U.K.-U.S. prize challenges
Accelerating the adoption and development of privacy-enhancing technologies (PETs)
Transforming financial crime prevention and boosting pandemic response capabilities through privacy-preserving federated learning
Click here to see the Phase 1 winners.
Red team registration is now closed.
Innovating to tackle global challenges
Privacy-enhancing technologies (PETs) have the potential to help us devise data-driven, innovative solutions to tackle the most pressing global societal challenges we're facing, while preserving citizens’ fundamental right to privacy, which constitutes a foundation for democratic societies.
By enabling organisations to share and collaboratively analyse sensitive data in a privacy-preserving manner, PETs open up unprecedented opportunities to harness the power of data through innovative and trustworthy applications.
That’s why the U.K. and U.S. governments are delivering a set of prize challenges - announced at the Summit for Democracy in December 2021 - to unleash the potential of these democracy-affirming technologies.
Innovators will compete for the chance to:
Win cash prizes from a total prize pool of approximately £1.3m / $1.6m
Engage with regulators, government agencies and global companies
Have their solutions profiled at the second Summit for Democracy, to be convened by President Joe Biden, in the first half of 2023.
The goals of the challenges
Drive innovation in the technological development and application of novel PETs
Deliver strong end-to-end privacy guarantees against a set of common threats and privacy attacks, leveraging a combination of input and output privacy techniques
Develop a privacy-preserving solution that is capable of efficiently generating high-utility machine learning models for one of two predefined use-cases in finance and public health, detailed below
Phase 1 winners
The winners of the first phase of the prize challenges are listed below:
- Corvus Research Limited
- DeepMind and OpenMined**
- Diagonal Works
- Featurespace Limited
- Privitar Limited
- Team IBM Research
- Team MusCAT: researchers from the Broad Institute, MIT, Harvard Business School, UT Austin, University of Toronto
- Team Secret Computers: researchers from Inpher, Inc.
- University of Cambridge
- University of Liverpool
**DeepMind and OpenMined have chosen not to accept any prize funds for this challenge.
Find profiles of the winners from the U.S. challenge here
In phase 2, teams from both sides of the Atlantic will go on to develop their prototypes.
Structure of the prize challenges
The challenges, which are free to enter, are taking the form of a multi-stage competition involving a white paper submission, prototype development, and a red-teaming phase.
Participants can select one track or both tracks, or for extra points, develop a solution that works for both.
Transforming financial crime prevention
Innovators will develop solutions that help tackle the challenge of international money laundering, which finances organized crime including human trafficking and terrorist financing, and undermines economic prosperity – costing up to US$2 trillion each year, according to UN estimates.
This illicit activity could be more effectively identified through information sharing and collaborative analytics among financial organisations, but such approaches are made more challenging by legal and technical requirements to ensure customer privacy. Organisations including the Financial Action Task Force have highlighted the potential of PETs to help tackle these barriers by enabling privacy-preserving access to data.
Innovators will develop end-to-end privacy-preserving federated learning solutions to detect potentially anomalous payments, leveraging a combination of input and output privacy techniques. To develop solutions, innovators will use synthetic datasets created by SWIFT, the global provider of secure financial messaging services.
While developing the solutions, innovators in the U.K. will be able to engage with the Information Commissioner’s Office (ICO), the U.K. National Economic Crime Centre, and the Financial Conduct Authority (FCA), and innovators in the U.S. will be able to engage with the Financial Crimes Enforcement Network (FinCEN).
Forecasting to bolster pandemic response capabilities
Innovators will bolster pandemic response capabilities in both the United States and United Kingdom by developing privacy-preserving federated learning solutions to improve forecasting. The COVID-19 pandemic - which has incurred an immense human cost and socio-economic impact across the globe - has demonstrated the importance of preparing for public health emergencies by harnessing the power of data through privacy-preserving data sharing and analytics.
Innovators will develop privacy-preserving federated learning solutions to forecast an individual’s risk of infection, leveraging a combination of input and output privacy techniques. Participants will have access to a synthetic dataset created by the University of Virginia’s Biocomplexity Institute, which represents a digital twin of a population with statistical and dynamical properties similar to a real population.
While developing the solutions, innovators in the U.K. will be able to engage with the Information Commissioner’s Office (ICO), NHS England, and the UKRI-funded Data and Analytics Research Environments UK (DARE UK), and innovators in the U.S. will be able to engage with staff from the Centers for Disease Control and Prevention (CDC).