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  • All HBS Web  (228)
    • News  (70)
    • Research  (90)
    • Events  (2)
  • Faculty Publications  (32)

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  • All HBS Web  (228)
    • News  (70)
    • Research  (90)
    • Events  (2)
  • Faculty Publications  (32)
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  • August 28, 2018
  • Article

How Intermittent Breaks in Interaction Improve Collective Intelligence

By: Ethan Bernstein, Jesse Shore and David Lazer
People influence each other when they interact to solve problems. Such social influence introduces both benefits (higher average solution quality due to exploitation of existing answers through social learning) and costs (lower maximum solution quality due to a... View Details
Keywords: Transparency; Social Influence; Collective Intelligence; Interaction; Problem Solving; Collaboration; Intermittant; Breaks; Always On; Communication Technologies; Communication; Design; Information; Management; Leadership; Organizational Design; Organizational Structure; Performance; Social and Collaborative Networks; Information Technology
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Bernstein, Ethan, Jesse Shore, and David Lazer. "How Intermittent Breaks in Interaction Improve Collective Intelligence." Proceedings of the National Academy of Sciences 115, no. 35 (August 28, 2018).
  • November–December 2023
  • Article

Network Centralization and Collective Adaptability to a Shifting Environment

By: Ethan S. Bernstein, Jesse C. Shore and Alice J. Jang
We study the connection between communication network structure and an organization’s collective adaptability to a shifting environment. Research has shown that network centralization—the degree to which communication flows disproportionately through one or more... View Details
Keywords: Network Centralization; Collective Intelligence; Organizational Change and Adaptation; Organizational Structure; Communication; Decision Making; Networks; Adaptation
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Bernstein, Ethan S., Jesse C. Shore, and Alice J. Jang. "Network Centralization and Collective Adaptability to a Shifting Environment." Organization Science 34, no. 6 (November–December 2023): 2064–2096.
  • August 2017 (Revised July 2019)
  • Case

GROW: Using Artificial Intelligence to Screen Human Intelligence

By: Ethan Bernstein, Paul McKinnon and Paul Yarabe
Over 10% of all 2017 university graduates in Japan used GROW, an artificial intelligence platform and mobile app developed by Tokyo-based people analytics startup IGS, to recruit for a job. This case puts participants in the shoes of IGS founder and CEO Masahiro... View Details
Keywords: Big Data; Artificial Intelligence; Talent and Talent Management; Recruitment; Selection and Staffing; Human Resources; Information Technology; AI and Machine Learning; Analytics and Data Science; Financial Services Industry; Air Transportation Industry; Advertising Industry; Manufacturing Industry; Technology Industry; Japan
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Bernstein, Ethan, Paul McKinnon, and Paul Yarabe. "GROW: Using Artificial Intelligence to Screen Human Intelligence." Harvard Business School Case 418-020, August 2017. (Revised July 2019.)
  • 2024
  • Chapter

Regulating Collective Emotions

By: Amit Goldenberg
When we think of emotion and emotion regulation, we typically think of them as processes occurring at the individual level. Even when emotions are experienced by multiple people who interact with each other, analysis is typically centered around individual-level... View Details
Keywords: Groups and Teams; Emotions; Behavior
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Goldenberg, Amit. "Regulating Collective Emotions." Chap. 22 in Handbook of Emotion Regulation. Third Edition edited by James J. Gross and Brett Q. Ford, 183–189. Guilford Press, 2024.
  • 2014
  • Other Unpublished Work

Neutral Point of View and Collective Intelligence Bias: The Case of Wikipedia

By: Shane Greenstein
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Greenstein, Shane. "Neutral Point of View and Collective Intelligence Bias: The Case of Wikipedia." 2014.
  • 07 Nov 2014
  • Working Paper Summaries

Do Experts or Collective Intelligence Write with More Bias? Evidence from Encyclopædia Britannica and Wikipedia

Keywords: by Shane Greenstein & Feng Zhu; Information; Publishing
  • Article

A Collective Biological Processing Algorithm for EKG Signals

By: Mike Horia Teodorescu
We establish and explore an analogy between hunting by packs of agents and signal processing. We present a version of adaptive ‘Hunting Swarm’ algorithm (HSA), apply it to EKG signals, and investigate the influence of the model parameters on the filtering of stationary... View Details
Keywords: Artificial Intelligence; Technological Innovation; Health Care and Treatment
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Teodorescu, Mike Horia. "A Collective Biological Processing Algorithm for EKG Signals." Proceedings of the International Conference on Bio-inspired Systems and Signal Processing 4th (2011): 413–420. (IEEE BIOSIGNALS 2011.)
  • 2019
  • Working Paper

Intelligent Design of Inclusive Growth Strategies

By: Robert S. Kaplan, George Serafeim and Eduardo Tugendhat
Improving corporate engagement with society, as advocated in the Business Roundtable’s 2019 statement, should not be viewed as a zero-sum proposition where attention to new stakeholders detracts from delivering shareholder value. Corporate programs for sustainable and... View Details
Keywords: Inclusion; Sustainability; Performance Measures; Environmental Sustainability; Social Issues; Strategy; Governance; Corporate Social Responsibility and Impact; Business and Stakeholder Relations
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Kaplan, Robert S., George Serafeim, and Eduardo Tugendhat. "Intelligent Design of Inclusive Growth Strategies." Harvard Business School Working Paper, No. 20-050, October 2019.
  • 02 Jan 2019
  • What Do You Think?

SUMMING UP: Do We Need an Artificial Intelligence Czar?

with it. At the same time, we have made giant strides in methods of addressing nearly any problem one can imagine. Many are associated with the development of artificial intelligence (AI). In a nutshell, cloud-enabled data View Details
Keywords: by James Heskett; Technology
  • 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; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products 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.)
  • May 2021
  • Article

Ideology and Composition Among an Online Crowd: Evidence From Wikipedians

By: Shane Greenstein, Grace Gu and Feng Zhu
Online communities bring together participants from diverse backgrounds and often face challenges in aggregating their opinions. We infer lessons from the experience of individual contributors to Wikipedia articles about U.S. politics. We identify two factors that... View Details
Keywords: User Segregation; Online Community; Contested Knowledge; Collective Intelligence; Ideology; Bias; Wikipedia; Knowledge Sharing; Perspective; Government and Politics
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Greenstein, Shane, Grace Gu, and Feng Zhu. "Ideology and Composition Among an Online Crowd: Evidence From Wikipedians." Management Science 67, no. 5 (May 2021): 3067–3086.
  • May 2021 (Revised February 2024)
  • Teaching Note

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

By: Ayelet Israeli and Jill Avery
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; 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; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
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Israeli, Ayelet, and Jill Avery. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Teaching Note 521-097, May 2021. (Revised February 2024.)
  • 22 Oct 2019
  • Research & Ideas

Use Artificial Intelligence to Set Sales Targets That Motivate

advanced analytics that incorporate artificial intelligence (AI). “Chung has seen companies dramatically improve productivity after adopting advanced analytics to guide compensation.” In an ideal world, a company would use trial and error... View Details
Keywords: by Michael Blanding
  • 03 Jan 2023
  • Book

Confront Workplace Inequity in 2023: Dig Deep, Build Bridges, Take Collective Action

back up and running, many women are asking: What’s it going to take to effect real change? According to Tina Opie, visiting scholar at Harvard Business School and author of Shared Sisterhood: How to Take Collective Action for Racial and... View Details
Keywords: by Pamela Reynolds
  • September 2018
  • Article

Do Experts or Crowd-Based Models Produce More Bias? Evidence from Encyclopædia Britannica and Wikipedia

By: Shane Greenstein and Feng Zhu
Organizations today can use both crowds and experts to produce knowledge. While prior work compares the accuracy of crowd-produced and expert-produced knowledge, we compare bias in these two models in the context of contested knowledge, which involves subjective,... View Details
Keywords: Online Community; Collective Intelligence; Wisdom Of Crowds; Bias; Wikipedia; Britannica; Knowledge Production; Knowledge Sharing; Knowledge Dissemination; Prejudice and Bias
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Greenstein, Shane, and Feng Zhu. "Do Experts or Crowd-Based Models Produce More Bias? Evidence from Encyclopædia Britannica and Wikipedia." MIS Quarterly 42, no. 3 (September 2018): 945–959.
  • May 2017 (Revised March 2018)
  • Case

Predicting Consumer Tastes with Big Data at Gap

By: Ayelet Israeli and Jill Avery
CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big... View Details
Keywords: Retailing; Preference Elicitation; Big Data; Predictive Analytics; Artificial Intelligence; Fashion; Marketing; Marketing Strategy; Marketing Channels; Brands and Branding; Consumer Behavior; Demand and Consumers; Analytics and Data Science; Forecasting and Prediction; E-commerce; Apparel and Accessories Industry; Consumer Products Industry; Fashion Industry; Retail Industry; United States; Canada; North America
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Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Case 517-115, May 2017. (Revised March 2018.)
  • 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
Keywords: Artificial Intelligence; Market Research; Business Model; Finance; Revenue; Decision Making; Risk and Uncertainty; Market Entry and Exit; Applications and Software; AI and Machine Learning; Information Technology Industry; Auto Industry; United States
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Greenstein, Shane, and John Masko. "Feeling Machines: Emotion AI at Affectiva." Harvard Business School Case 620-058, October 2019.
  • Article

The Impact of the 'Open' Workspace on Human Collaboration

By: Ethan Bernstein and Stephen Turban
Organizations’ pursuit of increased workplace collaboration has led managers to transform traditional office spaces into “open,” transparency-enhancing architectures with fewer walls, doors, and other spatial boundaries, yet there is scant direct empirical research on... View Details
Keywords: Open Office; Transparency; Collaboration; Collective Intelligence; Workspace; Workspace Design; Architecture; Cubicles; Boundaries; Spatial Boundaries; Human Behavior; Propinquity; Co-location; Interaction; Sociometers; People Analytics; Buildings and Facilities; Communication; Design; Human Resources; Leadership; Management; Organizational Design; Organizational Structure; Networks; Social and Collaborative Networks; Information Technology; United States
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Bernstein, Ethan, and Stephen Turban. "The Impact of the 'Open' Workspace on Human Collaboration." Art. 239. Philosophical Transactions of the Royal Society B, Biological Sciences 373, no. 1753 (August 19, 2018).
  • December 2023 (Revised August 2024)
  • Supplement

Microsoft Azure and the Cloud Wars (B)

By: Andy Wu and Matt Higgins
By 2023, the global market for cloud infrastructure had consolidated into a three-horse race. As of Q4 2022, Amazon, Microsoft, and Google collectively accounted for 66% of the global market. AWS had a market share of 33%, Microsoft Azure had 23%, and Google Cloud had... View Details
Keywords: Microsoft; Artificial Intelligence; AI; Competition; Information Infrastructure; Market Participation
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Wu, Andy, and Matt Higgins. "Microsoft Azure and the Cloud Wars (B)." Harvard Business School Supplement 724-434, December 2023. (Revised August 2024.)
  • July 2023 (Revised July 2023)
  • Background Note

Generative AI Value Chain

By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value
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Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
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