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      • 2023
      • Book

      Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow

      By: Ken Huang, Yang Wang, Feng Zhu, Xi Chen and Chunxiao Xing
      This book explores the transformative potential of ChatGPT, Web3, and their impact on productivity and various industries. It delves into Generative AI (GenAI) and its representative platform ChatGPT, their synergy with Web3, and how they can revolutionize business... View Details
      Keywords: Generative Ai; AI and Machine Learning; Ethics; Technology Adoption
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      Huang, Ken, Yang Wang, Feng Zhu, Xi Chen, and Chunxiao Xing, eds. Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow. Springer, 2023.
      • 2023
      • Working Paper

      Financial and Informational Integration Through Oracle Networks

      By: Lin William Cong, Eswar Prasad and Daniel Rabetti
      Oracles are software components that enable data exchange between siloed blockchains and external environments, enhancing smart contract capabilities and platform interoperability. We find that oracle integration is positively associated with total value locked and... View Details
      Keywords: Decentralized Finance; Blockchain; Smart Contract; International Economy; Interoperability; Risk Sharing; Applications and Software; Financial Markets; Economics; Risk Management
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      Cong, Lin William, Eswar Prasad, and Daniel Rabetti. "Financial and Informational Integration Through Oracle Networks." Working Paper, December 2023.
      • 2023
      • Article

      M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models

      By: Himabindu Lakkaraju, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai and Haoyi Xiong
      While Explainable Artificial Intelligence (XAI) techniques have been widely studied to explain predictions made by deep neural networks, the way to evaluate the faithfulness of explanation results remains challenging, due to the heterogeneity of explanations for... View Details
      Keywords: AI and Machine Learning
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      Lakkaraju, Himabindu, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai, and Haoyi Xiong. "M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
      • 2023
      • Article

      MoPe: Model Perturbation-based Privacy Attacks on Language Models

      By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
      Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training... View Details
      Keywords: Large Language Model; AI and Machine Learning; Cybersecurity
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      Li, Marvin, Jason Wang, Jeffrey Wang, and Seth Neel. "MoPe: Model Perturbation-based Privacy Attacks on Language Models." Proceedings of the Conference on Empirical Methods in Natural Language Processing (2023): 13647–13660.
      • 2023
      • Article

      Post Hoc Explanations of Language Models Can Improve Language Models

      By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
      Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance... View Details
      Keywords: AI and Machine Learning; Performance Effectiveness
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      Krishna, Satyapriya, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, and Himabindu Lakkaraju. "Post Hoc Explanations of Language Models Can Improve Language Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
      • December 2023
      • Article

      Self-Orienting in Human and Machine Learning

      By: Julian De Freitas, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum and T. Ullman
      A current proposal for a computational notion of self is a representation of one’s body in a specific time and place, which includes the recognition of that representation as the agent. This turns self-representation into a process of self-orientation, a challenging... View Details
      Keywords: AI and Machine Learning; Behavior; Learning
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      De Freitas, Julian, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum, and T. Ullman. "Self-Orienting in Human and Machine Learning." Nature Human Behaviour 7, no. 12 (December 2023): 2126–2139.
      • 2023
      • Other Article

      The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications

      By: Mirac Suzgun, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers and Stuart Shieber
      Innovation is a major driver of economic and social development, and information about many kinds of innovation is embedded in semi-structured data from patents and patent applications. Though the impact and novelty of innovations expressed in patent data are difficult... View Details
      Keywords: USPTO; Natural Language Processing; Classification; Summarization; Patent Novelty; Patent Trolls; Patent Enforceability; Patents; Innovation and Invention; Intellectual Property; AI and Machine Learning; Analytics and Data Science
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      Suzgun, Mirac, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers, and Stuart Shieber. "The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
      • 2023
      • Chapter

      The Platform Organization

      By: Annabelle Gawer, Michael A. Cusumano and David B. Yoffie
      The industry platform is a distinct organizational form that has grown into importance over the past 20 years. We focus on the digital platform, which, along with its associated ecosystem, is uniquely positioned to create and capture value in the digital economy. View Details
      Keywords: Platform; Organization; Organizations; Internet and the Web; Value Creation; Digital Platforms
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      Gawer, Annabelle, Michael A. Cusumano, and David B. Yoffie. "The Platform Organization." Chap. 5 in Designing Adaptive Organizations, edited by Charles Snow and Øystein D. Fjeldstad, 86–103. Cambridge Companions to Management. Cambridge University Press, 2023.
      • 2024
      • Working Paper

      The Uneven Impact of Generative AI on Entrepreneurial Performance

      By: Nicholas G. Otis, Rowan Clarke, Solène Delecourt, David Holtz and Rembrand Koning
      Scalable and low-cost AI assistance has the potential to improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it difficult to know whether recent AI advances can help business owners make... View Details
      Keywords: AI and Machine Learning; Performance Improvement; Small Business; Decision Choices and Conditions; Kenya
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      Otis, Nicholas G., Rowan Clarke, Solène Delecourt, David Holtz, and Rembrand Koning. "The Uneven Impact of Generative AI on Entrepreneurial Performance." Harvard Business School Working Paper, No. 24-042, December 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
      Keywords: AI and Machine Learning; Mathematical Methods
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      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).
      • 2023
      • Article

      Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness

      By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
      One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details
      Keywords: AI and Machine Learning; Mathematical Methods
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      Srinivas, Suraj, Sebastian Bordt, and Himabindu Lakkaraju. "Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness." Advances in Neural Information Processing Systems (NeurIPS) (2023).
      • November 2023
      • Case

      Open Source Machine Learning at Google

      By: Shane Greenstein, Martin Wattenberg, Fernanda B. Viégas, Daniel Yue and James Barnett
      Set in early 2023, the case exposes students to the challenges of managing open source software at Google. The case focuses on the challenges for Alex Spinelli, Vice President of Product Management for Core Machine Learning. He must set priorities for Google’s efforts... View Details
      Keywords: Decision Choices and Conditions; Technological Innovation; Open Source Distribution; Strategy; AI and Machine Learning; Applications and Software; Technology Industry; United States
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      Greenstein, Shane, Martin Wattenberg, Fernanda B. Viégas, Daniel Yue, and James Barnett. "Open Source Machine Learning at Google." Harvard Business School Case 624-015, November 2023.
      • November 2023
      • Case

      Riiid: Scaling AI Educational Services Globally

      By: John Jong-Hyun Kim, Nancy Dai and Ruru Hoong
      This article explores the definition and evolution of AI, its applications in education, and the role of AI, particularly in K-12 education. It discusses the founding of Riiid, an AI-driven educational technology company, and its journey in the education sector, with a... View Details
      Keywords: AI and Machine Learning; Economic Sectors; Technological Innovation; Education Industry; South Korea; Asia
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      Kim, John Jong-Hyun, Nancy Dai, and Ruru Hoong. "Riiid: Scaling AI Educational Services Globally." Harvard Business School Case 324-030, November 2023.
      • November 2023
      • Case

      Copilot(s): Generative AI at Microsoft and GitHub

      By: Frank Nagle, Shane Greenstein, Maria P. Roche, Nataliya Langburd Wright and Sarah Mehta
      This case tells the story of Microsoft’s 2018 acquisition of GitHub and the subsequent launch of GitHub Copilot, a tool that uses generative artificial intelligence to suggest snippets of code to software developers in real time. Set in late 2021, when Copilot was... View Details
      Keywords: Business Ventures; Strategy; AI and Machine Learning; Applications and Software; Product Launch; Information Technology Industry; Information Technology Industry; Information Technology Industry; United States; California
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      Nagle, Frank, Shane Greenstein, Maria P. Roche, Nataliya Langburd Wright, and Sarah Mehta. "Copilot(s): Generative AI at Microsoft and GitHub." Harvard Business School Case 624-010, November 2023.
      • November 2023 (Revised March 2024)
      • Technical Note

      Customer Data Privacy

      By: Eva Ascarza and Ta-Wei Huang
      This note provides an overview of the evolving landscape of customer data privacy in 2023. It highlights two pivotal aspects that make privacy a central concern for businesses: building and maintaining customer trust and navigating the intricate regulatory... View Details
      Keywords: Customer Relationship Management; Governance Compliance; Governing Rules, Regulations, and Reforms; Risk and Uncertainty; Reputation; Trust; Information Management; Retail Industry; Technology Industry; Financial Services Industry; Telecommunications Industry; Europe; United States
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      Ascarza, Eva, and Ta-Wei Huang. "Customer Data Privacy." Harvard Business School Technical Note 524-005, November 2023. (Revised March 2024.)
      • November 2023
      • Case

      Will Fintechs and Central Banks Play in Emtech's Sandbox?

      By: Daniel Isenberg and William R. Kerr
      In February 2023, Emtech’s founder Carmelle Cadet is facing a dilemma. Rapidly running out of cash, Cadet has a term sheet from a leading VC but has a choice of how to structure the investment. The decision will have significant implications for Cadet’s own stake, as... View Details
      Keywords: Cryptocurrency; Business Startups; Venture Capital; Cash Flow; Currency; Governing Rules, Regulations, and Reforms; Digital Platforms
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      Isenberg, Daniel, and William R. Kerr. "Will Fintechs and Central Banks Play in Emtech's Sandbox?" Harvard Business School Case 824-096, November 2023.
      • 2023
      • Book

      How the Harvard Business School Changed the Way We View Organizations

      By: Jay W. Lorsch
      The story of the field of organizational behavior (which overlaps considerably with the origin story of Harvard Business School) and how it created the “medical model” of systems thinking—anchored in the practices of listening, observing, testing, and only then... View Details
      Keywords: Organizational Behavior; Systems Thinking; Medical Model; Organizations; Behavior; System; History
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      Lorsch, Jay W. How the Harvard Business School Changed the Way We View Organizations. Business Expert Press, 2023.
      • November 2023 (Revised January 2024)
      • Case

      Bridgit: Persevere or Pivot?

      By: Reza Satchu and Patrick Sanguineti
      In late 2012, Mallorie Brodie and Lauren Lake, two young women in their final year of college, founded Bridgit, a technology startup that developed solutions to simplify vital but laborious processes within the construction industry. In the Fall of 2013, after months... View Details
      Keywords: Entrepreneur; Founder; Co-founders; Women Executives; Pivot; Startup; Business Model; Business Startups; Entrepreneurship; Applications and Software; Product Launch; Research and Development; Competition; Construction Industry; Technology Industry; United States; Canada
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      Satchu, Reza, and Patrick Sanguineti. "Bridgit: Persevere or Pivot?" Harvard Business School Case 824-118, November 2023. (Revised January 2024.)
      • November 2023 (Revised April 2024)
      • Case

      Khanmigo: Revolutionizing Learning with GenAI

      By: William A. Sahlman, Allison M. Ciechanover and Emily Grandjean
      Already a leader in the edtech space since its 2008 launch, Khan Academy was now one of the first edtech organizations to embrace generative artificial intelligence ("genAI"). In March 2023, Khan Academy began beta testing Khanmigo, a genAI “guide” and tutor built with... View Details
      Keywords: Technology Adoption; Leading Change; Entrepreneurship; Risk and Uncertainty; Education; AI and Machine Learning; Corporate Social Responsibility and Impact; Education Industry; Technology Industry; United States; San Francisco
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      Sahlman, William A., Allison M. Ciechanover, and Emily Grandjean. "Khanmigo: Revolutionizing Learning with GenAI." Harvard Business School Case 824-059, November 2023. (Revised April 2024.)
      • November–December 2023
      • Article

      Iterative Coordination and Innovation: Prioritizing Value over Novelty

      By: Sourobh Ghosh and Andy Wu
      An innovating organization faces the challenge of how to prioritize distinct goals of novelty and value, both of which underlie innovation. Popular practitioner frameworks like Agile management suggest that organizations can adopt an iterative approach of frequent... View Details
      Keywords: Innovation; Novelty; Goals; Specialization; Coordination; Field Experiment; Software Development; Agile; Scrum; Iteration; Iterative; Organizations; Innovation and Invention; Value; Goals and Objectives; Integration; Applications and Software
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      Ghosh, Sourobh, and Andy Wu. "Iterative Coordination and Innovation: Prioritizing Value over Novelty." Organization Science 34, no. 6 (November–December 2023): 2182–2206.
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