Data Science & AI Development

The Laboratory for Innovation Science at Harvard (LISH) is conducting a number of different crowdsourcing challenges and field research aimed at using the tools of data science and artificial intelligence to provide innovative solutions. LISH is working to help its partner organizations understand the value of data collection and the power of data analysis to drive problem solving. Browse LISH’s Data Science & Artificial Intelligence projects and papers below.

Publications

Hannah Mayer. 7/2020. “AI in Enterprise: AI Product Management.” Edited by Jin H. Paik, Jenny Hoffman, and Steven Randazzo.Abstract

While there are dispersed resources to learn more about artificial intelligence, there remains a need to cultivate a community of practitioners for cyclical exposure and knowledge sharing of best practices in the enterprise. That is why Laboratory for Innovation Science at Harvard launched the AI in the Enterprise series, which exposes managers and executives to interesting applications of AI and the decisions behind developing such tools. 

Moderated by HBS Professor and co-author of Competing in the Age of AI, Karim R. Lakhani, the July virtual session featured Peter Skomoroch from DataWrangling and formerly at LinkedIn. Together, they discussed what differentiates AI product management from managing other tech products and how to adapt to the uncertainty in the AI product lifecycle.

Hannah Mayer. 10/2020. “Data Science is the New Accounting.” Edited by Jin H. Paik and Jenny Hoffman.Abstract

In the October session of the AI in Enterprise series, HBS Professor and co-author of Competing in the Age of AI, Karim R. Lakhani and Roger Magoulas (Data Science Advisor) delved into O'Reilly's most recent survey of AI adoption in larger companies. The discussion explored common risk factors, techniques, tools, as well as the data governance and data conditioning that large companies are using to build and scale their AI practices. 

 

Read Hannah Mayer's recap of the event to learn more about what senior managers in enterprises need to know about AI - particularly, if they want to adopt at scale. 

 

Hannah Mayer. 9/2020. “AI in Enterprise: In Tech We Trust.. Maybe Too Much?Edited by Jin H. Paik and Jenny Hoffman.Abstract

While there are dispersed resources to learn more about artificial intelligence, there remains a need to cultivate a community of practitioners for cyclical exposure and knowledge sharing of best practices in the enterprise. That is why Laboratory for Innovation Science at Harvard launched the AI in the Enterprise series, which exposes managers and executives to interesting applications of AI and the decisions behind developing such tools. 

In the September session of the AI in Enterprise series, HBS Professor and co-author of Competing in the Age of AI, Karim R. Lakhani spoke with Latanya Sweeney about algorithmic bias, data privacy, and the way forward for enterprises adopting AI. They explored how AI and ML can impact society in unexpected ways and what senior enterprise leaders can do to avoid negative externalities. Professor of the Practice of Government and Technology at the Harvard Kennedy School and in the Harvard Faculty of Arts and Sciences, director and founder of the Data Privacy Lab, and former Chief Technology Officer at the U.S. Federal Trade Commission, Latanya Sweeney pioneered the field known as data privacy and launched the emerging area known as algorithmic fairness.

Hannah Mayer, Jin H. Paik, Timothy DeStefano, and Jenny Hoffman. 8/2020. “From Craft to Commodity: The Evolution of AI in Pharma and Beyond”.Abstract

While there are dispersed resources to learn more about artificial intelligence, there remains a need to cultivate a community of practitioners for cyclical exposure and knowledge sharing of best practices in the enterprise. That is why Laboratory for Innovation Science at Harvard launched the AI in the Enterprise series, which exposes managers and executives to interesting applications of AI and the decisions behind developing such tools. 

Moderated by HBS Professor and co-author of Competing in the Age of AI, Karim R. Lakhani, the August virtual session featured Reza Olfati-Saber, an experienced academic researcher currently managing teams of data scientists and life scientists across the globe for Sanofi. Together, they discussed the evolution of AI in life science experimentation and how it may become the determining factor for R&D success in pharma and other industries.

Jin H. Paik, Steven Randazzo, and Jenny Hoffman. 6/2020. “AI in the Enterprise: How Do I Get Started?”.Abstract

While there are dispersed resources to learn more about artificial intelligence, there remains a need to cultivate a community of practitioners for cyclical exposure and knowledge sharing of best practices in the enterprise. That is why Laboratory for Innovation Science at Harvard launched the AI in the Enterprise series, which exposes managers and executives to interesting applications of AI and the decisions behind developing such tools. 

Moderated by HBS Professor and co-author of Competing in the Age of AI, Karim R. Lakhani, the most recent virtual session with over 240 attendees featured Rob May, General Partner at PJC, an early-stage venture capital firm, and founder of Inside AI, a premier source for information on AI, robotics and neurotechnology. Together, they discussed why we have seen a rise in interest in AI, what managers should consider when wading into the AI waters, and what steps they can take when it is time to do so. 

Marco Iansiti and Karim R. Lakhani. 3/3/2020. “From Disruption to Collision: The New Competitive Dynamics.” MIT Sloan Management Review.Abstract
In the age of AI, traditional businesses across the economy are being attacked by highly scalable data-driven companies whose operating models leverage network effects to deliver value.
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