Publications
Publications
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- All HBS Web
(1,089)
- Faculty Publications (429)
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
- Article
How to Use Heuristics for Differential Privacy
By: Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
We develop theory for using heuristics to solve computationally hard problems in differential privacy. Heuristic approaches have enjoyed tremendous success in machine learning, for which performance can be empirically evaluated. However, privacy guarantees cannot be... View Details
- October 2019
- Case
Feeling Machines: Emotion AI at Affectiva
By: Shane Greenstein and John Masko
In 2016, Affectiva—a Boston-based emotion AI software company with a long track record of building emotion-sensing software for market research—had attempted to expand into new verticals by releasing a mobile software development kit (SDK) that downloaders could adapt... View Details
- Article
Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles
By: Prithwiraj Choudhury, Dan Wang, Natalie A. Carlson and Tarun Khanna
We demonstrate how a novel synthesis of three methods—(1) unsupervised topic modeling of text data to generate new measures of textual variance, (2) sentiment analysis of text data, and (3) supervised ML coding of facial images with a cutting-edge convolutional neural... View Details
- October 2019
- Case
Leading Bank Leumi into the Future
By: Joshua D. Margolis, Allison M. Ciechanover, Nicole Keller and Danielle Golan
An unlikely but highly effective leader of a traditional bank, Rakefet Russak-Aminoach, simultaneously leads a classic change effort and an unconventional effort to innovate. She focuses her initial energy on making the bank more efficient in the face of industry... View Details
Keywords: Mobile Banking; Digital Banking; Fintech; Startup; Financial Services; Artificial Intelligence; Innovation; Efficiency; Organizational Change; Personal Development; Female Ceo; Banks and Banking; Mobile and Wireless Technology; Leadership; Organizational Change and Adaptation; Innovation and Invention; Disruption; Information Technology; Opportunities; Performance Effectiveness; Personal Development and Career; AI and Machine Learning; Financial Services Industry; Banking Industry; Israel
- October 2019 (Revised March 2021)
- Background Note
Modern Automation (B): Robotics
By: William R. Kerr and James Palano
Driven largely by advances in perception and situational awareness, robots in the 2010s were gaining functionality that allowed them to be applied to fundamentally new types of work. The expanding range of new tasks that could be completed by machines had significant... View Details
- 2019
- Working Paper
Soul and Machine (Learning)
By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Alex Burnap, Tong Guo, Dokyun Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
Machine learning is bringing us self-driving cars, improved medical diagnostics, and machine translation, but can it improve marketing decisions? It can. Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to rich media... View Details
- 2020
- Working Paper
Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
We study how a regulator can best target inspections. Our case study is a US Occupational Safety and Health Administration (OSHA) program that randomly allocated some inspections. On average, each inspection averted 2.4 serious injuries (9%) over the next five years.... View Details
- July 2019 (Revised November 2019)
- Case
Osaro: Picking the Best Path
By: William R. Kerr, James Palano and Bastiane Huang
The founder of Osaro saw the potential of deep reinforcement learning to allow robots to be applied to new applications. Osaro targeted warehousing, already a dynamic industry for robotics and automation, for its initial product—a system which would allow robotic arms... View Details
Keywords: Artificial Intelligence; Machine Learning; Robotics; Robots; Ecommerce; Fulfillment; Warehousing; AI; Startup; Technology Commercialization; Business Startups; Entrepreneurship; Logistics; Order Taking and Fulfillment; Information Technology; Commercialization; Learning; Complexity; Competition; E-commerce
- July 2019
- Teaching Note
Miroglio Fashion
By: Sunil Gupta
Teaching Note for HBS Nos. 519-053, 519-070, and 519-072. View Details
- June 2019
- Teaching Note
Zebra Medical Vision
By: Shane Greenstein and Sarah Gulick
Teaching note is meant to accompany Zebra Medical Vision case, which offers a look at a company’s decisions as a small startup competing with other startups and major technology companies. It also demonstrates the challenges faced by a machine learning company working... View Details
- Article
Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting
By: Raymond H. Mak, Michael G. Endres, Jin Hyun Paik, Rinat A. Sergeev, Hugo Aerts, Christopher L. Williams, Karim R. Lakhani and Eva C. Guinan
Importance: Radiation therapy (RT) is a critical cancer treatment, but the existing radiation oncologist work force does not meet growing global demand. One key physician task in RT planning involves tumor segmentation for targeting, which requires substantial... View Details
- April 2019 (Revised June 2019)
- Case
From Globalization to Dual Digital Transformation: CEO Thierry Breton Leading Atos Into 'Digital Shockwaves' (A)
By: Tsedal Neeley, JT Keller and James Barnett
Thierry Breton, chairman and CEO of IT company Atos, faced a pivotal juncture. After spending eight intense years scaling the company globally to over 100,000 employees in 70 countries, he was ready to take the next crucial step. Breton was convinced that rapid digital... View Details
- 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
Keywords: Fintech; Big Data; Data; Technology; Artificial Intelligence; Great Recession; Regulation; Innovation; Banks; Lending; Loans; Access To Capital; American Dream; Community Banking; Small Business Administration; Entrepreneur; Government; Public Policy; API; Policy Making; Small Business; Financing and Loans; Technological Innovation; Financial Crisis; Banks and Banking; Governing Rules, Regulations, and Reforms; Policy; AI and Machine Learning; Analytics and Data Science; United States
- 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
- 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
Keywords: Platform Businesses; Creative Industries; Publishing; Data Science; Machine Learning; Collaborative Filtering; Women And Leadership; Managing Data Scientists; Big Data; Recommender Systems; Digital Platforms; Information Technology; Intellectual Property; Analytics and Data Science; Publishing Industry; Entertainment and Recreation Industry; Canada; United States; Philippines; Viet Nam; Turkey; Indonesia; Brazil
- 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
Keywords: Start-up Growth; Startup; Positioning; Targeting; Go To Market Strategy; B2B2C; B2B Vs. B2C; 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
- 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
- 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
- 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