Data Science and AI

The Data Science and Artificial Intelligence (AI) Section is a section of the Royal Statistical Society that was established in 2017. The section includes representatives from business, industry, government and academia and was formed to address the emerging opportunities and challenges that arise around data science and artificial intelligence. This will ultimately impact the long term success of these important areas, from a range of perspectives including societal, professional, ethical and policy.

Note: The Data Science and AI Section scope is complementary to that of the Computational Statistics & Machine Learning Section, in that the latter focuses primarily on the methodological / mathematical aspects of machine learning, while the Data Science and AI Section will focus on the application and implementation aspects.

Learn more about the Section at datasciencesection.org

 
 

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Remit

The remit of the section is to represent the data science community in the UK and overseas, as well as help develop the role of the RSS as a professional body to support data scientists and promote good practice within data science. The section will organise meetings for a broad range of attendees, and provide advice that is aimed at:

  • Promoting good practice and clarifying the required skillset for professional data scientists and AI practitioners and leaders
  • Promoting the statistical aspects of data science and AI
  • Supporting the pipeline and career development of data scientists and statisticians
  • Pushing forward the debate around opportunities and challenges posed by data science, artificial intelligence and machine learning.
  • The societal, ethical and policy implications of data science & AI, including input to policy decisions concerning the data science profession
     

Upcoming meetings and events...

Scaling AI in public services followed by Christmas drinks
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Additional Information

If you want to learn more about our activities, please contact us.

A Guide for Ethical Data Science, co-authored with the Institute and Faculty of Actuaries (with accompanying Additional information).

The DSS has contributed to Parliamentary Office of Science and Technology POSTnote briefings on interpretable machine learning (October 2020) and AI and healthcare (January 2021)