U.K. PETs Prize Challenge

Privacy-enhancing technologies (PETs) have the potential to unlock more trustworthy innovation in data analysis and machine learning. Federated learning is one such technology that enables organisations to analyse sensitive data while providing improved privacy protections. These technologies could advance innovation and collaboration in new fields and help harness the power of data to tackle some of our most pressing societal challenges.

That’s why the U.S. and U.K. governments are partnering to deliver a set of prize challenges to unleash the potential of these democracy-affirming technologies to make a positive impact. In particular, this challenge will tackle two critical problems via separate data tracks: Data Track A will help with the identification of financial crime, while Data Track B will bolster pandemic responses.

By entering the prize challenges, innovators will have the opportunity to compete for cash prizes and engage with regulators and government agencies. Announced at the Summit for Democracy in December 2021, the prize challenges are a product of a collaboration between multiple government departments and agencies on both sides of the Atlantic. Winning solutions will have the opportunity to be profiled at the second Summit for Democracy, to be convened by President Joe Biden, in early 2023.

You are on the home page for the U.K. side of the challenge. You can find the U.S. challenge here.

Results

The challenge is over. Congratulations to the winners!

Phase 2 (Blue Teams)

• Joint 1st place: University of Cambridge | STARLIT (Privitar, UCL, Cardiff Univ.)
• 3rd place: Faculty
• 4th place: Featurespace
• Special Recognition:
  • Usability prizes: Featurespace | Faculty
  • Novel modelling/design prizes: STARLIT | University of Liverpool
  • Regulatory distinction prize: Diagonal

Phase 3 (Red Teams)

• 1st place: Trūata

You can read more about the results of the challenge and meet the winning teams in this blog post by Innovate UK.

The synthetic pandemic outbreaks dataset from Track B of the challenge has also been made available for ongoing learning and development. See the dataset website for more information.