by Ai Hisano - Publications - Faculty & Research - Harvard Business School

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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

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

Keywords: Exploratory Learning Behaviors; Modeling; Artificial Intelligence; AI and Machine Learning

March 2020
Case

Sizmek Chapter 11: Surviving Walled Gardens in Their Ad Tech Empire

By: Ayelet Israeli, Danilo Tauro and Sarah Gulick

This case provides a post-mortem of the advertising technology (adtech) company Sizmek. Sizmek grew via multiple acquisitions, with the vision of becoming an integrated adtech company that could leverage AI to buy digital media, while creating and serving display and... View Details

Keywords: Digital Marketing; Insolvency and Bankruptcy; Mergers and Acquisitions; Applications and Software; Internet and the Web; Competition; Marketing; Advertising Industry; Web Services Industry; United States; Europe

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

Keywords: Artificial Intelligence; Design Thinking; Technological Innovation; Design; Change; Theory; AI and Machine Learning

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

Keywords: Artificial Intelligence; Algorithms; Technological Innovation; Business Model; Competition; Competitive Strategy; AI and Machine Learning

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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

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

Keywords: Robotics; Artificial Intelligence; Future Of Work; Technology Commercialization; Information Technology; Commercialization; Employment; AI and Machine Learning

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

Keywords: Machine Learning; Technological Innovation; Marketing; AI and Machine Learning

August 2019 (Revised March 2022)
Case

Lemonade: Disrupting Insurance with Instant Everything, Killer Prices, and a Big Heart

By: Elie Ofek and Danielle Golan

Launching its first products in the fall of 2016 in New York, insurtech startup Lemonade was on a mission to disrupt the insurance market by using AI and behavioral economics principles. The company offered renters, homeowners, and condo insurance and mainly targeted... View Details

Keywords: AI; Business Startups; Insurance; Technological Innovation; Business Model; Disruption; Brands and Branding; Growth and Development Strategy; Global Strategy; Decision Making; Insurance Industry; Technology Industry

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

Keywords: Crowdsourcing; AI Algorithms; Health Care and Treatment; Collaborative Innovation and Invention; AI and Machine Learning

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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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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

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

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

May 2018 (Revised February 2019)
Case

The Powers That Be (Internet Edition): Google, Apple, Facebook, Amazon, and Microsoft

By: Jeffrey F. Rayport, Julia Kelley and Nathaniel Schwalb

As of early 2018, five U.S. technology companies—Google, Apple, Facebook, Amazon, and Microsoft—were among the largest companies in the world. Similarly, three Chinese technology firms—Baidu, Alibaba, and Tencent, or BAT—had emerged as global players due in part to the... View Details

Keywords: Internet and the Web; Business Ventures; Customers; Analytics and Data Science; Safety; Corporate Strategy; Competitive Strategy; Technology Industry

April 2018 (Revised November 2019)
Case

JD: Envisioning the Future of Retail (A)

By: Feng Zhu and Shirley Sun

JD, China’s second largest e-commerce company by gross merchandise volume (GMV) after Alibaba, had expanded rapidly from 2012 to 2016. When the company celebrated its 13th birthday in 2017, Richard Liu, its founder, deliberated on the company’s growth strategies. The... View Details

Keywords: Growth and Development Strategy; Competitive Strategy; E-commerce; Retail Industry; China

February 2018 (Revised October 2019)
Case

HubSpot and Motion AI: Chatbot-Enabled CRM

By: Jill Avery and Thomas Steenburgh

HubSpot, an inbound marketing, sales, and customer relationship management (CRM) software provider, announced that it had acquired Motion AI, a software platform that enabled companies to easily build and deploy chatbots, fueled by artificial intelligence, to interact... View Details

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