[Ramm] [Gendered Innovations] US NIH request for info; gender and machine learning; diversity in teams

[Londa Schiebinger]

1. NIH request for information:  ORWH has published a Request for Information (RFI) on the next Trans-NIH Strategic Plan for Research on Women's Health.  It can be found in the latest NIH Guide (https://grants.nih.gov/grants/guide/notice-files/NOT-OD-17-108.html).

2. Gender and machine learning:  Semantics derived automatically from language corpora contain human-like biases by Aylin Caliskan, Joanna Bryson, Arvind Narayanan See all authors and affiliations, Science  14 Apr 2017: Vol. 356, Issue 6334, pp. 183-186 DOI: 10.1126/science.aal4230: http://science.sciencemag.org/content/356/6334/183

3. Gender and machine learning: Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints by Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez. Kai-Wei Chang

4. Fewer Women Run Big Companies Than Men Named John: https://www.nytimes.com/2015/03/03/upshot/fewer-women-run-big-companies-than-men-named-john.html?_r=0

5. Harvard Business Review on improving diversity in teams: https://hbr.org/2017/07/what-we-learned-from-improving-diversity-rates-at-pinterest


All best, Londa

Londa Schiebinger
Director, EU/US Gendered Innovations in Science, Health & Medicine, Engineering, and Environment Project
John L. Hinds Professor of History of Science, Stanford University
http://www.stanford.edu/dept/HPST/schiebinger.html

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