Twelve groups won in the initial phase of the U.K-U.S. privacy-enhancing technologies prize challenges for proposing platforms that can either improve financial crime detection or predict infection risk levels in people in the event of a pandemic.
The National Institute of Standards and Technology, one of the administrators of the PET prize challenge, said Thursday that the competition’s goal is to encourage the creation of artificial intelligence technologies that can manage sensitive data without violating privacy laws.
Aside from NIST, the challenges were prepared by the U.K. Centre for Data Ethics and Innovation, Innovate UK, the U.S. White House Office of Science and Technology Policy, and the U.S. National Science Foundation.
The agencies reviewed 76 technical paper submissions vying for the $1.6 million prize pool. The chosen entries received a combined total of $157,000 for Phase 1 of the competition.
For the U.S. challenge, one of the winning teams comprised of researchers from the Massachusetts Institute of Technology, Broad Institute of MIT and Harvard, Harvard Business School, the University of Texas Austin, and the University of Toronto. Two other prizes went to representatives of IBM Research and machine learning software developer Inpher.
The winning organizations in the U.K. are:
- Corvus Research Limited
- Diagonal Works
- GMV
- Faculty
- Featurespace Limited
- OpenMined and DeepMind
- Privitar Limited
- University of Cambridge
- University of Liverpool
“AI is driving rapid technology change that is based on ever-increasing amounts of disparate data, making privacy-enhancing technologies increasingly important,” said Laurie Locascio, under secretary of Commerce for standards and technology and director of NIST. “The U.S.-U.K. PET prize challenge provides a global venue to build and showcase cutting-edge and scalable solutions that respect human rights and civil liberties,” she commented.
