1 code implementation • 19 Apr 2024 • Alireza Javadian Sabet, Sarah H. Bana, Renzhe Yu, Morgan R. Frank
Higher education plays a critical role in driving an innovative economy by equipping students with knowledge and skills demanded by the workforce.
no code implementations • 6 Nov 2023 • Morgan R. Frank
Exciting advances in generative artificial intelligence (AI) have sparked concern for jobs, education, productivity, and the future of work.
no code implementations • 17 Jul 2023 • Joshua R. Minot, Marc Maier, Bradford Demarest, Nicholas Cheney, Christopher M. Danforth, Peter Sheridan Dodds, Morgan R. Frank
This suggests that females' resumes that are semantically similar to males' resumes may have greater wage parity.
no code implementations • 7 Jun 2023 • Ziv Epstein, Aaron Hertzmann, Laura Herman, Robert Mahari, Morgan R. Frank, Matthew Groh, Hope Schroeder, Amy Smith, Memo Akten, Jessica Fjeld, Hany Farid, Neil Leach, Alex Pentland, Olga Russakovsky
A new class of tools, colloquially called generative AI, can produce high-quality artistic media for visual arts, concept art, music, fiction, literature, video, and animation.
no code implementations • 25 Oct 2021 • Benjamin Meindl, Morgan R. Frank, Joana Mendonça
Our work not only allows analyses of the impact of 4IR technologies as a whole, but also provides exposure scores for more than 300 technology fields, such as AI and smart office technologies.
no code implementations • 18 Sep 2020 • Jaehyuk Park, Morgan R. Frank, Lijun Sun, Hyejin Youn
It is therefore important to recognize that classification system are not necessarily static, especially for economic systems, and even more so in urban areas where most innovation takes place and is implemented.
3 code implementations • 5 Aug 2020 • Ryan J. Gallagher, Morgan R. Frank, Lewis Mitchell, Aaron J. Schwartz, Andrew J. Reagan, Christopher M. Danforth, Peter Sheridan Dodds
A common task in computational text analyses is to quantify how two corpora differ according to a measurement like word frequency, sentiment, or information content.
no code implementations • 15 Jun 2014 • Peter Sheridan Dodds, Eric M. Clark, Suma Desu, Morgan R. Frank, Andrew J. Reagan, Jake Ryland Williams, Lewis Mitchell, Kameron Decker Harris, Isabel M. Kloumann, James P. Bagrow, Karine Megerdoomian, Matthew T. McMahon, Brian F. Tivnan, Christopher M. Danforth
Using human evaluation of 100, 000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language, observing that (1) the words of natural human language possess a universal positivity bias; (2) the estimated emotional content of words is consistent between languages under translation; and (3) this positivity bias is strongly independent of frequency of word usage.