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2019
Book

Fintech, Small Business & the American Dream: How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity

By: Karen G. Mills

Fintech, Small Business & the American Dream describes the needs of small businesses for capital and demonstrates how technology—novel data sources, artificial intelligence, machine learning—will transform the small business lending market. This market has been... View Details

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March 2019
Teaching Note

Numenta: Inventing and (or) Commercializing AI

By: David B. Yoffie

This teaching notes accompanies the Numenta case, HBS No. 716-469. The focus is how to scale a new artificial intelligence technology, how to build a platform and overcome chicken-or-the-egg problems, and how to utilize open source software and licensing. View Details

Keywords: Artificial Intelligence; Strategy; Information Technology; Technological Innovation; Commercialization; AI and Machine Learning

March 2019
Case

Wattpad

By: John Deighton and Leora Kornfeld

How to run a platform to match four million writers of stories to 75 million readers? Use data science. Make money by doing deals with television and filmmakers and book publishers. The case describes the challenges of matching readers to stories and of helping writers... View Details

March 2019
Case

DayTwo: Going to Market with Gut Microbiome

By: Ayelet Israeli and David Lane

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. After a first year of trial rollout in... View Details

February 2019
Case

Miroglio Fashion (A)

By: Sunil Gupta and David Lane

Francesco Cavarero, chief information officer of Miroglio Fashion, Italy’s third-largest retailer of women’s apparel, was trying to bring analytical rigor to the company’s forecasting and inventory management decisions. But fashion is inherently hard to predict. Can... View Details

Keywords: Inventory Management; Demand Forecasting; Artificial Intelligence; Machine Learning; Forecasting and Prediction; Operations; Management; Decision Making; AI and Machine Learning; Apparel and Accessories Industry; Fashion Industry

2020
Working Paper

Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach

By: Eva Ascarza

The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details

Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Customer Value and Value Chain; Consumer Behavior; Analytics and Data Science; Mathematical Methods; Retail Industry

Article

Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications

By: Daniel Elsner, Pouya Aleatrati Khosroshahi, Alan MacCormack and Robert Lagerström

Existing application performance management (APM) solutions lack robust anomaly detection capabilities and root cause analysis techniques that do not require manual efforts and domain knowledge. In this paper, we develop a density-based unsupervised machine learning... View Details

Keywords: Big Data; Data Science And Analytics Management; Governance And Compliance; Organizational Systems And Technology; Anomaly Detection; Application Performance Management; Machine Learning; Enterprise Architecture; Analytics and Data Science

January 2019 (Revised October 2019)
Case

Liulishuo: AI English Teacher

By: John J-H Kim and Shu Lin

Educators and entrepreneurs alike are excited about the potential for artificial intelligence (AI) and machine learning to change the way learning will look like in the future. There is a confluence of factors such as the availability of large sources of rich,... View Details

Keywords: AI; Artificial Intelligence; Education Technology; Information Technology; Education; Entrepreneurship; AI and Machine Learning; Education Industry; China

2019
Article

An Empirical Study of Rich Subgroup Fairness for Machine Learning

By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu

Kearns et al. [2018] recently proposed a notion of rich subgroup fairness intended to bridge the gap between statistical and individual notions of fairness. Rich subgroup fairness picks a statistical fairness constraint (say, equalizing false positive rates across... View Details

Keywords: Machine Learning; Fairness; AI and Machine Learning

Article

Faithful and Customizable Explanations of Black Box Models

By: Himabindu Lakkaraju, Ece Kamar, Rich Caruana and Jure Leskovec

As predictive models increasingly assist human experts (e.g., doctors) in day-to-day decision making, it is crucial for experts to be able to explore and understand how such models behave in different feature subspaces in order to know if and when to trust them. To... View Details

Keywords: Interpretable Machine Learning; Black Box Models; Decision Making; Framework

December 2018 (Revised March 2021)
Background Note

Modern Automation (A): Artificial Intelligence

By: William R. Kerr and James Palano

This primer is meant to be a field guide to the late 2010s' surge in business use of "Artificial Intelligence" (AI), or enterprise software based in machine learning. First, it provides an overview of the key trends—digitization, connectivity, the continuation of... View Details

Keywords: Artificial Intelligence; Digitization; Connectivity; Computing; Future Of Work; Automation; AI and Machine Learning

December 2018
Teaching Note

Autonomous Vehicles: The Rubber Hits the Road…but When?

By: William Kerr and James Palano

The autonomous vehicles have enormous implications for business and society. But, despite the headline-laden attention paid to the technology, there remain more questions than answers. Students will learn about the complex industry and have explicit discussions about... View Details

Keywords: Technology Management; Artificial Intelligence; General Management; Robotics; Technological Innovation; Transportation; Disruption; Information Technology; Management; Decision Making; AI and Machine Learning; Auto Industry; Technology Industry

December 2018
Case

Choosy

By: Jeffrey J. Bussgang and Julia Kelley

Founded in 2017, Choosy is a data-driven fashion startup that uses algorithms to identify styles trending on social media. After manufacturing similar items using a China-based supply chain, Choosy sells them to consumers through its website and social media pages.... View Details

October 2018
Case

Shield AI

By: Mitchell Weiss and A.J. Steinlage

Shield AI’s quadcopter – with no pilot and no flight plan – could clear a building and outpace human warfighters by almost five minutes. This was not to say that it was better than the warfighters or would replace their jobs, but it was evidence that autonomous robots... View Details

October 2018
Case

American Family Insurance and the Artificial Intelligence Opportunity

By: Rajiv Lal and Scott Johnson

October 2018
Article

The Operational Value of Social Media Information

By: Ruomeng Cui, Santiago Gallino, Antonio Moreno and Dennis J. Zhang

While the value of using social media information has been established in multiple business contexts, the field of operations and supply chain management have not yet explored the possibilities it offers in improving firms' operational decisions. This study attempts to... View Details

Keywords: Machine Learning; Information; Sales; Forecasting and Prediction; Social Media

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September 2018 (Revised December 2019)
Case

Zebra Medical Vision

By: Shane Greenstein and Sarah Gulick

An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making... View Details

2020
Working Paper

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury

Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details

Keywords: Machine Learning; Theory Building; Induction; Decision Trees; Random Forests; K-nearest Neighbors; Neural Network; P-hacking; Analytics and Data Science; Analysis

August 2018 (Revised October 2019)
Case

C3.ai—Driven to Succeed

By: Robert Simons and George Gonzalez

CEO Tom Siebel navigates his artificial intelligence (ai) startup through a series of pivots, market expansions, and even an elephant attack to become a leading platform ad service provider. The case describes his unusual management approach emphasizing employee... View Details

August 2018 (Revised October 2020)
Case

Tailor Brands: Artificial Intelligence-Driven Branding

Using proprietary artificial intelligence technology, startup Tailor Brands set out to democratize branding by allowing small businesses to create their brand identities by automatically generating logos in just minutes at minimal cost with no branding or design skills... View Details

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