Dr. Sasha Rubel:

On our approach to responsible AI, we very much have a four-pronged approach noting that we have a responsible and acceptable use policy. Our understanding is that there needs to be a life-cycle approach because responsibility should be the responsibility of everybody. These four-pronged approaches are very much dedicated to, first of all, transforming responsible AI from theory to practice. If one talks about, for example, our principles such as transparency, veracity and robustness, there is general consensus that these are important principles but what does that mean to an engineer? We have placed a great deal of focus on translating these principles into operational guidelines for engineers, not only inside our company, but also for our customers, so that they can translate those into practice in the design, development and deployment of their solutions.

The second aspect is integrating responsibility into the entirety of the life-cycle, as I mentioned. Third, it is about nurturing education and diverse teams. We see diversity as a key lever to responsibility, so we have a real emphasis on ensuring that teams are diverse, not only in background, but also in training, so that we get the best AI solution possible. We are convinced that the AI solutions which are being developed, and that those who are developing them, need to be as diverse as the communities and end-users that this solution is intended to help.

Further, we are very much focused on advancing the science behind responsible AI. Generative AI raises many new questions around intellectual property and copyright, fidelity and hallucinations, data protection and privacy. One of our commitments is very much about working with academics, civil society and policymakers to think through these questions.

Lastly, and very quickly on the Deputy's question on education, we see generative AI as completely transforming the education sector through multiple levels and the first is improving student outcomes.

In a lot of countries, teachers are completely overwhelmed and overworked. We see generative AI as an opportunity to help teachers make sure they are delivering the best possible student outcomes. On helping to increase online learning reach, I was home-schooled when I was young. If I had generative AI, my learning outcomes, path and trajectory would have been extremely different because it would have allowed me to access the information I needed in real time in order to progress.

On accelerating research and discovery in research institutions, we see amazing breakthroughs in generative AI that can digest an enormous amount of data that would have taken six months to garner insights and wisdom from in six minutes. We really see this technology transforming the scale of research, including in areas like clinical trials and medicine.

We see this happening across the board, from primary education to higher education. Part of our commitment in responsible AI is the necessity to have a human in the loop. We see AI complementing teachers rather than replacing them. That is part of our commitment as regards human oversight and responsibility.