by Charlotte Gurney
The number of women in STEM, AI and data science careers is woefully low and this is a problem, not just for those who are female and might be interested in a career in this field but for development in these areas, which benefit enormously from more female participation. There has been a big push to attract women into STEM, AI and data science, including from the World Economic Forum and big names such as IBM, IPsoft and Microsoft. But where has this inequality come from and what really needs to change to make the industry more inclusive?
Why are we here?
Currently women make up around 28% of the science and engineering workforce and women appear infrequently as AI professionals or authoring AI studies. One of the big issues in not correcting this is that a male dominated workforce means businesses aren’t optimising the technology they’re creating and using. Machine learning technologies are being loaded with a stream of gender biased data developed by male-heavy creators and developers, which will create junk results that don’t reflect the full picture. So, change is very necessary but what’s holding this back?
Many businesses in this area still don’t recognise the benefits of diverse teams. This is despite the fact that the World Economic Forum has said “Non-homogeneous teams are more capable than homogenous teams of recognising their biases and solving issues when interpreting data, testing solutions or making decisions.”
There are very few female role models in this area. Research has found that the presence of female STEM role models increased female interest in STEM careers by 20%.
Female scientists are often viewed as inferior. Toxic workplace cultures dominated by men perpetuate old-fashioned stereotypes that demote women, purely to advantage their male counterparts.
Women are looking for roles with meaning and purpose. However, many don’t perceive that a STEM career could offer this.
Communication with women about the roles available is poor. Women are not engaged with this area and only around half feel they know enough about the opportunities on offer.
What steps are being taken to change this?
IPSoft, IBM and the US Chamber of Commerce are some of the organisations that have launched campaigns to get more women into STEM and AI careers. AI itself could also have a big role to play in helping to rebalance the scales by removing bias in recruiting, evaluation, and promotion decisions. This could not only help to get more women into AI but also to ensure that they stay there. With more women in AI there would be more opportunity to eliminate the biased algorithms that result from a male dominated workforce and this too could help to close the gender gap. Reskilling/upskilling initiatives could make it much simpler and easier for more women to enter the world of STEM, AI and data science at a faster rate.
Currently, women are severely underrepresented in AI and this is having a damaging impact on the product of the industry. Increasing diversity not only benefits women but the effectiveness of AI technology overall.
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