Natalie Torbett

30 October 2020

10 min read


How is AI changing the world?

By Ryan Lawler

3 min read

The tech space is notoriously challenging for women to break into. In fact, as of 2019 only 20 percent of all jobs in technology were held by women around the world. While there has been some progress in closing the gender gap, it is simply not happening fast enough.

In Germany, the proportion of women in tech jobs between 2012 and 2018 increased by a mere two percent and women in machine and vehicle technology even fell by about one percent. Clearly as an industry, we still have work to do.

Despite the fairly slow progress, several women in Europe are leading the charge by founding their own companies, serving as Chief Technology Officer, and showing other young women interested in tech that there is a space for them.

We spoke with three Berlin-based leaders in this field -- Maria Meier, Naja von Schmude, and Micol de Ruvo -- who are on the cutting edge of their industries. They are also experts in the challenge of excelling in an industry that has historically been unwelcoming to women. They see tech as a reflection of society’s development, so it makes sense that innovation in this space requires both doing the work and being seen doing it.

In our conversations with Maria, Naja, and Micol, we discussed the societal challenges they are tackling in their work, how they are diversifying their talent pipeline, and how to improve inclusivity in the tech space overall.

Maria Meier
Maria Meier is the founder and CTO of Phantasma Labs, which seeks to make human behavior understandable for any AI algorithm that will guide an autonomous car, which can improve the quality and safety of the experience. Maria has a Bachelors of Science in Information Systems and a Masters in Software Engineering.
What’s the problem you’re trying to solve?

If you want to have a self-driving car in Berlin, or in a city in India with many more people, you will need to understand how we can train cars to be safe enough to interact with human beings.

Human beings are very unpredictable, especially the way we interact in big urban cities, as opposed to what you might see in the press where people have already deployed a self-driving car on a highway or in an American suburb.

What’s your solution?

Phantasma Labs helps self-driving cars understand humans better. So we make human and especially pedestrian behavior understandable for any AI algorithm that is going to be inside a self-driving car.

Currently, companies are using real fleets of cars to collect data about scenarios that can occur in traffic between cars and vulnerable road users, such as pedestrians or cyclists. Many of these scenarios are very rare and so statistically speaking one would need to drive millions of kilometers to encounter them. This is why they are called edge cases. Other edge cases aren’t possible to be collected from the real world, as it would be unethical to record them (such as a child running in front of a car).

This is what we specialize in at Phantasma Labs. We are enabling companies to train their algorithms for these rare and dangerous scenarios in city environments through simulations.

How are you working to diversify the hiring pipeline?

One basic thing is to post your job on different platforms like Women Who Code and Elpha. Also, Unicorns In Tech focuses on [recruiting diversity in] sexual orientation.

I think you have to really make an effort to reach out to underrepresented people. I would also like to give a shout-out to organizations working on including BIPoC in tech, such as Talent Diverse. Also Frauenloop who are training women for engineering and data science jobs.

When I applied for jobs in the past I always looked at the website, I checked out the team of the company, I read the job description, and I was filtering for, “How friendly is this environment going to be?” I was usually the only woman on the team so I wanted to make sure that I was working in a welcoming and supportive environment.

Also, yesterday someone told me that for every CV you read from a white man, you should make a point of how many CVs from an underrepresented group you should be reading. I think this could be another way of ensuring that you're diversifying your pipeline as well.

How can the tech space become more inclusive to women?

In Germany only 20 percent of women work full-time in our country. 20 percent. It's very, very low. I think you can see that the norms are not as progressive as we want them to be yet. We have a lot of work to do in making the workplace more inclusive and I think there are two ways to do this.

One way is to make computer science a science subject on the same level as physics, so you can make the subject accessible to anyone who goes to a public school. A second thing is to make the working environment for women who are already in professional areas so good and inclusive that they don't leave -- because there's a problem that no one talks about.

A lot of women actually leave the tech field because it can be unwelcoming, because traditionally women do more care work and it can be not inclusive for women who have a full-time job. Those are the two fields where I think we should be working on.

Naja von Schmude
Naja von Schmude is the founder and CTO of Peregrine Technologies, which provides actionable information for commercial fleet operations and mobility services through AI-powered video analytics. Naja has a PhD in Computer Science.
What’s the problem you’re trying to solve?

All the [autonomous] cars out there and also the cars in the next years to come, don't necessarily have the capabilities for getting insights generated from the image content around them to fuel their development.

What’s your solution?

We see ourselves as a data and technology provider and we empower teams to build a safer and more sustainable mobility ecosystem by putting dashcams running our software in commercial vehicles.

The software is analyzing and interpreting all the images in real time. We get an awareness of the whole situation, meaning, “What traffic participants are there, where do they come from, where do they go? How fast are they?”

In general, it's a better assessment of the whole situation and its risk. This data helps a fleet manager to better support and teach the drivers. In case of an accident the fleet manager also has proof of what was going on. In the end he can then prevent accidents and save costs.

It is very important to highlight that all our models and our algorithms are constantly learning and becoming better and better with each drive. That of course has a very, very broad range of applications also besides fleet customers. For example, we also work with insurance, but you can also think of autonomous driving, which needs a lot of data to improve their development and all their processes as well.

How are you working to diversify the hiring pipeline?

There are not many women at the moment in Engineering or Computer Science. That's why, for example, if I look at resumes and I see it is a woman applying, then I really take extra care to read through it and to make sure that I don't miss something.

And in addition, women want to check all the requirements which are listed in a job description, so we emphasize that actually you can also apply if you don't check everything.

How can the tech space become more inclusive to women?

I think that is very deeply rooted in our society or the gender stereotypes. We need more opportunities for younger girls and younger boys to show them they can really do what they want and what they find interesting and whether they are good at. We need more lighthouse figures or role models.

That's also why I’m doing this interview today - to show there are people like myself or others out there who actually work in tech. It's cool, and it's fun, and you can do that.

Micol de Ruvo
Micol de Ruvo is the founder and CTO of CogniScent, a company that uses machine learning and in-depth medical knowledge to support early diagnosis and management of neurodegenerative diseases like Parkinson’s and Alzheimer’s. Micol has a Masters in Biomedical Engineering, a PhD in Computational Biology, and years of experience in developing algorithms for digital health applications.
What’s the problem you’re trying to solve?

The misdiagnosis rate of both Parkinson’s and Alzheimer’s is really high, especially in the early stage of the disease. And that's because many of the early symptoms are unspecific or overlap with other conditions.

In Parkinson’s, an accurate diagnosis only occurs when the late-stage symptoms appear, like tremors, but by then it's too late to focus on targeted interventions and the quality of life has a really big negative impact.

What’s your solution?

At CogniScent, we combine medical knowledge with machine learning to deliver at-home testing that supports a timely diagnosis and self-management of neurodegenerative diseases like Parkinson's or Alzheimer's.

Let’s assume a 60-year-old person is worried about developing Parkinson's and they read in the media that, for instance, smell impairments or poor sleep can lead to Parkinson's. They simply order our test online, they will get sent a smell test at home to check for smell impairments, and they will answer a series of straightforward but clinically-validated questionnaires.

In about 25 minutes they will get results on whether their unique combination of symptoms is likely to be related to Parkinson’s or not. This results in a flagging mechanism that supports physicians in reaching an accurate diagnosis sooner.

In our solution, AI plays a crucial role in giving patients a clear picture of their early symptoms. They can check which kind of symptoms are more crucial or at risk or not, they can monitor their symptoms so they will get offered tailored recommendations and self-management interventions. And that's thanks to the power of AI in learning from past data.

On the other hand physicians, especially at the primary care level, will have access to information that otherwise would be only accessible for researchers and specialists. In that way, they can make an informed decision on the next steps but also focus only on the patients at risk.

How are you working to diversify the hiring pipeline?

We really try and start from the beginning of the process, which is the job description. I realize that it's such an important way of attracting talents. There are some words you can use, like “supportive” or “inclusive,” that immediately signal how much we care about building a diverse team.

It sounds obvious, but I believe it is a clear statement for our company culture. Furthermore, we are an international company, we speak English at work, and we believe we highly benefit from merging different cultures.

As for gender diversity, I believe in having women on the interview panel is also of great importance And, of course, also joining women in tech circles or meetings - opportunities where you can start building your network. I for myself joined some groups in healthcare for women in tech and I think that can help.

How can we encourage more women to found engineering-centric and deep-tech startups?

In my opinion, it's about confidence, awareness, and role models. When it comes to the first two aspects, I think we're still experiencing a long-term effect from a past where women were not joining risky businesses and they were more focused on family responsibilities.

This is slowly changing now, but I feel we're still missing networking and awareness on how other women founders are doing that, and also highlighting the benefits of founding a company.

As for the role models, I would like to share my experience as I think it brings a positive message. In academia, actually, it's not rare to see women in engineering, tech, or IT. When I was a biomedical engineering student and researcher, I had two advisors who were both women professors. They were strong, passionate, and inspiring. And over time they became a reference for my career decisions.

I think that's really helped me not being scared of building my own team and co-founding a tech company.

Maria Meier, Naja Von Schmude, and Dr. Micol de Ruvo’s companies each reflect tech’s shifting focus to creating real life solutions. Their bold work is breaking new ground in autonomous driving and in neurodegenerative disease treatments, thereby improving the lives of thousands of people. Their positive impact does not stop there, though. Their presence as leaders in their organizations provides young women and girls with the exact kind of role models to whom they ascribe their success. They challenge the tech industry, one committed to constantly driving positive change, to consider more diverse candidates and bolder ideas to make the world a safer, smarter, and healthier place.