Scaling up analogical innovation with crowds and AI.

Kittur, Aniket; Yu, Lixiu; Hope, Tom; Chan, Joel; Lifshitz-Assaf, Hila; Gilon, Karni; Ng, Felicia; Kraut, Robert E; Shahaf, Dafna

Kittur, Aniket; Yu, Lixiu; Hope, Tom; Chan, Joel; Lifshitz-Assaf, Hila; Gilon, Karni; Ng, Felicia; Kraut, Robert E; Shahaf, Dafna.

Afiliación

Kittur A; Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA 15213; nkittur@cs.cmu.edu.
Yu L; Robert Bosch, Research and Technology Center, Division 3, Pittsburgh, PA 15222.
Hope T; School of Computer Science and Engineering, The Hebrew University of Jerusalem, 9190401 Jerusalem, Israel.
Chan J; College of Information Studies, University of Maryland, College Park, MD 20742.
Lifshitz-Assaf H; Department of Information, Operations and Management Sciences, Leonard N. Stern School of Business, New York University, New York, NY 10012.
Gilon K; School of Computer Science and Engineering, The Hebrew University of Jerusalem, 9190401 Jerusalem, Israel.
Ng F; Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA 15213.
Kraut RE; Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA 15213.
Shahaf D; School of Computer Science and Engineering, The Hebrew University of Jerusalem, 9190401 Jerusalem, Israel.

Proc Natl Acad Sci U S A ; 116(6): 1870-1877, 2019 02 05.

Article en En | MEDLINE | ID: mdl-30718420

Palabras clave

AI; analogy; crowdsourcing; innovation; machine learning

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2019 Tipo del documento: Article