My first year at the Alan Turing Institute




  • What scientific challenges does a particular theme present?
  • Do these challenges require new approaches in machine learning and statistical modelling?
  • What are the key research questions?
  • What is the state of the art?
  • What are the interdisciplinary challenges?
  • Who needs to be involved (skills, expertise, partners)?
  • What data is needed? Who are the data owners?
  • What resources are required?
  • What are the issues relating to privacy, security, and trust?


The year ahead

  • How do we better map and understand the AI skills and interests of our community?
  • How do we offer directionality in this space? How can we best pick up signals and emerging themes and provide our network with nurturing environments to thrive?
  • How can we achieve a more integrated portfolio of projects and increase the knowledge transfer inside our portfolio, but also across the Turing network and across the UK?
  • How do we close the loop between methodologically driven AI challenges and challenge-driven methodological work?
  • How can we have better public dialogue and public engagement regarding the development of AI systems?
  • What is the AI world we would like to see and how can we help shape this narrative?
  • How can we better define and capture the impacts of these sociotechnical systems in different sectors and applications?
  • How do we ensure diversity and equality of participation in the teams we create?




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Eirini Malliaraki

Eirini Malliaraki

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