By Deslyn Taylor, NCWQ Education Advisor
Much has appeared in the media recently about bullying and particularly about bullying against women. The Queensland Government has recently led a National Day of Action Against Bullying and Violence (NDA). This was aimed at “empowering students to feel confident and to be part of the solution to bullying, both online and in the schoolyard”.
It is important to realise that students are subjected to both online and physical bullying. The Queensland Government has created some support material to help with this “The courses – ‘Your Digital Journey’, ‘Enhancing your digital identity’ and ‘CyberSafety – Making Positive Online Choices’ – will give students the tools and knowledge they need to keep online communication respectful, safe and kind.” Physical bullying requires a different approach.
For more information visit https://bullyingnoway.gov.au/
These experiences with bullying often follow girls through into adulthood. Many have assumed that girls are not confident of their technical skills. A recent study has found that this is not correct. “We found the women students in STEM are equally if not more confident than men in their problem-solving and decision-making, goal-directed behaviour, self-esteem, career exploration and career awareness. They were also more likely to have a “plan B” for their careers.” Despite this “The fact remains that in addition to men dominating STEM professions such as engineering, many women working in these industries enjoy less career success. Their attrition rate far outweighs that of men. The problem seems to be the inflexibility of work and gendered behaviour.
“It is important to understand what happens in these professions and to consider how gendered behaviour and the inflexibility of work might be overcome.” (The Conversation)
Other studies highlight the difficulties facing brilliant women trying to forge a career. An example was given in 2005 “Andrea Hodge is a research scientist at Lawrence Livermore National Laboratory. Her research interests focuses on nanomechanics and the processing and characterization of nanocrystalline materials.
Despite her accomplishments, when a group of Japanese scientists visited to meet with her recently, they waited patiently for “Dr. Hodge” to arrive. The catch was, Hodge was already there. They had seen her, but assumed she was a secretary. “It had not occurred to them that it would be me,” Hodge said.” (TMS, 2005).
Another area of concern that is starting to be considered is the long term effects of gender bias when it comes to developing software and the increased use of Artificial Intelligence (AI) in Society.
“The proportion of women in computing occupations has been steadily declining from 36% in 1991 to 25% today” and “We found that gendered behavior is a significant source of disadvantage in open source software development: our models show negative coefficients for femaleness, and only weak support for categorical discrimination. Femaleness of behavior is not only a disadvantage for women: men and users with unidentifiable gender are just as disadvantaged along this dimension. “ (EPJ Data Science)
In AI “Interaction between humans and machines has opened up new opportunities for fighting bias in the workplace. Here’s how artificial intelligence can help companies reach gender parity.”
…or not. “If there is sexism embedded within the data, they will pick up that pattern and exhibit the same sexist behaviour in their output. And unfortunately, the workforce in AI is male dominant.”
(Dr. Muneera Bano) This is an interesting article and warning bells should ring as we recognise that sexism is embedded in the data that we are using to “teach” the computers that are using Artificial Intelligence and the old Sexism will continue into the future and become even more difficult to change given it would now be backed by powerful computer systems. It is not enough to teach our children that gender should not define us but we must also teach our machines the same lesson. (A conversation on Artificial Intelligence and Gender Bias)
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