Lakkaraju, Himabindu, Satyapriya Krishna, and Jiaqi Ma. "Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 17808–17826.
- 2023
- Other Unpublished Work
Visions of Vision Pro
Daily ups and downs of the market are often driven by changes in interest-rate expectations and investor risk aversion. But over the long run, it's often technological change that is the primary driver of value. A decade ago, Tyler Cowen argued in his book The Great...
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Cohen, Randolph B. "Visions of Vision Pro." August 2023. (LinkedIn Articles.)
- July 2023 (Revised July 2023)
- Background Note
Generative AI Value Chain
By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are...
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Keywords:
AI;
Artificial Intelligence;
Model;
Hardware;
Data Centers;
AI and Machine Learning;
Applications and Software;
Analytics and Data Science;
Value
Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
- 2023
- Working Paper
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false...
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Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
- June 2023
- Case
Verve Therapeutics: Taking DNA Editing to Heart
By: Shikhar Ghosh and Shweta Bagai
Verve Therapeutics, a public biotech company based in Boston, created a novel approach to addressing cardiovascular disease (CVD) - a leading cause of deaths globally. The company's approach was a single shot treatment to permanently lower cholesterol, thus reducing...
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Keywords:
AI;
Genetic Engineering;
Medicine;
Health Care and Treatment;
Genetics;
Innovation Strategy;
Business and Stakeholder Relations;
Medical Specialties;
Innovation and Invention;
Entrepreneurship;
Biotechnology Industry
Ghosh, Shikhar, and Shweta Bagai. "Verve Therapeutics: Taking DNA Editing to Heart." Harvard Business School Case 823-113, June 2023.
- 2023
- Article
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju
As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means...
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Pawelczyk, Martin, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci, and Himabindu Lakkaraju. "Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse." Proceedings of the International Conference on Learning Representations (ICLR) (2023).
- May 2023
- Article
Where Sales Technology (Really) Helps
Interest in Sales Enablement (SE), the catch-all term for attempts to increase sales productivity with AI and other technologies, is driven by multiple factors. One is the declining costs of the tools. Also, selling is now data-hungry work and not just in tech sectors....
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- 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...
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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.)
- April 2023 (Revised February 2024)
- Case
AI Wars
By: Andy Wu, Matt Higgins, Miaomiao Zhang and Hang Jiang
In February 2024, the world was looking to Google to see what the search giant and long-time putative technical leader in artificial intelligence (AI) would do to compete in the massively hyped technology of generative AI. Over a year ago, OpenAI released ChatGPT, a...
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Keywords:
AI;
Artificial Intelligence;
AI and Machine Learning;
Technology Adoption;
Competitive Strategy;
Technological Innovation
Wu, Andy, Matt Higgins, Miaomiao Zhang, and Hang Jiang. "AI Wars." Harvard Business School Case 723-434, April 2023. (Revised February 2024.)
- 2023
- Working Paper
Feature Importance Disparities for Data Bias Investigations
By: Peter W. Chang, Leor Fishman and Seth Neel
It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection...
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Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
- April 2023
- Article
On the Privacy Risks of Algorithmic Recourse
By: Martin Pawelczyk, Himabindu Lakkaraju and Seth Neel
As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely beneficial to affected...
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Pawelczyk, Martin, Himabindu Lakkaraju, and Seth Neel. "On the Privacy Risks of Algorithmic Recourse." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 206 (April 2023).
- March–April 2023
- Article
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in...
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Keywords:
Price;
Demand and Consumers;
AI and Machine Learning;
Investment Return;
Entertainment and Recreation Industry;
Sports Industry
Alley, Michael, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li, and Georgia Perakis. "Pricing for Heterogeneous Products: Analytics for Ticket Reselling." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 409–426.
- 2023
- Working Paper
The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities
By: David S. Scharfstein and Sergey Chernenko
We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement bias in...
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Keywords:
Racial Disparity;
Paycheck Protection Program;
Measurement Error;
AI and Machine Learning;
Race;
Measurement and Metrics;
Equality and Inequality;
Prejudice and Bias;
Forecasting and Prediction;
Outcome or Result
Scharfstein, David S., and Sergey Chernenko. "The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities." Working Paper, April 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...
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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–February 2023
- Article
Forecasting COVID-19 and Analyzing the Effect of Government Interventions
By: Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis and Dimitris Bertsimas
We developed DELPHI, a novel epidemiological model for predicting detected cases and deaths in the prevaccination era of the COVID-19 pandemic. The model allows for underdetection of infections and effects of government interventions. We have applied DELPHI across more...
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Keywords:
COVID-19 Pandemic;
Epidemics;
Analytics and Data Science;
Health Pandemics;
AI and Machine Learning;
Forecasting and Prediction
Li, Michael Lingzhi, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis, and Dimitris Bertsimas. "Forecasting COVID-19 and Analyzing the Effect of Government Interventions." Operations Research 71, no. 1 (January–February 2023): 184–201.
- 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...
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Keywords:
Information Infrastructure;
Disruptive Innovation;
Innovation and Invention;
Marketing Strategy;
Marketing Channels;
Customers;
Technology Industry;
United States;
California
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.)