In this contributed post, Christine Flounders, regional manager for engineering at Bloomberg L.P. London explains the importance of diversity in open source.
Tech’s gender gap is no secret. It has been widely discussed for a decade, yet little progress has been made. In the five years between 2010 and 2015, the percentage of women in tech jobs in the UK increased from 17% to just 18%. This figure is underwhelming to say the least, but there is one critical area of technology where the gender gap is even wider.
Data-driven algorithms govern many aspects of life: university admissions, resume screening, and a person’s ability to get a car or home loan. Often, using data leads to more efficient allocation of resources and better outcomes for everyone. But algorithms can come with unintended consequences—and without care, their application can result in a society we don’t want.
“Sometimes, you run into a road block and you’re stuck, but that’s what engineering is all about: finding a better solution.” — Amy Villasenor
A digital clock in my parents’ room was the first object that got me interested in technology. I was seven years old, and I’d stare at it and wonder, “How does that clock know that that number needs to change? How does it know that 60 seconds just passed?”
After three summers of Qcamp for Girls in STEM, I am excited to report that the seeds we planted two years ago and continued to nurture in order to positively impact the way girls learn science, technology, engineering and math (STEM) education and careers have bud