I’m thrilled to announce that our principal, Jen Stirrup, is presenting at Women in Data Science in Zurich, Switzerland on 3rd April. At Data Relish, we are truly honoured because of the calibre of other speakers, such as the following leaders and role in Data Science.
Fernanda Viegas, Senior Staff Research Scientist at Google Brain
Valentina Boeva, Assistant Professor of Biomedical Informatics, ETH Zürich
Ines Montani, Founder at Explosion
Aleksandra Przegalinska, Associate Professor, Kozminski University
Susanna Tron, Analytics Knowledge Engineer, Swiss Re
Almerima J.-Kapic, Senior Data Scientist at Data, Analytics & AI, Swisscom
Why are events such as Women in Data Science important?
The tech industry is still overwhelmingly white and male, and while some attempts to increase diversity in the field has been effective, some has been misguided and largely unsuccessful. There are still a number of marginalised groups who are not receiving the representation they deserve in the field.
Diversity in tech is absolutely essential. Without a more diverse workforce, the industry is holding itself back from making real social and economic impact and progress. There are countless reasons why diversity in tech is so important, and here we will look at only a few comparably, but the need for more representation of marginalised groups in STEM fields extends beyond what we can list here.
One of the most important things to consider is that diversity in tech, while it has been getting more attention in recent years, is often misunderstood. It’s important that we strive for the right kind of diversity, rather than resorting to tokenism or becoming shortsighted when looking at groups who need more attention.
While more women are being accepted into tech workplaces now, with companies such as Netflix leading the way with a gender-balanced workforce, there are still improvements to be made — less than 10 percent of tech startups are women-owned, and women in tech earn on average almost 30% less than their male colleagues (1). However, these statistics do not account for the experiences of transgender women, who are not only underrepresented but often treated with outright contempt. A brief Google search for ‘trans women in tech’ told me everything I needed to know about how this group is treated in the industry. This goes to show that, while we may be filling certain gaps, we are still making crucial oversights, and neglecting entire oppressed groups who are in serious need of more representation. Those of us in STEM leadership positions should be striving to confront some of these cruel biases; while we can be thankful for and embrace the improvements that have come in recent years, there is still more work to be done.
Why we need more diversity in tech:
The STEM field is rapidly increasing. Jobs in STEM are estimated to increase by 17% by 2026 (2). The emerging workforce is full of talented, skilled people from minority groups. If these groups are neglected in the application and hiring process, the rapidly-growing industry will continue to be largely white and male, and will become more and more homogenous. This risks bringing up more barriers along the way, while losing out on potentially amazing new perspectives and talents.
Setting a good example. The tech industry receives a lot of attention worldwide. Tech affects all of our daily lives more and more every year, and so the people behind it are enjoying their time in the spotlight. There are many, many industries that lack diversity; InfoSec is around 80% male, the vast majority of professional psychologists and veterinarians are white, and lawyers are largely white and male, to name a few (3). Openly and loudly embracing diversity in tech could set a positive example for other industries that have gone down, or are at risk of going down, the same road.
Ignoring a wide talent pool. Oppressed groups have historically had their expression and creativity stifled, with fewer opportunities to pursue their goals and express their ideas. Many people in oppressed groups can face “stereotype threat”, where they feel they are at risk of conforming to negative stereotypes about their group. This can easily extend to the workplace — if a woman is told that jobs in tech are not for her, she may decide not to pursue what could be a lucrative and exciting career. Similarly, failing to see anyone like you in STEM leadership could lead to a lack of interest or motivation to get involved. If we continue to leave these groups out of the industry, some great ideas and exciting innovation could be continuously ignored, and people in minority groups could understandably become more discouraged to get involved in the first place.
Tech should reflect its audience. A homogenous workforce that is largely male and white doesn’t reflect the real world population that uses the tech being created. This results in shortsightedness when it comes to innovation. Recently, a government analysis of the most common facial recognition algorithms found a significant positive bias towards white subjects. If the technology that we are all using, whether we know it or not, isn’t programmed to treat individuals equally, that is a glaring sign that the development team behind that tech is in need of a wider range of people. More insight is essential in the creation of technology that is going to affect every group in society.
A diverse workforce makes employees happier. Studies have shown that a workforce that embraces diversity at every employment stage, as opposed to only tokenism in hiring practices, has increased employee engagement. Companies are more productive and have less absenteeism and much better employee retention. It makes perfect sense that people in the workforce who don’t represent the majority would be much more likely to stay with a company that shows they are committed to supporting them. It creates a sense of belonging and acceptance, and encourages a culture that embraces better collaboration and teamwork.
We hope to see you at Women in Data Science in Zurich on 3rd of April. Please sign up here for more information.