Alexandra is Head of Product Policy & Partnerships at Google DeepMind. She is also a Technology & Human Rights Fellow at the Harvard Carr Center for Human Rights Policy.
I joined the MPA straight after my first degree in international affairs in France. I had spent my summers interning for the United Nations and the European Parliament and was hesitating between starting my career in the French civil service or taking advantage of a scholarship to study abroad. I knew I wanted to work in public policy but the MPA in Economic Policy felt like the opportunity to develop more solid quantitative skills, and I liked the fact that we could spend the second year in a partner university - I ended up graduating with a dual degree from the Lee Kuan Yew School of Public Policy in Singapore.
My mind was quite set on being a public servant at the start of the MPA, but throughout the programme, and as I met students with very different backgrounds, I came to realise the number of fascinating public policy roles that existed in the private sector. When I was in Singapore, I started working in Standard Chartered’s public sector group, and then became a foreign exchange economist, both roles requiring me to rely on my quantitative skills, but also my knowledge of how government works and how policy decisions are made.
The skills I acquired during the MPA were also not specific to a single sector. I ended up in public policy roles in energy, finance and then AI, with a focus that shifted between global, US, Asia, EU or just the UK. Sector-specific knowledge and contacts can always be developed in a new role, but what matters the most is to have solid foundations and an understanding of public policy - and it actually becomes an asset to be able to draw comparisons across sectors and regions.
So eventually, after the MPA, none of my roles were within government, but they were always about governments and public policy: from advising governments in Asia on their economic policies at Tony Blair Associates; to campaigning for more sustainable finance at Aviva; or in my current role at Google Deepmind where I think about what is the right, future-proof way of regulating AI.
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