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New research on technological innovation from Harvard Business School faculty on issues including using data mining to improve productivity, why business IT innovation is so difficult, and the business implications of the technology revolution.
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Can AI and Machine Learning Help Park Rangers Prevent Poaching?

Re: Brian L. Trelstad

Globally there are too few park rangers to prevent the illegal trade of wildlife across borders, or poaching. In response, Spatial Monitoring and Reporting Tool (SMART) was created by a coalition of conservation organizations to take historical data and create geospatial mapping tools that enable more efficient deployment of rangers. SMART had demonstrated significant improvements in patrol coverage, with some observed reductions in poaching. Then a new predictive analytic tool, the Protection Assistant for Wildlife Security (PAWS), was created to use artificial intelligence (AI) and machine learning (ML) to try to predict where poachers would be likely to strike. Jonathan Palmer, Executive Director of Conservation Technology for the Wildlife Conservation Society, already had a good data analytics tool to help park rangers manage their patrols. Would adding an AI- and ML-based tool improve outcomes or introduce new problems? Harvard Business School senior lecturer Brian Trelstad discusses the importance of focusing on the use case when determining the value of adding a complex technology solution in his case, “SMART: AI and Machine Learning for Wildlife Conservation.”

ChatGPT: Did Big Tech Set Up the World for an AI Bias Disaster?

by Scott Van Voorhis

Google tried to silence AI bias warnings from ethicist Timnit Gebru. Will a world enamored with OpenAI's ChatGPT be able to confront them? Tsedal Neeley reflects on Gebru's experience in a case study, and offers advice on managing the ethical risks of AI.

Can Insurance Technology Solve the Uninsured Driver Problem?

by Ray Kluender

High fees prevent many drivers from buying auto insurance—often with catastrophic consequences. Raymond Kluender offers a novel way to make coverage affordable and roads safer: Let drivers pay for only the days they drive.

What Makes Employees Trust (vs. Second-Guess) AI?

by Rachel Layne

While executives are quick to adopt artificial intelligence, front-line employees might be less willing to take orders from an algorithm. Research by the Laboratory for Innovation Science at Harvard sheds light on what it takes for people to get comfortable with machine learning.

Metaverse Seoul: How One City Used Citizen Input to Pilot a Government-Run Metaverse

Re: Mitchell B. Weiss

In May 2022, the Seoul Metropolitan Government in Seoul, Korea launched the pilot of Metaverse Seoul, a virtual version of Seoul’s mayor’s office. As they worked towards building a broad, immersive, online government platform, they hoped to gain insights from citizens about everything from popular local tourist sites that could be experienced virtually to government services that could be delivered in the metaverse. But to do that, the team had to figure out how to solicit ideas from citizens and then determine which ideas to put to use. Professor Mitchell Weiss discusses their approach, as well as questions relating to his research on public entrepreneurship and what he calls “possibility government,” in his case, “Metaverse Seoul.”

The Value of Descriptive Analytics: Evidence from Online Retailers

by Ron Berman and Ayelet Israeli

Analytics are descriptive when they describe what happened. Descriptive-analytics solutions are popular among marketers and retailers. This paper provides a benchmark for the benefits of using a descriptive dashboard and illustrates how to potentially extract these benefits.

What Can Economics Say About Alzheimer's Disease?

by Amitabh Chandra, Courtney Coile, and Corina Mommaerts

This essay discusses the role of market frictions and "missing medicines" in drug innovation and highlights how frameworks and toolkits of economists can help our understanding of the determinants and effects of Alzheimer's disease on health.

From the Plow to the Pill: How Technology Shapes Our Lives

by Dina Gerdeman

Many technologies have upended long-held beliefs about love, sex, marriage, and reproduction, says Debora Spar in a new book, Work Mate Marry Love: How Machines Shape Our Human Destiny. Open for comment; 0 Comments.

Is a Pandemic the Best Time To Try Out a New Idea?

Re: Mitchell B. Weiss

Singapore's new nationwide, Bluetooth-based contact tracing program TraceTogether must overcome privacy issues to be effective. Would Singaporeans adopt TraceTogether? Professor Mitch Weiss discusses his new case study. Open for comment; 0 Comments.

Are Digital Organizations Better at Overcoming COVID?

by Danielle Kost

Experts from Harvard Business School's Digital Initiative discuss how technology is helping leading companies gain an edge during the coronavirus pandemic. Open for comment; 0 Comments.

Autonomous Vehicles Are Ready to Disrupt Society, Business—and You

Re: Elie Ofek & William R. Kerr

The rise of autonomous vehicles has enormous implications for business and society. Professors William R. Kerr and Elie Ofek explore the factors influencing their development and commercialization. Open for comment; 0 Comments.

The One Good Thing Caused by COVID-19: Innovation

by Hong Luo and Alberto Galasso

Hong Luo and Alberto Galasso see risk-mitigating innovation everywhere the virus spreads. Open for comment; 0 Comments.

Warring Algorithms Could Be Driving Up Consumer Prices

by Kristen Senz

Companies increasingly use software to conduct rapid price changes. Alexander MacKay explains why firms might benefit but consumers should be worried. Open for comment; 0 Comments.

From Know-It-Alls to Learn-It-Alls: Executive Development in the Era of Self-Refining Algorithms, Collaborative Filtering and Wearable Computing

by Mihnea Moldoveanu and Das Narayandas

Learning happens most reliably and efficiently when it is contextualized, personalized, and socialized. This is important for executive learning in particular and adult learning more generally. Innovators and educational designers can leverage technologies that enable sensing, interacting, computing, searching, and storing to produce learner-optimal experiences.

It's No Joke: AI Beats Humans at Making You Laugh

by Dina Gerdeman

New research shows people don’t trust recommendations from algorithms—and that’s a problem for companies that increasingly rely on AI-based technology to persuade consumers. Michael H. Yeomans explains how businesses can overcome that bias. Open for comment; 0 Comments.

Gender Bias Complaints against Apple Card Signal a Dark Side to Fintech

by Karen G. Mills

The possibility that Apple Card applicants were subject to gender bias opens a new frontier for the financial services sector in which regulators are largely absent, argues Karen Mills. Open for comment; 0 Comments.

Soul and Machine (Learning)

by Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano et al.

This paper argues with examples and predictions that while marketing science theory, engineering, and machine learning capabilities are changing the way we think about marketing, true advances will come when marketing managers know when to trust the machine and when to trust their instincts.

Female Inventors and Inventions

by Rembrand Koning, Sampsa Samila, and John-Paul Ferguson

Does the gender of inventors make a difference for who benefits from their inventions? Analysis of all U.S. biomedical patents issued between 1976 and 2010 shows that research teams with women were more likely to produce patents addressing women’s health conditions, especially when female researchers led the teams. This link suggests that the dearth of women inventors might also result in fewer female-focused inventions.

Who Drives Digital Innovation? Evidence from the US Medical Device Industry

by Cirrus Foroughi and Ariel Dora Stern

Major industries are undergoing a digital transformation, in which key aspects of new product development are migrating to a software-driven context. In the medical device industry, experience matters, as does the geographic clustering of new product development, which gives advantages to both new entrants and incumbent firms.

What Machine Learning Teaches Us about CEO Leadership Style

by Michael Blanding

Tarun Khanna and Prithwiraj Choudhury use machine-learning technology to look for links between a CEO's communications style and company performance. Open for comment; 0 Comments.