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- All HBS Web
(1,194)
- People (1)
- News (232)
- Research (675)
- Events (17)
- Multimedia (8)
- Faculty Publications (560)
Policy versus Practice: Conceptions of Artificial Intelligence
The recent growth of concern around issues such as social biases implicit in algorithms, economic impacts of artificial intelligence (AI), or potential existential threats posed... View Details
- 02 May 2024
- Video
OpenAI CEO Sam Altman on AI’s Impact on Business and Society
- 2022
- Working Paper
The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives
By: Ariel Dora Stern
For those who follow health and technology news, it is difficult to go more than a few days without reading about a compelling new application of Artificial Intelligence (AI) to health care. AI has myriad applications in medicine and its adjacent industries, with... View Details
Keywords: AI and Machine Learning; Health Care and Treatment; Governing Rules, Regulations, and Reforms; Technological Innovation; Medical Devices and Supplies Industry
Stern, Ariel Dora. "The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives." NBER Working Paper Series, No. 30639, December 2022.
- Research Summary
Overview
By: Isamar Troncoso
Professor Troncoso's research explores problems related to digital marketplaces and AI applications in marketing, and combines toolkits from econometrics, causal inference, and machine learning. She has studied how different platform design choices can lead to... View Details
- 2021
- Article
To Thine Own Self Be True? Incentive Problems in Personalized Law
By: Jordan M. Barry, John William Hatfield and Scott Duke Kominers
Recent years have seen an explosion of scholarship on “personalized law.” Commentators foresee a world in which regulators armed with big data and machine learning techniques determine the optimal legal rule for every regulated party, then instantaneously disseminate... View Details
Keywords: Personalized Law; Regulation; Regulatory Avoidance; Regulatory Arbitrage; Law And Economics; Law And Technology; Law And Artificial Intelligence; Futurism; Moral Hazard; Elicitation; Signaling; Privacy; Law; Governing Rules, Regulations, and Reforms; Information Technology; AI and Machine Learning
Barry, Jordan M., John William Hatfield, and Scott Duke Kominers. "To Thine Own Self Be True? Incentive Problems in Personalized Law." Art. 2. William & Mary Law Review 62, no. 3 (2021).
- 2024
- Working Paper
Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions
By: Caleb Kwon, Ananth Raman and Jorge Tamayo
We investigate whether corporate officers should grant managers discretion to override AI-driven demand forecasts and labor scheduling tools. Analyzing five years of administrative data from a large grocery retailer using such an AI tool, encompassing over 500 stores,... View Details
Keywords: AI and Machine Learning; Forecasting and Prediction; Working Conditions; Performance Productivity
Kwon, Caleb, Ananth Raman, and Jorge Tamayo. "Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions." Working Paper, April 2024.
- October 14, 2019
- Article
How Artificial Intelligence Is Changing Health Care Delivery
By: Samantha F. Sanders, Mats Terwiesch, William J. Gordon and Ariel Dora Stern
The development of intelligent machines holds great promise for making health care delivery more accurate, efficient, and accessible, but challenges remain for incorporating AI into clinical and administrative settings. View Details
Keywords: Artificial Intelligence; Health Care and Treatment; Service Delivery; Technological Innovation; AI and Machine Learning
Sanders, Samantha F., Mats Terwiesch, William J. Gordon, and Ariel Dora Stern. "How Artificial Intelligence Is Changing Health Care Delivery." NEJM Catalyst (October 17, 2019).
- 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
Kerr, William R., and Gorick Ng. "Talent Management and the Future of Work." Harvard Business School Technical Note 820-084, February 2020.
- 01 Mar 2024
- News
Alumni and Faculty Books and Podcasts
Edited by Margie Kelley Alumni Books You Got This! A Straightforward, No-Nonsense Playbook for Crushing 130+ Workplace Challenges By Heidi Abelli (MBA 1993) Palmetto Publishing Stepping into the corporate world can feel like navigating a labyrinth, especially when... View Details
- July 2024
- Case
Knowledge-Enabled Financial Advice: Digital Transformation at Edward Jones
By: Lauren Cohen, Richard Ryffel, Grace Headinger and Sophia Pan
Edward Jones, a wealth management advisory firm that prided itself on its interpersonal connections and face-to-face interactions, was eager to augment their services with AI capabilities. Built on 1-to-1 close-knit relationships, the firm had more than 15,000 offices... View Details
Keywords: Fintech; Innovation And Strategy; Financial Advisors; Big Data; Artificial Intelligence; Digitization; Financial Institutions; Business Strategy; Competitive Advantage; Technology Adoption; Business Plan; Technological Innovation; Interpersonal Communication; Communication Intention and Meaning; Communication Strategy; Transformation; Employee Stock Ownership Plan; Disruptive Innovation; Innovation Strategy; Innovation and Management; Innovation Leadership; Knowledge Acquisition; Knowledge Use and Leverage; Customer Relationship Management; AI and Machine Learning; Digital Strategy; Financial Services Industry; St. Louis; Missouri; United States; Canada
Cohen, Lauren, Richard Ryffel, Grace Headinger, and Sophia Pan. "Knowledge-Enabled Financial Advice: Digital Transformation at Edward Jones." Harvard Business School Case 225-009, July 2024.
Himabindu Lakkaraju
Himabindu "Hima" Lakkaraju is an Assistant Professor of Business Administration at Harvard Business School. She is also a faculty affiliate in the Department of Computer Science at Harvard University, the Harvard Data Science Initiative, Center for Research on... View Details
- Article
Ideation with Generative AI—In Consumer Research and Beyond
By: Julian De Freitas, G. Nave and Stefano Puntoni
The use of large language models (LLMs) in consumer research is rapidly evolving, with applications including synthetic data generation, data analysis, and more. However, their role in creative ideation—a cornerstone of consumer research—remains underexplored. Drawing... View Details
- 23 May 2023
- Research & Ideas
Face Value: Do Certain Physical Features Help People Get Ahead?
empirically predicted with a machine learning model, suggests work by Shunyuan Zhang, an assistant professor at Harvard Business School, and collaborators. “Our research... View Details
Keywords: by Kara Baskin
- 12 PM – 1 PM EDT, 22 Sep 2023
- Webinars: Career
Tech in the Job Search: ChatGPT for Job-Seekers
Join CPD and a former LinkedIn insider for an enlightening webinar and learn to harness the potential of AI tools like ChatGPT to revolutionize your job search experience. View Details
- Research Summary
Overview
Paul is primarily interested in studying explainable machine learning (ML), digital transformation, and data science operations. He works on research that explores how stakeholders within organizations can use machine learning to make better decisions. In particular,... View Details
- June 2024
- Article
Oral History and Business History in Emerging Markets
By: Geoffrey Jones
This article describes the motivation, structure and use of the Creating Emerging Markets (CEM) oral history-based project at the Harvard Business School. The project consists of lengthy interviews with business leaders from emerging markets. By June 2024 183... View Details
Jones, Geoffrey. "Oral History and Business History in Emerging Markets." Investigaciones de historia económica 20, no. 2 (June 2024): 1–4.
Magie Cheng
Mengjie (Magie) Cheng is a Ph.D. student in Marketing at Harvard Business School. She received her B.S. in Finance from Chu Kochen Honors College at Zhejiang University and M.S. in Management Science and... View Details
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.
- 2023
- Article
Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability
By: Usha Bhalla, Suraj Srinivas and Himabindu Lakkaraju
With the increased deployment of machine learning models in various real-world applications, researchers and practitioners alike have emphasized the need for explanations of model behaviour. To this end, two broad strategies have been outlined in prior literature to... View Details
Bhalla, Usha, Suraj Srinivas, and Himabindu Lakkaraju. "Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability." Advances in Neural Information Processing Systems (NeurIPS) (2023).