Only 17% of data engineers are female

Today, I stumbled upon a statistic in a TechUK article that underscored a growing concern I've had about AI development and its inherent biases. The statistic revealed that a mere 17% of data engineers in the UK are women1. That's less than one in five!

We know that AI is fundamentally a reflection of the data it's trained on and the perspectives of those who develop it. With such a stark gender imbalance in the field of data engineering, we're exacerbating the risk of creating AI systems that predominantly reflect a masculine perspective.

So, what does this mean in practical terms? Well, we're already seeing AI systems inadvertently leaning towards male-centric viewpoints. This is not because AI has a gender preference, but because the diverse perspectives that women bring to the table are not sufficiently represented in its development process. This bias has manifested in various ways and will keep manifesting in many ways, from voice recognition systems that better understand male voices for example, or to a job recruitment AI tool that unconsciously favours male candidates. A case in point is Amazon, which in 2018 had to scrap a recruitment tool that discriminated against all female applicants2.

The lack of women in data engineering isn't just a matter of fairness. It's about creating AI systems that are balanced, unbiased, and truly representative of the diverse world we live in. The underrepresentation of women in data engineering has far-reaching implications for the development of AI. It's high time we address this imbalance and work towards creating a more inclusive and representative AI landscape.

Sources:

1- https://www.techuk.org/resource/why-is-there-a-gender-gap-in-tech-and-how-to-solve-it.html

2- https://www.reuters.com/article/us-amazon-com-jobs-automation-insight-idUSKCN1MK08G