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- All HBS Web
(4,043)
- Faculty Publications (1,260)
- 2023
- Article
On the Impact of Actionable Explanations on Social Segregation
By: Ruijiang Gao and Himabindu Lakkaraju
As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research... View Details
Gao, Ruijiang, and Himabindu Lakkaraju. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.
- September–October 2023
- Article
Reskilling in the Age of AI
In the coming decades, as the pace of technological change continues to increase, millions of workers may need to be not just upskilled but reskilled—a profoundly complex societal challenge that will sometimes require workers to both acquire new skills and... View Details
Keywords: Competency and Skills; AI and Machine Learning; Training; Adaptation; Employees; Digital Transformation
Tamayo, Jorge, Leila Doumi, Sagar Goel, Orsolya Kovács-Ondrejkovic, and Raffaella Sadun. "Reskilling in the Age of AI." Harvard Business Review 101, no. 5 (September–October 2023): 56–65.
- September 2023
- Article
The Dynamics of Team Learning: Harmony and Rhythm in Teamwork Arrangements for Innovation
By: Jean-François Harvey, Johnathan R. Cromwell, Kevin J. Johnson and Amy C. Edmondson
Innovation teams must navigate inherent tensions between different learning activities to produce high levels of performance. Yet, we know little about how teams combine these activities—notably reflexive, experimental, vicarious, and contextual learning—most... View Details
Keywords: Groups and Teams; Learning; Performance Effectiveness; Collaborative Innovation and Invention
Harvey, Jean-François, Johnathan R. Cromwell, Kevin J. Johnson, and Amy C. Edmondson. "The Dynamics of Team Learning: Harmony and Rhythm in Teamwork Arrangements for Innovation." Administrative Science Quarterly 68, no. 3 (September 2023): 601–647.
- August 2023 (Revised December 2023)
- Case
Automating Morality: Ethics for Intelligent Machines
By: Joseph L. Badaracco Jr. and Tom Quinn
As autonomy became a more significant part of modern life – most notably in autonomous vehicles (AVs), such as Teslas – ethical debates about whether and how to impart ethics to machines heated up. Utilitarians pointed out that autonomous vehicles crashed much less... View Details
Keywords: Cost vs Benefits; Judgments; Fairness; Moral Sensibility; Values and Beliefs; Cross-Cultural and Cross-Border Issues; Disruptive Innovation; Technology Adoption; Risk and Uncertainty; Cognition and Thinking; Technological Innovation; Auto Industry; Technology Industry; Africa; Asia; Europe; North and Central America; Oceania; South America
Badaracco, Joseph L., Jr., and Tom Quinn. "Automating Morality: Ethics for Intelligent Machines." Harvard Business School Case 324-007, August 2023. (Revised December 2023.)
- 2024
- Working Paper
The Crowdless Future? Generative AI and Creative Problem Solving
The rapid advances in generative artificial intelligence (AI) open up attractive opportunities for creative problem-solving through human-guided AI partnerships. To explore this potential, we initiated a crowdsourcing challenge focused on sustainable, circular economy... View Details
Keywords: Large Language Models; Crowdsourcing; Generative Ai; Creative Problem-solving; Organizational Search; AI-in-the-loop; Prompt Engineering; AI and Machine Learning; Innovation and Invention
Boussioux, Léonard, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim R. Lakhani. "The Crowdless Future? Generative AI and Creative Problem Solving." Harvard Business School Working Paper, No. 24-005, July 2023. (Revised July 2024.)
- 2023
- Working Paper
Channeled Attention and Stable Errors
By: Tristan Gagnon-Bartsch, Matthew Rabin and Joshua Schwartzstein
We develop a framework for assessing when somebody will eventually notice that she has
a misspecified model of the world, premised on the idea that she neglects information that
she deems—through the lens of her misconceptions—to be irrelevant. In doing so, we... View Details
Gagnon-Bartsch, Tristan, Matthew Rabin, and Joshua Schwartzstein. "Channeled Attention and Stable Errors." Working Paper, August 2023. (Revise and Resubmit, Quarterly Journal of Economics.)
- August 2023
- Article
Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel
By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use... View Details
Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel." Nature Machine Intelligence 5, no. 8 (August 2023): 873–883.
- 2023
- Article
Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten
By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details
Keywords: Analytics and Data Science; AI and Machine Learning; Decision Making; Governing Rules, Regulations, and Reforms
Lakkaraju, Himabindu, Satyapriya Krishna, and Jiaqi Ma. "Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 17808–17826.
- 2023
- Working Paper
Was That a Microaggression: A Multilevel Theory of Microaggression Sensemaking
By: Summer R. Jackson and Basima Tewfik
- 2023
- Working Paper
Beyond the Hype: Unveiling the Marginal Benefits of 3D Virtual Tours in Real Estate
By: Mengxia Zhang and Isamar Troncoso
3D virtual tours (VTs) have become a popular digital tool in real estate platforms, enabling potential buyers to virtually walk through the houses they search for online. In this paper, we study home sellers’ adoption of VTs and the VTs’ relative benefits compared to... View Details
Zhang, Mengxia, and Isamar Troncoso. "Beyond the Hype: Unveiling the Marginal Benefits of 3D Virtual Tours in Real Estate." Harvard Business School Working Paper, No. 24-003, July 2023.
- July 2023 (Revised October 2024)
- Case
Revenue Recognition at Stride Funding: Making Sense of Revenues for a Fintech Startup
By: Paul M. Healy and Jung Koo Kang
The case explores the challenges of revenue recognition and financial reporting for Stride Funding (Stride), a fintech startup that has disrupted the student loan market. Stride leveraged proprietary machine learning and financial models to underwrite alternative... View Details
Keywords: Revenue Recognition; Financial Reporting; Entrepreneurial Finance; Business Startups; Growth and Development Strategy; Governance Compliance; Accrual Accounting; Financial Services Industry; United States
Healy, Paul M., and Jung Koo Kang. "Revenue Recognition at Stride Funding: Making Sense of Revenues for a Fintech Startup." Harvard Business School Case 124-015, July 2023. (Revised October 2024.)
- July 2023
- Case
DayTwo: Going to Market with Gut Microbiome (Abridged)
By: Ayelet Israeli
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. After a first year of trial rollout in... View Details
Keywords: Business Startups; AI and Machine Learning; Nutrition; Market Entry and Exit; Product Marketing; Distribution Channels
Israeli, Ayelet. "DayTwo: Going to Market with Gut Microbiome (Abridged)." Harvard Business School Case 524-015, July 2023.
- 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
Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
- 2023
- Working Paper
The Complexity of Economic Decisions
By: Xavier Gabaix and Thomas Graeber
We propose a theory of the complexity of economic decisions. Leveraging a macroeconomic framework of production functions, we conceptualize the mind as a cognitive economy, where a task’s complexity is determined by its composition of cognitive operations. Complexity... View Details
Gabaix, Xavier, and Thomas Graeber. "The Complexity of Economic Decisions." Harvard Business School Working Paper, No. 24-049, February 2024.
- 2024
- Working Paper
Second- versus Third-party Audit Quality: Evidence from Global Supply Chain Monitoring
By: Maria R. Ibanez, Ashley Palmarozzo, Jodi L. Short and Michael W. Toffel
Capitalizing on the superior credibility and flexibility and potential lower cost of external assessments, many global buyers are relying less on their own employee (“second-party”) auditors and more on third-party auditors to monitor and prevent environmental and... View Details
Keywords: Auditing; Audit Quality; Working Conditions; Sustainability; Empirical Operations; Empirical Service Operations; Sustainability Management; Corporate Accountability; Corporate Social Responsibility and Impact; Supply Chain Management
Ibanez, Maria R., Ashley Palmarozzo, Jodi L. Short, and Michael W. Toffel. "Second- versus Third-party Audit Quality: Evidence from Global Supply Chain Monitoring." Working Paper, August 2024.
- June 2023 (Revised July 2023)
- Case
Social Media Background Screening at Fama Technologies
By: Joseph Pacelli, Jillian Grennan and Alexis Lefort
Fama Technologies is an online screening company that uses AI to analyze job applicants' publicly available online content for signs of risk and culture fit. The case opens with Ben Mones, founder and CEO, looking to secure funding from venture firms. He is running... View Details
Keywords: Human Resources; Recruitment; Retention; Selection and Staffing; Organizational Culture; Talent and Talent Management; AI and Machine Learning; Social Media; Venture Capital; Entrepreneurship; United States
Pacelli, Joseph, Jillian Grennan, and Alexis Lefort. "Social Media Background Screening at Fama Technologies." Harvard Business School Case 123-010, June 2023. (Revised July 2023.)
- June 20, 2023
- Article
Cautious Adoption of AI Can Create Positive Company Culture
By: Joseph Pacelli and Jonas Heese
Pacelli, Joseph, and Jonas Heese. "Cautious Adoption of AI Can Create Positive Company Culture." CMR Insights (June 20, 2023).
- 2023
- Working Paper
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details
Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
- June 12, 2023
- Article
How AI Will Accelerate the Circular Economy
By: Shirley Lu and George Serafeim
Despite living on a planet with finite resources, our economy remains largely linear and full of single-use products. The shift toward a circular economy, where companies recover or recycle resources, has hit roadblocks, including low value of used products and high... View Details
Keywords: Recycling; Materials Management; Innovation and Management; Technological Innovation; Climate Change; Environmental Sustainability; AI and Machine Learning; Operations; Industrial Products Industry; Consumer Products Industry; Technology Industry
Lu, Shirley, and George Serafeim. "How AI Will Accelerate the Circular Economy." Harvard Business Review Digital Articles (June 12, 2023).
- May–June 2023
- Article
Analytics for Marketers: When to Rely on Algorithms and When to Trust Your Gut
By: Fabrizio Fantini and Das Narayandas
Advanced analytics can help companies solve a host of management problems, including those related to marketing, sales, and supply-chain operations, which can lead to a sustainable competitive advantage. But as more data becomes available and advanced analytics are... View Details
Fantini, Fabrizio, and Das Narayandas. "Analytics for Marketers: When to Rely on Algorithms and When to Trust Your Gut." Harvard Business Review 101, no. 3 (May–June 2023): 82–91.