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      • January 2021
      • Case

      Anodot: Autonomous Business Monitoring

      By: Antonio Moreno and Danielle Golan
      Autonomous business monitoring platform Anodot leveraged machine learning to provide real-time alerts regarding business anomalies. Anodot’s solution was used in various industries in order to primarily monitor business health, such as revenue and payments, product... View Details
      Keywords: Digital Platforms; Internet and the Web; Knowledge Sharing; Information Management; Sales; Value Creation; Product Positioning; Israel
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      Moreno, Antonio, and Danielle Golan. "Anodot: Autonomous Business Monitoring." Harvard Business School Case 621-084, January 2021.
      • January 2021 (Revised March 2021)
      • Case

      THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

      By: Jill Avery, Ayelet Israeli and Emma von Maur
      THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details
      Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; "Marketing Analytics"; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; United States
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      Avery, Jill, Ayelet Israeli, and Emma von Maur. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Case 521-070, January 2021. (Revised March 2021.)
      • June 2021
      • Article

      From Predictions to Prescriptions: A Data-driven Response to COVID-19

      By: Dimitris Bertsimas, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg and Cynthia Zeng
      The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at... View Details
      Keywords: COVID-19; Health Pandemics; AI and Machine Learning; Forecasting and Prediction; Analytics and Data Science
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      Bertsimas, Dimitris, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg, and Cynthia Zeng. "From Predictions to Prescriptions: A Data-driven Response to COVID-19." Health Care Management Science 24, no. 2 (June 2021): 253–272.
      • Winter 2021
      • Editorial

      Introduction

      By: Michael A. Wheeler
      This issue of Negotiation Journal is dedicated to the theme of artificial intelligence, technology, and negotiation. It arose from a Program on Negotiation (PON) working conference on that important topic held virtually on May 17–18. The conference was not the... View Details
      Keywords: Artificial Intelligence; Information Technology; Negotiation; AI and Machine Learning
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      Wheeler, Michael A. "Introduction." Special Issue on Artificial Intelligence, Technology, and Negotiation. Negotiation Journal 37, no. 1 (Winter 2021): 5–12.
      • Article

      Towards Robust and Reliable Algorithmic Recourse

      By: Sohini Upadhyay, Shalmali Joshi and Himabindu Lakkaraju
      As predictive models are increasingly being deployed in high-stakes decision making (e.g., loan approvals), there has been growing interest in post-hoc techniques which provide recourse to affected individuals. These techniques generate recourses under the assumption... View Details
      Keywords: Machine Learning Models; Algorithmic Recourse; Decision Making; Forecasting and Prediction
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      Upadhyay, Sohini, Shalmali Joshi, and Himabindu Lakkaraju. "Towards Robust and Reliable Algorithmic Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
      • December 2020 (Revised April 2021)
      • Case

      IBM Watson at MD Anderson Cancer Center

      By: Shane Greenstein, Mel Martin and Sarkis Agaian
      After discovering that their cancer diagnostic tool, designed to leverage the cloud computing power of IBM Watson, needed greater integration into the clinical processes at the MD Anderson Cancer Center, the development team had difficult choices to make. The Oncology... View Details
      Keywords: Decision Making; Innovation Strategy; Knowledge Management; Knowledge Use and Leverage; Operations; Failure; Information Technology; Applications and Software; Health Care and Treatment; Product Development; Health Industry; Information Technology Industry; Technology Industry; United States; Houston; Texas
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      Greenstein, Shane, Mel Martin, and Sarkis Agaian. "IBM Watson at MD Anderson Cancer Center." Harvard Business School Case 621-022, December 2020. (Revised April 2021.)
      • December 2020
      • Case

      VIA Science (A)

      By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
      Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details
      Keywords: Data Analytics; Machine Learning; Artificial Intelligence; Strategy; Business Startups; Markets; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan
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      Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (A)." Harvard Business School Case 721-367, December 2020.
      • December 2020
      • Supplement

      VIA Science (B)

      By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
      Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details
      Keywords: Data Analytics; Machine Learning; Artificial Intelligence; Strategy; Business Startups; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan
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      Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (B)." Harvard Business School Supplement 721-368, December 2020.
      • Article

      Robust and Stable Black Box Explanations

      By: Himabindu Lakkaraju, Nino Arsov and Osbert Bastani
      As machine learning black boxes are increasingly being deployed in real-world applications, there has been a growing interest in developing post hoc explanations that summarize the behaviors of these black boxes. However, existing algorithms for generating such... View Details
      Keywords: Machine Learning; Black Box Models; Framework
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      Lakkaraju, Himabindu, Nino Arsov, and Osbert Bastani. "Robust and Stable Black Box Explanations." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020): 5628–5638. (Published in PMLR, Vol. 119.)
      • Article

      Soul and Machine (Learning)

      By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
      Machine learning is bringing us self-driving cars, medical diagnoses, and language translation, but how can machine learning help marketers improve marketing decisions? Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to... View Details
      Keywords: Machine Learning; Marketing Applications; Knowledge; Technological Innovation; Core Relationships; Marketing; Applications and Software
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      Proserpio, Davide, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu, and Hema Yoganarasimhan. "Soul and Machine (Learning)." Marketing Letters 31, no. 4 (December 2020): 393–404.
      • 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.... View Details
      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; Food and Beverage Industry; Food and Beverage Industry; Food and Beverage Industry; Food and Beverage Industry; Food and Beverage Industry; Israel; United States
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      Israeli, Ayelet. "DayTwo: Going to Market with Gut Microbiome." Harvard Business School Teaching Note 521-052, November 2020.
      • September 22, 2020
      • Article

      Amazon's AI Is Learning New Rules to Win for the Holidays: With Stressed Supply Chains and Changing Consumer Behaviors, the Holidays Are Likely to Accelerate Amazon's Advantage

      By: Jeffrey F. Rayport and Niall Murphy
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      Rayport, Jeffrey F., and Niall Murphy. "Amazon's AI Is Learning New Rules to Win for the Holidays: With Stressed Supply Chains and Changing Consumer Behaviors, the Holidays Are Likely to Accelerate Amazon's Advantage." Forbes.com (September 22, 2020).
      • September 2020
      • Case

      True North: Pioneering Analytics, Algorithms and Artificial Intelligence

      By: Karim R. Lakhani, Kairavi Dey and Hannah Mayer
      True North was a private equity fund that specialized in the growth and buyout of mid-market, India-centric companies. The leadership team initially believed that technology was not core to traditional businesses and steered clear of new age technology-oriented... View Details
      Keywords: Artificial Intelligence; Information Technology; Management; Operations; Organizations; Leadership; Innovation and Invention; Business Model; AI and Machine Learning; Computer Industry; Technology Industry
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      Lakhani, Karim R., Kairavi Dey, and Hannah Mayer. "True North: Pioneering Analytics, Algorithms and Artificial Intelligence." Harvard Business School Case 621-042, September 2020.
      • 2020
      • Working Paper

      (When) Does Appearance Matter? Evidence from a Randomized Controlled Trial

      By: Prithwiraj Choudhury, Tarun Khanna, Christos A. Makridis and Subhradip Sarker
      While there is evidence about labor market discrimination based on race, religion, and gender, we know little about whether physical appearance leads to discrimination in labor market outcomes. We deploy a randomized experiment on 1,000 respondents in India between... View Details
      Keywords: Behavioral Economics; Coronavirus; Discrimination; Homophily; Labor Market Mobility; Limited Attention; Resumes; Personal Characteristics; Prejudice and Bias
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      Choudhury, Prithwiraj, Tarun Khanna, Christos A. Makridis, and Subhradip Sarker. "(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial." Harvard Business School Working Paper, No. 21-038, September 2020.
      • 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
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      Ferreira, Kris, and Srikanth Jagabathula. "JOANN: Joannalytics Inventory Allocation Tool." Harvard Business School Case 621-055, September 2020. (Revised March 2022.)
      • September 2020
      • Article

      Creativity, Artificial Intelligence, and a World of Surprises

      By: Teresa M. Amabile
      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
      Keywords: Artificial Intelligence; AI Creativity; Computer Science; Organizational Behavior; Psychology; Creativity; Technological Innovation; AI and Machine Learning
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      Amabile, Teresa M. "Creativity, Artificial Intelligence, and a World of Surprises." Academy of Management Discoveries 6, no. 3 (September 2020): 351–354.
      • August 2020 (Revised September 2020)
      • Technical Note

      Assessing Prediction Accuracy of Machine Learning Models

      By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne
      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
      Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods
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      Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
      • 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

      Keywords: Economics Of AI; Machine Learning; Non-stationarity; Perishability; Value Depreciation; Analytics and Data Science; Value
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      Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)
      • 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
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      Spar, Debora L. Work, Mate, Marry, Love: How Machines Shape Our Human Destiny. New York: Farrar, Straus and Giroux, 2020.
      • 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
      Keywords: Machine Learning; Algorithms; Objective Perturbation; Mathematical Methods
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      Neel, Seth, Aaron Leon Roth, Giuseppe Vietri, and Zhiwei Steven Wu. "Oracle Efficient Private Non-Convex Optimization." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020).
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