[Ramm] [Gendered Innovations] artificial intelligence, robotics, life sciences

[Londa Schiebinger]

Some items of interest!
1. Anupam Datta designed a programme<https://www.economist.com/news/science-and-technology/21737018-if-it-cannot-who-will-trust-it-artificial-intelligence-thrive-it-must> to test whether AI showed bias in hiring new employees. Machine learning can be used to pre-select candidates based on various criteria such as skills and education. This produces a score which indicates how fit the candidate is for the job. In a candidate selection program, Datta's program randomly changed the gender and the weight applicants said they could lift in their application, and if there was no change in the number of women that were pre-selected for interviews, then it is not the applicant's sex that determined the hiring process. See: https://theconversation.com/artificial-intelligence-could-reinforce-societys-gender-equality-problems-92631  Stanford Gendered Innovations is doing a Workshop on Gender/Fairness and Machine Learning in late March. We will be preparing a case study mapping problems, solutions, and who should make decisions about what is "fair"? (And what is fair??)
2.Jahna Otterbacher et al.:  S/he's too Warm/Agentic! The Influence of Gender on Uncanny Reactions to Robots. Gender stereotypes are strong influences on human behavior. Given our tendency to anthropomorphize, incorporating gender cues into a robot's design can influence acceptance by humans. However, little is known about the interaction between human and robot gender...to read the study:  http://www.jahna-otterbacher.net/wp-content/uploads/2017/06/robot-gender-fixed.pdf
3. Petra Verdonk, Janusz Janczukowicz, Editorial, Diversity in Medical Education: While medical schools need to address the health care needs of diverse populations and to accommodate to the diverse needs of their students and staff, addressing and studying diversity in medical education remains challenging. In teaching cultural competence, several approaches are identified, including a cultural expertise approach, a cultural sensibility approach and a cross-cultural approach. We propose the analysis of diversity related issues at three distinct levels: fixing the numbers, fixing the institutions and fixing the knowledge. https://www.mededpublish.org/manuscripts/1415
4. Dyna Rochmyaningsih. "Showcase scientists from the global south", https://www.nature.com/articles/d41586-018-00662-w
5. On p. 8 of this document, you find a link to Participant Portal: "Topics with a Gender Dimension"--from the European Commission. These are topics where the EC requires applicants to address sex/gender analysis in their proposal for EC funding: German Federal Ministry of Education and Research, Gender and Equal Opportunities under Horizon 2020: https://www.bmbf.de/pub/Gender_and_Equal_Opportunities_under_Horizon_2020.pdf
6. From Paul Fowler's group: "The human fetal adrenal produces cortisol but no detectable aldosterone throughout the second trimester." https://link.springer.com/article/10.1186/s12916-018-1009-7


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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