Associate Professor, UiB
How did your journey in AI start - what brought you to AI?
I started studying description logic ontologies during my master studies. Then, during my PhD studies, I got interested in the papers by Prof. Dana Angluin about the exact learning model. Since then, a lot of my research has focus on learning ontologies.
What is the biggest change you have observed in AI compared to when you entered the field at the start of your career?
AI became a widespread term used by the general public (and sometimes feared). This was not the case 10 years ago.
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?
I am currently not involved in any specific initiative to introduce more women to AI. I think that the biggest challenge is not to inspire more women to pursue careers within AI but to keep them in the exact sciences long enough so that they can start a career within AI. Then, once they start, support them so that they can continue.
Why is it important for more women to get involved in AI?
That is to increase diversity, which helps on finding solutions for this challenging field.
What advice would you like to give women who are pursuing their careers in AI?
Go ahead with confidence! If something turns against your progress, then be patient and seek advice from more senior female colleagues.
What advice do you have for organizations who wish to recruit and retain female researchers and professionals in AI?
Listen to them!
Who is your biggest role model within your field, and why?
Prof. Dana Angluin is my biggest role model. She recently retired but she worked as a full professor in machine learning at Yale. She created the exact learning model, in which a learner attempts to learn a concept from a teacher via queries. Recently this model has been applied to extract explanatory information from black-box machine learning models.
What role can NORA take on to empower diversity and inclusion in AI in Norway?
That is a difficult question. The current initiative of asking women in the field to answer this interview is already an excellent way of obtaining some input and insight on how to answer this question. Then, perhaps striving to keep diversity and inclusion in all activities is a good way to empower different kinds of researchers.
Ana Ozaki was mentioned many times when we asked our network for people that deserve to be on this list. Ozaki is an Associate Professor at the University of Bergen. Her focus within artificial intelligence is learning theory, knowledge representation and reasoning. How does reasoning processes and learning interact? This is one of the questions Ozaki is concerned with. She is a member of the editorial boards of the Journal of Machine Learning Research and the Journal of Web Semantics. She has also recently worked as Program Committee Chair for the 27th International Symposium on Temporal Representation and Reasoning. The current work of Ozaki is with strategies to learn Horn rules from neural networks by posing them queries. She firmly believes recent advances need to be accompanied by theoretical development so systems can provide formal guarantees that contribute to more trustworthy systems.