Publications
Publications
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- All HBS Web
(1,089)
- Faculty Publications (429)
- September 2020 (Revised March 2022)
- Case
JOANN: Joannalytics Inventory Allocation Tool
By: Kris Ferreira and Srikanth Jagabathula
Michael Joyce, Vice President of Inventory Management at JOANN, championed an effort to develop and implement an inventory allocation analytics tool that used advanced analytics to predict in-season demand of seasonal items for each of JOANN’s nearly 900 stores and... View Details
Keywords: Analytics; Machine Learning; Optimization; Inventory Management; Mathematical Methods; Decision Making; Operations; Supply Chain Management; Resource Allocation; Distribution; Technology Adoption; Applications and Software; Change Management; Fashion Industry; Consumer Products Industry; Retail Industry; United States; Ohio
- September 2020
- Article
Creativity, Artificial Intelligence, and a World of Surprises
In recent years, progress has been made toward AI Creativity, which I define as the production of highly novel, yet appropriate, ideas, problem solutions, or other outputs by autonomous machines. I argue that organizational researchers of creativity and innovation... View Details
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
- 2021
- Working Paper
Time and the Value of Data
By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details
- August 2020
- Article
Machine Learning and Human Capital Complementarities: Experimental Evidence on Bias Mitigation
By: Prithwiraj Choudhury, Evan Starr and Rajshree Agarwal
The use of machine learning (ML) for productivity in the knowledge economy requires considerations of important biases that may arise from ML predictions. We define a new source of bias related to incompleteness in real time inputs, which may result from strategic... View Details
- 2020
- Book
Work, Mate, Marry, Love: How Machines Shape Our Human Destiny
By: Debora L. Spar
Covering a time frame that ranges from 8000 BC to the present, and drawing upon both Marxist and feminist theories, the book argues that nearly all the decisions we make in our most intimate lives—whom to marry, how to have children, how to have sex, how to think about... View Details
Keywords: Innovation; Family; Women; Reproduction; Artificial Intelligence; Robots; Gender; Demography; History; Innovation and Invention; Relationships; Society; Information Technology; AI and Machine Learning; Biotechnology Industry; Computer Industry; Health Industry; Information Technology Industry; Manufacturing Industry; Technology Industry; Africa; Asia; Europe; Latin America; North and Central America
- Article
Oracle Efficient Private Non-Convex Optimization
By: Seth Neel, Aaron Leon Roth, Giuseppe Vietri and Zhiwei Steven Wu
One of the most effective algorithms for differentially private learning and optimization is objective perturbation. This technique augments a given optimization problem (e.g. deriving from an ERM problem) with a random linear term, and then exactly solves it.... View Details
- 2021
- Conference Presentation
An Algorithmic Framework for Fairness Elicitation
By: Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Leon Roth, Logan Stapleton and Zhiwei Steven Wu
We consider settings in which the right notion of fairness is not captured by simple mathematical definitions (such as equality of error rates across groups), but might be more complex and nuanced and thus require elicitation from individual or collective stakeholders.... View Details
- Article
Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs
By: Michael G. Endres, Florian Hillen, Marios Salloumis, Ahmad R. Sedaghat, Stefan M. Niehues, Olivia Quatela, Henning Hanken, Ralf Smeets, Benedicta Beck-Broichsitter, Carsten Rendenbach, Karim R. Lakhani, Max Helland and Robert A. Gaudin
Periapical radiolucencies, which can be detected on panoramic radiographs, are one of the most common radiographic findings in dentistry and have a differential diagnosis including infections, granuloma, cysts, and tumors. In this study, we seek to investigate the... View Details
- May 2020
- Case
Numenta in 2020: The Future of AI
By: David B. Yoffie, Cameron Armstrong, Mei Tao and Marta Zwierz
In 2020, Numenta’s co-founder, Jeff Hawkins, completed his pathbreaking research on artificial intelligence. His co-founder and CEO, Donna Dubinsky, had to find a business model to monetize the technology. This case explores the challenges of building a business... View Details
- 2020
- Article
Public Sentiment and the Price of Corporate Sustainability
By: George Serafeim
Combining corporate sustainability performance scores based on environmental, social, and governance (ESG) data with big data measuring public sentiment about a company’s sustainability performance, I find that the valuation premium paid for companies with strong... View Details
Keywords: Sustainability; ESG; ESG (Environmental, Social, Governance) Performance; Investment Management; Investment Strategy; Big Data; Machine Learning; Environment; Environmental Sustainability; Corporate Governance; Performance; Asset Pricing; Investment; Management; Strategy; Human Capital; Public Opinion; Value; Analytics and Data Science
- April 29, 2020
- Article
The Case for AI Insurance
By: Ram Shankar Siva Kumar and Frank Nagle
When organizations place machine learning systems at the center of their businesses, they introduce the risk of failures that could lead to a data breach, brand damage, property damage, business interruption, and in some cases, bodily harm. Even when companies are... View Details
- 26 Apr 2020
- Other Presentation
Towards Modeling the Variability of Human Attention
By: Kuno Kim, Megumi Sano, Julian De Freitas, Daniel Yamins and Nick Haber
Children exhibit extraordinary exploratory behaviors hypothesized to contribute to the building of models of their world. Harnessing this capacity in artificial systems promises not only more flexible technology but also cognitive models of the developmental processes... View Details
- April 2020
- Article
CEO Behavior and Firm Performance
By: Oriana Bandiera, Stephen Hansen, Andrea Prat and Raffaella Sadun
We measure the behavior of 1,114 CEOs in six countries parsing granular CEO diary data through an unsupervised machine learning algorithm. The algorithm uncovers two distinct behavioral types: "leaders" and "managers." Leaders focus on multi-function, high-level... View Details
- Mar 2020
- Conference Presentation
A New Analysis of Differential Privacy's Generalization Guarantees
By: Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi and Moshe Shenfeld
We give a new proof of the "transfer theorem" underlying adaptive data analysis: that any mechanism for answering adaptively chosen statistical queries that is differentially private and sample-accurate is also accurate out-of-sample. Our new proof is elementary and... View Details
- 2020
- Working Paper
Design in the Age of Artificial Intelligence
By: Roberto Verganti, Luca Vendraminelli and Marco Iansiti
Artificial Intelligence (AI) is affecting the scenario in which innovation takes place. What are the implications for our understanding of design? Is AI just another digital technology that, akin to many others, will not significantly question what we know about... View Details
- February 2020
- Technical Note
Talent Management and the Future of Work
By: William R. Kerr and Gorick Ng
The nature of work is changing—and it is changing rapidly. Few days go by without industry giants such as Amazon and AT&T announcing plans to invest billions of dollars towards retraining nearly half of their respective workforces for jobs of the future. What changes... View Details
Keywords: Human Resource Management; Human Capital Development; Human Resource Practices; Talent; Talent Acquisition; Talent Development; Talent Development And Retention; Talent Management; Talent Retention; Labor Flows; Labor Management; Labor Market; Strategy Development; Strategy Management; Strategy Execution; Strategy And Execution; Strategic Change; Transformations; Organization; Organization Alignment; Organization Design; Organizational Adaptation; Organizational Effectiveness; Management Challenges; Management Of Business And Political Risk; Change Leadership; Future Of Work; Future; Skills Gap; Skills Development; Skills; Offshoring And Outsourcing; Investment; Capital Allocation; Work; Work Culture; Work Force Management; Work/life Balance; Work/family Balance; Work-family Boundary Management; Workers; Worker Productivity; Worker Performance; Work Engagement; Work Environment; Work Environments; Productivity; Organization Culture; Soft Skills; Technology Management; Technological Change; Technological Change: Choices And Consequences; Technology Diffusion; Disruptive Technology; Global Business; Global; Workplace; Workplace Context; Workplace Culture; Workplace Wellness; Collaboration; Competencies; Productivity Gains; Digital; Digital Transition; Competitive Dynamics; Competitiveness; Competitive Strategy; Data Analytics; Data; Data Management; Data Strategy; Data Protection; Aging Society; Diversity; Diversity Management; Millennials; Communication Complexity; Communication Technologies; International Business; Work Sharing; Global Competitiveness; Global Corporate Cultures; Intellectual Property; Intellectual Property Management; Intellectual Property Protection; Intellectual Capital And Property Issues; Globalization Of Supply Chain; Inequality; Recruiting; Hiring; Hiring Of Employees; Training; Job Cuts And Outsourcing; Job Performance; Job Search; Job Design; Job Satisfaction; Jobs; Employee Engagement; Employee Attitude; Employee Benefits; Employee Compensation; Employee Fairness; Employee Relationship Management; Employee Retention; Employee Selection; Employee Motivation; Employee Feedback; Employee Coordination; Employee Performance Management; Employee Socialization; Process Improvement; Application Performance Management; Stigma; Institutional Change; Candidates; Digital Enterprise; Cultural Adaptation; Cultural Change; Cultural Diversity; Cultural Context; Cultural Strategies; Cultural Psychology; Cultural Reform; Performance; Performance Effectiveness; Performance Management; Performance Evaluation; Performance Appraisal; Performance Feedback; Performance Measurement; Performance Metrics; Performance Measures; Performance Efficiency; Efficiency; Performance Analysis; Performance Appraisals; Performance Improvement; Automation; Artificial Intelligence; Technology Companies; Managerial Processes; Skilled Migration; Assessment; Human Resources; Management; Human Capital; Talent and Talent Management; Retention; Demographics; Labor; Strategy; Change; Change Management; Transformation; Organizational Change and Adaptation; Organizational Culture; Working Conditions; Information Technology; Technology Adoption; Disruption; Economy; Competition; Globalization; AI and Machine Learning; Digital Transformation
- January–February 2020
- Article
Competing in the Age of AI
By: Marco Iansiti and Karim R. Lakhani
Today’s markets are being reshaped by a new kind of firm—one in which artificial intelligence (AI) runs the show. This cohort includes giants like Google, Facebook, and Alibaba, and growing businesses such as Wayfair and Ocado. Every time we use their services, the... View Details
- Article
Fake AI People Won't Fix Online Dating
Computer-generated images may inspire even more distrust and surely won’t lead to the love of a lifetime. View Details
- 2020
- Book
Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World
By: Marco Iansiti and Karim R. Lakhani
In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very... View Details