10.Nov 2021

Artificial Intelligence: Women wanted

Machines are able to do almost everything for mankind, perfectionizing almost every process beyond our possibilities. The value global market of artificial intelligence in 2020 rose over $62B in 2020. And will keep rising with speed. Today we get closer and closer to teaching technology even the most complicated human abilities: learning, reasoning, planning, interpreting language and solving problems. But as we continue on creating artificial intelligence, we overlook the danger of having it suffering from a birth defect. But there are initiatives to change this. Like the Female Data Science Network by Siemens. Dr. Ulrike Dowie and Dr. Sylvia Endres tell us about their view on diversity in AI and their Women AI Hackathon.

Artificial Intelligence and Diversity

We need to keep one thing in mind: Artificial Intelligence is currently learning from those who teach. And these teachers are mostly male. Only 22% of people working in the AI sector are women as declared by a report of the Alan Turing Institute. Why is this a problem? Because the system created will be biased by those whose data it relies on. That makes it not only biased in its decisions but also passes these biased views onto those it interacts with. Of course the need for diversity in artificial intelligence does not only apply to sex but every other aspect e.g. race.

Not Enough Women

To address this problem, companies started various campaigns and initiatives to encourage women to work in this business field. At Siemens Dr. Ulrike Dowie and Dr. Sylvia Endres founded the Female Data Science Network. They believe in the success of diverse teams of data-driven minds. Together with our team from German Entrepreneurship, they set up a virtual hackathon for women from all over the world.

Why do you think there are so few women in data science and in the AI field?

There are more talented women in Data Science and AI out there than one might think. For the WomenHackAI, we received more than 100 applications within a very short amount of time. Internally at Siemens, there are already more than 50 women part of the Female Data Science Network, which we founded less than one year ago. But like other MINT courses, studying computer sciences and statistics (the typical areas for future Data Scientists) have not been attracting as many women as men. Thus, we need to make them more attractive. We need to inform about future job possibilities, present role models and convince girls to pursue studies in this area. This is one of the main goals of the Female Data Science Network.

Why do we need more female data scientists?

Diverse Teams make all the difference: Not only in data science projects, but in general, diverse teams in all dimensions are reportedly more innovative and better at problem-solving thanks to their variety of views, backgrounds and characteristics.

What advice can you give women who are interested in Artificial Intelligence?

Get a basic or more advanced understanding of statistics. Read “Invisible women – exposing data bias in a world designed for men” by Caroline Criado Perez. And check out online courses (e.g., Coursera or Udemy) or any online class by Andrew Ng. Further, get in touch with other data scientists that are already where you would like to be, for example via communities and meetups.

What was your experience during the AI Hackathon and would you do it again?

We were impressed by the amazing spirit and the bright ladies, lots and lots of energy, enthusiasm, and FUN. So we will definitely do this again!

What is your hope Artificial Intelligence will be able to do for us someday?

Beam us to any remote location without any emissions and instantaneously. Reduce climate change and give us global peace. 

Is your creatitvity challanged in a hackathon or in any other test? We present seven creativity techniques to push your brain for more creativity.

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