How did your journey in AI start - what brought you to AI?
I have always been attracted to the analytics space, and early in my career this brought me to a software company where I worked with what we then called “analytical intelligence” and what would probably have been called data science or AI today. Ever since, I have been working within the field of data, analytics and AI – first hands on and later in business and management roles.
What is the biggest change you have observed in AI compared to when you entered the field at the start of your career?
Definitely the number of organisations that develop and use AI, and the size of the AI community. When I started, mainly large finance and telco companies used data science/AI, and I knew a large proportion of the data science professionals in Norway. The increase in number of organisations that develop and use AI, the variety of application areas and the number of data and AI professionals has increased dramatically.
Another important change is the focus on digital ethics and responsible AI. I am almost getting ashamed when I think about the credit models I built 10-15 years ago. For instance fairness was never a topic we touched upon when building and applying the models – which we would definitely consider today.
What excites you about working in AI, and what are you working on right now?
You can combine analytical skills, creativity and business acumen, there is always new things to learn and there are endless opportunities no matter if you want to focus on a subfield of data science, if you want to work close to the business or if you want to take on management roles.
How do you see the number of female researchers and professionals in AI grow? How do you involve yourself in initiatives to introduce more women to AI, and what initiatives can we make to inspire more women to pursue careers within AI?
Unfortunately, the number of females within AI is still way too low. I participate in presentations at universities and I hope I can motivate more girls to enter the field of AI through showing how fun it is and showing that there are women in AI. However, I believe more should be done at an even earlier stage, to make more girls choose math, informatics and other scientific studies.
Why is it important for more women to get involved in AI?
I would point at two factors:
- When there are mainly men (or other categories of people, for that sake) within an AI, it suggests that we have not recruited from the whole population. It means there is a lot of great people that potentially could have been great contributors to the AI community
- Diversity among those who develop and apply AI increases the possibility that AI is used for the best for the society, and reduce the risk of unwanted discrimination.
What advice would you like to give women who are pursuing their careers in AI?
- Go for it!
- Make sure you don´t underestimate your own skills and potential.
- Embrace all opportunities to present yourself and your work, to grow your network, to apply for new positions and so on.
What advice do you have for organizations who wish to recruit and retain female researchers and professionals in AI?
Arrange visits to universities, be present at conferences – and make sure you have a healthy, inclusive working environment where a diversity of employees will thrive.
Who is your biggest role model within your field, and why?
I know many great data scientists and AI leaders, that are role models in various ways. However, to pick one that would be Inga Strümke. She shows such great enthusiasm and combine high professional skills with communication skills, and through her visibility in blog posts, podcasts ++ she manages to both show the possibilities in technology and AI, as well as put focus on the ethical aspects of AI.
What role can NORA take on to empower diversity and inclusion in AI in Norway?
Putting AI females in the spotlight like the “Women in data science” initiative is great.
And maybe they can collaborate with “lær kidsa koding” and/or create a similar organisation that introduce kids (including girls) to quantitative/AI-related topics early.
About Cathrine
NAV, or the Norwegian Labour and Welfare Administration, employs around 19,000 people to ensure that more people are active and in work. When one comes to understand that NAV administers a third of the national budget one can begin to understand the importance of management of technology in this context. Cathrine Pihl Lyngstad is heading the data section in NAV, where she works to deliver better services and more efficient use of taxpayer money through the use of data and machine learning. Lyngstad has extensive experience within digitalisation and is very concerned with responsible use of artificial intelligence. Especially during the lockdown in Norway to prevent COVID-19 Norwegians may have noticed to a smaller or larger extent how seamlessly the Norwegian welfare system works online. It is hard to imagine a more important contribution within the field of artificial intelligence at this time, for the benefit of the entire working population of Norway and those that urgently need welfare services.