Interview by Jyoti Narang Apr 5, 2017 Photo (above): From right to left, Elaine Chew and Jyoti Narang. Photo by Anna Xambó at Georgia Tech. A few words about Elaine: Elaine Chew is Professor of Digital Media in the School of Electronic Engineering and Computer Science at Queen Mary University of London, where she is…
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This article explains the artificial intelligence (AI) algorithm Word-Embedding Association Test (WEAT), which looks into bias in English language. The algorithm is based on the Implicit Association Test (IAT), used to measure implicit bias. The results of the algorithm are promising as an indicator of biases in human language. Read more here
This article asks 17 women from Microsoft research their thoughts on how they envision their fields both in 2017 and in 10 years time. The fields discussed include natural language processing, machine learning, artificial intelligence, information retrieval, biological computation, virtual reality, social sciences, economics, software engineering, human-centered computing, mathematics, cryptography, ecology, computer vision, mobile computing,…
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Improving gender diversity in AI includes questioning the language and data sets created by a male-dominated field. Some women in the field are working on the next generation by mentoring girls and making more visible their own work. Find out more at http://www.bloomberg.com/news/Readings/2016-06-23/artificial-intelligence-has-a-sea-of-dudes-problem
