Gender diversity crucial to artificial intelligence sector

SERIES (4): "Female AI – four questions to women in AI." Interviewee: Dr.-Ing. Susan Wegner VP AI & Data Analytics at Lufthansa Industry Solutions
26 October 2021
Diversity in der KI

The Hamburg-based AI company Synergeticon, the ARIC Hamburg association and the proTechnicale initiative are raising the visibility of AI and promoting women in the sector, which holds all kinds of exciting career opportunities. Hamburg News’ interview series "Female AI - four questions to Women in AI" features women who have already gained a foothold in the industry. 

Our latest interviewee, Dr.-Ing. Susan Wegner, is responsible for the "Artificial Intelligence & Data Analytics" business unit at Lufthansa Industry Solutions in the Hamburg Metropolitan Region. Wegner has over 15 years of experience in machine learning, AI and platform/software design, and previously worked for Deutsche Telekon and Bosch, among others. A computer scientist and mathematician by profession, AI quickly became her focal point. Wegner also volunteers as an ambassador for proTechnicale, the technical orientation and qualification year for young women.

Hamburg News: What do you do in the AI industry, and why is that important?

Dr.-Ing. Susan Wegner: My job is to make AI tangible and usable for everyone. AI systems already help and relieve people with everyday tasks and that allows us to use our valuable time more efficiently. I explore use cases where AI can help us with tasks and actions thereby making our routines and lives more efficient and effective. Humanity can evolve significantly with the support of AI, not only in terms of positive financial impact for businesses, but also as a community and society.

Hamburg News: How did you get involved with AI?

Wegner: I studied computer science and mathematics and took some AI-related courses at university. After my Master's degree, I started working on a research project at the German Heart Centre on the campus of the University Hospital in Berlin. One of the main topics was precisely locating tumors in MRI and CT images. Given my background in mathematics, that was both fascinating and highly challenging, so I started looking into image segmentation or AI. However, it was not as applicable as it is today, meaning that segmenting a 10x10 image took the neural network a full night before we had the results in the morning.

Susan Wegner
© Susan Wegner
Dr.-Ing. Susan Wegner

Hamburg News: What are your plans for the future?

Wegner: I'm currently pursuing two major strategies. The first is to make AI solutions easy and quick for everyone to use, for instance, by offering AI as a service. Until now, the development of AI has tended to focus on custom programming, for which AI experts frequently had to be found and trained first. That made projects lengthy and expensive. On top of that, only large and financially buoyant companies were able to handle such projects. Thanks to cloud services, AI has come within the reach of mid-sized companies. AI as a service lowers the barriers because the provider has already solved many sub-problems. Companies can benefit from AI far faster as a result.

My second strategy is to make the Artificial Intelligence & Data Analytics business unit at Lufthansa Industry Solutions "a well-known and recognized large AI team in Germany. We already have a very skilled and experienced team with a long history of bringing AI cases to production and generating business impact. We are now growing this team and aim to more than double in size in next year.

Hamburg News: Why should there be more women in AI?

Wegner: AI is trained by humans or data, so we bring our personal perspective to the training. If you think about a tennis or soccer coach, for instance, the personal touch alway rubs off on the players, whether it's the spin or the rituals before a match. For that reason, players are advised to change their coaches every now and then. Not because the coaches do a bad job, but simply to gain a new perspective. The game would not evolve significantly, if there were only one type of coach for players all over the world. Players who not fit in would be rejected. When those criteria are applied to AI, that means the technology must cover every possible perspective to progress everywhere.

AI should not be discriminatory. Thus, gender diversity in AI is crucial to its success. I believe that for AI to unfold its promise as a solution, more women are needed to bring diversity to the existing sphere of AI creators and trainers and to remove prejudice. If diversity in AI is neglected, we run the risk of potentiating the gender gap we have been fighting for so long and continuing to neglect minorities, who are the only ones challenging the status quo. 
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