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Publications
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- 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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- July 2023
- Article
Negative Expressions Are Shared More on Twitter for Public Figures Than for Ordinary Users
By: Jonas P. Schöne, David Garcia, Brian Parkinson and Amit Goldenberg
Social media users tend to produce content that contains more positive than negative emotional language. However, negative emotional language is more likely to be shared. To understand why, research has thus far focused on psychological processes associated with...
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- 2023
- Article
Building the Business Case for an Inclusive Approach to Digital Health Measurement with a Web App (Market Opportunity Calculator): Instrument Development Study
By: Mitchell Tang, Yashoda Sharma, Jennifer C. Goldsack and Ariel Dora Stern
Background: The use of digital health measurement tools has grown substantially in recent years. However, there are concerns that the promised benefits from these products will not be shared equitably. Underserved populations, such as those with lower education and...
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- 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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- April 19, 2023
- Editorial
Extreme Views Are More Attractive Than Moderate Ones
By: Amit Goldenberg
Do you ever feel like everyone on social media has a more extreme viewpoint than your own? We often blame social media companies for the cacophony of politically extreme opinions around us. After all, these companies are generally motivated to promote the most...
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- April 2023 (Revised June 2023)
- Case
AI Wars
By: Andy Wu, Matt Higgins, Miaomiao Zhang and Hang Jiang
In November 2022, amidst a growing consensus that artificial intelligence (AI) would be the next breakthrough technology to reshape the future, OpenAI released the ChatGPT application built on an improved version of GPT-3 to the general public, capturing widespread...
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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...
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- 2022
- Article
Towards Robust Off-Policy Evaluation via Human Inputs
By: Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are crucial tools for evaluating policies in high-stakes domains such as healthcare, where direct deployment is often infeasible, unethical, or expensive. When deployment environments are expected to undergo changes (that is, dataset...
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- 2022
- Working Paper
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju
As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how...
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- 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...
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- Article
The Translucent Hand of Managed Ecosystems: Engaging Communities for Value Creation and Capture
By: Elizabeth J. Altman, Frank Nagle and Michael Tushman
Management research has increasingly explored the domains of ecosystems, platforms, and open/user/distributed innovation—governance structures focused on engaging with external communities. While these research areas include substantial empirical and theoretical work...
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- December 2021
- Article
Left- and Right-Leaning News Organizations Use Negative Emotional Content and Elicit User Engagement Similarly
By: Andrea Bellovary, Nathaniel Young and Amit Goldenberg
Negativity has historically dominated news content; however, little research has examined how news organizations use affect on social media, where content is generally positive. In the current project we ask a few questions: Do news organizations on Twitter use...
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Keywords:
Negative Press;
Twitter;
Political Affiliation;
Affect;
News;
Media;
Internet and the Web;
Emotions;
Perspective;
Social Media
- 2021
- Article
Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring
By: Tom Sühr, Sophie Hilgard and Himabindu Lakkaraju
Ranking algorithms are being widely employed in various online hiring platforms including LinkedIn, TaskRabbit, and Fiverr. Prior research has demonstrated that ranking algorithms employed by these platforms are prone to a variety of undesirable biases, leading to the...
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- Article
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses
By: Kaivalya Rawal and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision-making, there has been a lot of interest in developing algorithms which can provide recourses to affected individuals. While developing such tools is important, it is even more critical to...
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- November 2020
- Teaching Note
DayTwo: Going to Market with Gut Microbiome
By: Ayelet Israeli
Teaching Note for HBS Case No. 519-010. DayTwo is a young Israeli startup that applies research on the gut microbiome and machine learning algorithms to deliver personalized nutritional recommendations to its users in order to minimize blood sugar spikes after meals....
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Keywords:
Start-up Growth;
Startup;
Positioning;
Targeting;
Go To Market Strategy;
B2B Vs. B2C;
B2B2C;
Health ＆ Wellness;
AI;
Machine Learning;
Female Ceo;
Female Protagonist;
Science-based;
Science And Technology Studies;
Ecommerce;
Applications;
DTC;
Direct To Consumer Marketing;
US Health Care;
＂USA,＂;
Innovation;
Pricing;
Business Growth;
Segmentation;
Distribution Channels;
Growth and Development Strategy;
Business Startups;
Science-Based Business;
Health;
Innovation and Invention;
Marketing;
Information Technology;
Business Growth and Maturation;
E-commerce;
Applications and Software;
Health Industry;
Technology Industry;
Insurance Industry;
Information Technology Industry;
Food and Beverage Industry;
Israel;
United States
- November 2020
- Article
Disrupting the Disruptors or Enhancing Them? How Blockchain Re‐Shapes Two‐Sided Platforms
By: Daniel Trabucchi, Antonella Moretto, Tommaso Buganza and Alan MacCormack
The importance of platform‐based businesses in the modern economy is growing continuously and becoming increasingly relevant. Specifically, the deployment of digital technologies has enhanced the applicability of two‐sided business models, enabling companies to act not...
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- August 2020 (Revised January 2022)
- Case
1928 Diagnostics: Fighting Antibiotics Resistance
By: Ariel D. Stern and Daniela Beyersdorfer
In 2019, the co-founders of the Swedish medical start-up 1928 Diagnostics, CEO Dr. Kristina Lagerstedt and COO Dr. Susanne Staaf, had to pick the right business model to commercialize their novel technology to hospitals and health care providers. Developed in...
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Keywords:
Health Care and Treatment;
Entrepreneurship;
Leadership;
Science-Based Business;
Growth and Development Strategy;
Business Growth and Maturation;
Business Model;
Information Technology;
Digital Platforms;
Health Disorders;
Market Entry and Exit;
Value Creation;
Business and Stakeholder Relations;
Health Industry;
Medical Devices and Supplies Industry;
Technology Industry;
Europe;
Sweden
- Article
Assessing the Food and Drug Administration's Risk-Based Framework for Software Precertification with Top Health Apps in the United States: Quality Improvement Study
By: Noy Alon, Ariel Dora Stern and John Torous
BACKGROUND: As the development of mobile health apps continues to accelerate, the need to implement a framework that can standardize categorizing these apps to allow for efficient, yet robust regulation grows. However, regulators and researchers are faced with numerous...
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- June 2020
- Teaching Note
Understanding the Brand Equity of Nestlé Crunch Bar
By: Jill Avery and Gerald Zaltman
Teaching Note for HBS Case Nos. 519-061 and 519-062. In early 2018, Nestlé announced the sale of its U.S. candy-making division and a select collection of twenty of its confectionery brands, including the Nestlé Crunch Bar, to Ferrero SpA for $2.8 billion. Under the...
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- 2020
- Article
Inconvenient Truths: Interpreting the Origins of the Internet
By: Shane Greenstein
A conventional economic narrative provides intellectual underpinnings for governments to subsidize research and development ("R&D") that coordinates risky research to benefit many in society. This essay compares this narrative with the origins and invention of the...
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