Publications
Publications
Show Results For
-
All HBS Web
(1,258)
- Faculty Publications (325)
Page 1 of
325
Results
→
- 2022
- Working Paper
What Would It Mean for a Machine to Have a Self?
By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum and Tomer Ullman
What would it mean for autonomous AI agents to have a ‘self’? One proposal for a minimal
notion of self is a representation of one’s body spatio-temporally located in the world, with a tag
of that representation as the agent taking actions in the world. This turns...
View Details
- September 6, 2022
- Article
Creating a Platform for Costless Personalization in Clothing
By: Shane Greenstein
This study analyzes the role of co-invention in the creation of a platform for print-on-demand-clothing, or PODC. Co-invention is the invention of a new business process to complement new technology, and turn it into a valuable commercial service. PODC copies a design...
View Details
- 2022
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Flora Feng, Shunyuan Zhang and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the...
View Details
- September 2022
- Teaching Note
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli
Teaching Note for HBS Case No. 522-046.
View Details
Keywords:
Artificial Intelligence;
Pricing;
Pricing Algorithm;
Pricing Decisions;
Pricing Strategy;
Pricing Structure;
Promotion;
Promotions;
Online Marketing;
Data-driven Decision-making;
Data-driven Management;
Retail;
Retail Analytics;
Price;
Advertising Campaigns;
Analytics and Data Science;
Analysis;
Digital Marketing;
Budgets and Budgeting;
Marketing Strategy;
Marketing;
Transformation;
Decision Making;
AI and Machine Learning;
Retail Industry;
Italy
- August 2022
- Case
Icario Health: AI to Drive Health Engagement
By: David C. Edelman
Icario Health has built a market-leading AI engine to help health insurers drive better health behaviors for their members, enabling the insurers to improve their Medicare.
View Details
- August 25, 2022
- Article
Find the Right Pace for Your AI Rollout
By: Rebecca Karp and Aticus Peterson
Implementing AI can introduce disruptive change and disfranchise staff and employees. When members are reluctant to adopt a new technology, they might hesitate to use it, push back against its deployment, or use it in limited capacity — which affects the benefits an...
View Details
- 2022
- Working Paper
Ethical Risks of Autonomous Products: The Case of Mental Health Crises on AI Companion Applications
By: Julian De Freitas, Ahmet Kaan Uğuralp and Zeliha Uğuralp
Increasingly, some products do not merely automate some piece of our lives but act as
autonomous agents. When these technologies are not yet perfected, what are their risks? Here
we explore the case of AI companion apps. Although these apps are designed...
View Details
- 2022
- Working Paper
Machine Learning Models for Prediction of Scope 3 Carbon Emissions
By: George Serafeim and Gladys Vélez Caicedo
For most organizations, the vast amount of carbon emissions occur in their supply chain and in the post-sale processing, usage, and end of life treatment of a product, collectively labelled scope 3 emissions. In this paper, we train machine learning algorithms on 15...
View Details
- June 2022
- Article
The Use and Misuse of Patent Data: Issues for Finance and Beyond
By: Josh Lerner and Amit Seru
Patents and citations are powerful tools for understanding innovation increasingly used in financial economics (and management research more broadly). Biases may result, however, from the interactions between the truncation of patents and citations and the changing...
View Details
- May 2022
- Case
AWS and Amazon SageMaker (A): The Commercialization of Machine Learning Services
By: Karim R. Lakhani, Shane Greenstein and Kerry Herman
- May 2022
- Supplement
AWS and Amazon SageMaker (B): The Commercialization of Machine Learning Services
By: Karim R. Lakhani, Shane Greenstein and Kerry Herman
- May 2022 (Revised July 2022)
- Supplement
AWS and Amazon SageMaker (C): The Commercialization of Machine Learning Services
By: Karim R. Lakhani, Shane Greenstein and Kerry Herman
- May 2022
- Supplement
Borusan CAT: Monetizing Prediction in the Age of AI (B)
By: Navid Mojir and Gamze Yucaoglu
Borusan Cat is an international distributor of Caterpillar heavy machines. In 2021, it had been three years since Ozgur Gunaydin (CEO) and Esra Durgun (Director of Strategy, Digitization, and Innovation) started working on Muneccim, the company’s predictive AI tool....
View Details
- May 2022 (Revised August 2022)
- Case
LOOP: Driving Change in Auto Insurance Pricing
By: Elie Ofek and Alicia Dadlani
John Henry and Carey Anne Nadeau, co-founders and co-CEOs of LOOP, an insurtech startup based in Austin, Texas, were on a mission to modernize the archaic $250 billion automobile insurance market. They sought to create equitably priced insurance by eliminating pricing...
View Details
- May 2022 (Revised July 2022)
- Case
The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022
By: David B. Yoffie and Daniel Fisher
In 2022, after five years of pursuing a new "AI-first" strategy, Google had captured a sizeable share of the American and global markets for voice assistants. Google Assistant was used by hundreds of millions of users around the world, but Amazon retained the largest...
View Details
- Article
Developing a Digital Mindset: How to Lead Your Organization into the Age of Data, Algorithms, and AI
By: Tsedal Neeley and Paul Leonardi
Learning new technological skills is essential for digital transformation. But it is not enough. Employees must be motivated to use their skills to create new opportunities. They need a digital mindset: a set of attitudes and behaviors that enable people and...
View Details
- 2022
- Article
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.
By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a...
View Details
- 2022
- Book
The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI
By: Paul Leonardi and Tsedal Neeley
The pressure to "be digital" has never been greater, but you can meet the challenge.
The digital revolution is here, changing how work gets done, how industries are structured, and how people from all walks of life work, behave, and relate to each other. To thrive...
View Details
- April 2022
- Article
AI Insurance: How Liability Insurance Can Drive the Responsible Adoption of Artificial Intelligence in Health Care
By: Ariel Dora Stern, Avi Goldfarb, Timo Minssen and W. Nicholson Price II
Despite enthusiasm about the potential to apply artificial intelligence (AI) to medicine and health care delivery, adoption remains tepid, even for the most compelling technologies. In this article, the authors focus on one set of challenges to AI adoption: those...
View Details
- March 2022 (Revised July 2022)
- Module Note
Prediction & Machine Learning
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional...
View Details