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- November 2023
- Case
Zest AI: Machine Learning and Credit Access
By: David S. Scharfstein and Ryan Gilland
Scharfstein, David S., and Ryan Gilland. "Zest AI: Machine Learning and Credit Access." Harvard Business School Case 224-033, November 2023.
- November–December 2023
- Article
Keep Your AI Projects on Track
By: Iavor Bojinov
AI—and especially its newest star, generative AI—is today a central theme in corporate boardrooms, leadership discussions, and casual exchanges among employees eager to supercharge their productivity. Sadly, beneath the aspirational headlines and tantalizing potential...
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Keywords:
Generative Models;
AI and Machine Learning;
Success;
Failure;
Product Development;
Technology Adoption
Bojinov, Iavor. "Keep Your AI Projects on Track." Harvard Business Review 101, no. 6 (November–December 2023): 53–59.
- October 2023
- Case
ReUp Education: Can AI Help Learners Return to College?
By: Kris Ferreira, Christopher Thomas Ryan and Sarah Mehta
Founded in 2015, ReUp Education helps “stopped out students”—learners who have stopped making progress towards graduation—achieve their college completion goals. The company relies on a team of success coaches to engage with learners and help them reenroll. In 2019,...
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- October 2023
- Case
Ball: EVA Driving the World’s Leading Can Manufacturer (A)
By: Jonas Heese and Susan Pinckney
Ball used Economic Value Added analysis to determine if it should open a new metal can manufacturing facility, which mandated closing two recently acquired factories, or recapitalize and update the two legacy factories.
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Keywords:
Accounting;
Budgets and Budgeting;
Cost Accounting;
Financial Reporting;
Financial Statements;
Buildings and Facilities;
Green Building;
Acquisition;
Mergers and Acquisitions;
Customer Satisfaction;
Decision Making;
Decisions;
Forecasting and Prediction;
Engineering;
Machinery and Machining;
Finance;
Asset Pricing;
Corporate Finance;
Capital;
Cost;
Financial Management;
Goods and Commodities;
Compensation and Benefits;
Executive Compensation;
Employee Relationship Management;
Management;
Goals and Objectives;
Resource Allocation;
Strategy;
Business Strategy;
Corporate Strategy;
Food and Beverage Industry;
United States;
Arizona;
California;
Texas
- October 2023
- Article
Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
We study how a regulator can best target inspections. Our case study is a U.S. Occupational Safety and Health Administration (OSHA) program that randomly allocated some inspections. On average, each inspection averted 2.4 serious injuries (9%) over the next five years....
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Keywords:
Safety Regulations;
Regulations;
Regulatory Enforcement;
Machine Learning Models;
Safety;
Operations;
Service Operations;
Production;
Forecasting and Prediction;
Decisions;
United States
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA." American Economic Journal: Applied Economics 15, no. 4 (October 2023): 30–67.
- October 14, 2023
- Article
Will Consumers Buy Selfish Self-Driving Cars?
De Freitas, Julian. "Will Consumers Buy Selfish Self-Driving Cars?" Wall Street Journal (October 14, 2023), C5.
- September 2023
- Case
TetraScience: Noise and Signal
By: Thomas R. Eisenmann and Tom Quinn
In 2019, TetraScience CEO “Spin” Wang needed advice. Five years earlier, he had cofounded a startup that saw early success with a hardware product designed to help laboratory scientists in the biotechnology and pharmaceutical spaces more easily collect data from...
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Keywords:
Entrepreneurship;
Business Growth and Maturation;
Business Organization;
Restructuring;
Forecasting and Prediction;
Digital Platforms;
Analytics and Data Science;
AI and Machine Learning;
Organizational Structure;
Network Effects;
Competitive Strategy;
Biotechnology Industry;
Pharmaceutical Industry;
United States;
Boston
- 2023
- Working Paper
Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality
By: Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani
The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine...
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Keywords:
Large Language Model;
AI and Machine Learning;
Performance Efficiency;
Performance Improvement
Dell'Acqua, Fabrizio, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, and Karim R. Lakhani. "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality." Harvard Business School Working Paper, No. 24-013, September 2023.
- September 2023
- Case
AI21 Labs in 2023: Strategy for Generative AI
By: David Yoffie, Orna Dan and Elena Corsi
Tel Aviv-based generative artificial intelligence company AI21 Labs considers how to remain competitive among the biggest players in the technology and AI arena.
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Keywords:
Decision Making;
Information Technology;
AI and Machine Learning;
Innovation Strategy;
Growth and Development Strategy;
Technology Industry
Yoffie, David, Orna Dan, and Elena Corsi. "AI21 Labs in 2023: Strategy for Generative AI." Harvard Business School Case 724-383, September 2023.
- 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...
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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...
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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.
- August 2023 (Revised August 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...
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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;
Auto Industry;
Technology Industry;
Africa;
Asia;
Europe;
North and Central America;
Oceania;
South America
- 2023
- Working Paper
The Crowdless Future? How Generative AI Is Shaping the Future of Human Crowdsourcing
The rapid advances in generative AI have the potential to reshape organizational innovation, raising uncertainty about the role of human solvers in this new era of augmented intelligence. We initiated a crowdsourcing challenge focused on sustainable, circular economy...
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Boussioux, Léonard, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim R. Lakhani. "The Crowdless Future? How Generative AI Is Shaping the Future of Human Crowdsourcing." Harvard Business School Working Paper, No. 24-005, July 2023. (Revised November 2023.)
- 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...
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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.
- July–August 2023
- Article
What Smart Companies Know About Integrating AI
By: Silvio Palumbo and David Edelman
AI has the power to gather, analyze, and utilize enormous volumes of individual customer data to achieve precision and scale in personalization. The experiences of Mercury Financial, CVS Health, and Starbucks debunk the prevailing notion that extracting value from AI...
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Keywords:
AI and Machine Learning;
Customization and Personalization;
Integration;
Technology Adoption
Palumbo, Silvio, and David Edelman. "What Smart Companies Know About Integrating AI." Harvard Business Review 101, no. 4 (July–August 2023): 116–125.
- 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...
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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
- Supplement
Honeycomb (B): Jumping on The Generative AI Bandwagon?
By: Jeffrey J. Bussgang and Kumba Sennaar
Honeycomb, an audio app enabling users to record stories and save family memories, considers pivoting to embrace generative AI. What should the co-founders business model look like if they pursued this new direction?
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- July 2023 (Revised August 2023)
- 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...
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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 August 2023.)
- 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...
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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...
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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.)