In part three of our women in AI series, Professor Marta Kwiatkowska, a computer scientist at Oxford’s Department of Computer Science discusses her research specialism in developing modelling and analysis methods for complex systems. This work includes those arising in computational networks (which are applicable to autonomous technology), electronic devices and biological organisms.
Are there any AI research developments that excite you or that you are particularly interested in?
Robotics, including autonomous vehicles, and the potential of neural networks, such as autonomous vehicles, image and speech recognition technology. For example, developments like the Amazon Alexa-controlled Echo speaker have inspired me to work on techniques to support the design and specifically safety assurance and social trust of such systems.
What can be done to encourage more women in AI?
I think women should have the same opportunities as men and we should raise awareness of these opportunities, through networking, female role models and the media. AI is embedded in all aspects of our lives and we need all sections of society to contribute to the design and utilisation of AI systems in equal measure, and this includes women as well as men.
What research projects are you currently working on?
I am following several strands of work of relevance for autonomous systems, mobile devices and AI, including developing formal safety guarantees for software based on neural networks, such as those applied in autonomous vehicles. This involves formalising and evaluating the social trust between humans and robots. A social trust model is based on the human notion of trust, which is subjective. To make the model applicable to technology you have to develop 'correct by construction' techniques and tools for safe, efficient and predictable mobile autonomous robots. That means building personalised tools for monitoring and the regulation of affective behaviours through wearable devices.
In your opinion, what are the biggest challenges facing the field?
Technological developments present my field with tremendous opportunities, but the speed of progress creates challenges around formal verification and synthesis – particularly the complexity of the systems to be modelled. We therefore need to develop techniques that can be accurate at scale, deal with adaptive behaviour and produce effective results quickly.
What motivates you in your field?
I like working on mathematical foundations and gaining new insight from that, but my main motivation is to make the theoretical work applied through developing algorithms and software tools: I refer to this as a 'theory to practice' transfer of the techniques.
What research are you most proud of?
I was involved in the development of a software tool called PRISM, which is a probabilistic model checker. It is widely used for research and teaching and has been downloaded 65,000 times.
Who inspires you?
I have been inspired by several leading academics in my career, but one particular female scientist and my fellow countrywoman has been a role model and an inspiration for me throughout: Maria Sklodowska-Curie, because she combined a successful career with family.