Shakir Mohamed
GenAI and The End of Science? Sociotechnical AI Foundations for Scientific Advancement
One narratives enshrouding GenAI says that AI will either be the end of everything, or will be the rescuer of everything. The Sciences are one such area, confronted with that dichotomy: will AI end the age of scientific advancement as we know it and automate the scientists; or will it enable scientists to unlock a new golden age of scientific successes; or perhaps something in between. I want to use this divergence in views of the future to consider the larger sociotechnical ecosystem in AI for Science, looking at advancement in both the natural and human sciences. I’ll use progress in weather and climate, and learning and education, as concrete areas where there is significant activity, and give an update on our technical progress. Ultimately, I want to provoke our thinking on future progress in the sciences, and on our responsibilities as innovators in AI.will showcase the value of a systems approach to AI Security. Unlike current methods that focus on protecting machine learning models in isolation, the systems approach examines end-to-end properties and focuses on threats and defenses from that perspective. This approach secures real world computer systems from powerful adversaries and my thesis is that its principles can be adapted to protect AI systems. As evidence, I will discuss my group's work in discovering realistic threats on modern AI systems. I will also discuss work on improving the infrastructure supporting AI systems with a particular focus on authorization protocols that allow AI systems to access external resources.
Bio:
Shakir Mohamed works on technical and sociotechnical questions in AI research and development, working on problems in foundational AI, applied problems in healthcare, education and environment, and participation and responsibility. Shakir is a Research Director at Google DeepMind in London, an Associate Fellow at the Leverhulme Centre for the Future of Intelligence, and a Honorary Professor of University College London. Shakir is a founder and trustee of the Deep Learning Indaba, a grassroots charity whose work is to build pan-African capacity and leadership in AI. In 2023, Shakir was included in the TIME 100 most influential people in AI. He serves on several boards, including the oversight board of the Ada Lovelace Institute, as the Chair of the international scientific advisory committee for the pan-Canadian AI strategy, the Royal Society Diversity and Inclusion committee, and the AI field’s leading conferences (ICLR, ICML, NeurIPS). Shakir is from South Africa, he completed a postdoc at the University of British Columbia, received his PhD from St John's College in the University of Cambridge, and received his masters and undergraduate degrees in Electrical and Information engineering from the University of the Witwatersrand, Johannesburg.