UTU will work with University of Southampton and UKRI to improve recommendation systems that help users retain control over their data privacy.
UTU is proud to congratulate Dr Sebastian Stein of the Agents, Interaction and Complexity (AIC) research group at the University of Southampton on his Turing Artificial Intelligence Acceleration Fellowship.
We are beyond excited to collaborate with him on the creation of AI systems that are aware of citizens’ preferences and act to maximise the benefit to society. In these systems, citizens are supported by trusted personal software agents that learn an individual’s preferences. Importantly, rather than share this data with a centralised system, the AI agents keep it safe on private smart devices and only use it in their owners’ interests.
Over the next five years, the £1.4m fellowship will develop and trial citizen-centric AI systems in a range of application areas. Named after AI pioneer Alan Turing, the Fellowships are supported by a £20 million government investment in AI being delivered by UK Research and Innovation (UKRI), in partnership with the UK Department for Business Energy and Industrial Strategy, Office for AI and the Alan Turing Institute.
UTU will collaborate with Dr. Stein across a number of areas with a primary focus on how citizens can share their preferences and recommendations with trusted peers while retaining control over what data is shared and with whom. About the collaboration with UTU, Dr. Stein said:
I am extremely excited to work with UTU on this fellowship. We share a common passion in building smart software that can offer personalised services and recommendations to individuals, while giving them the power to control their own data.
A key aspect of citizen-centric AI systems is that users are able to selectively share some of their data with trusted peers, and UTU’s experience in designing a social trust engine will be invaluable in achieving this.
It’s fantastic to have UTU’s support on this project and I look forward to work with them on transitioning fundamental research into real, practical applications. I’m particularly honoured to have a partner based in Kenya on this project. This will help ensure that the work has global impact and benefits users beyond the UK.
UTU believes deeply in Dr. Stein’s stance that “Novel approaches are needed to build AI systems that are trusted by citizens, that are inclusive and that achieve their goals effectively. To enable this, citizens must be viewed as first-class agents at the centre of AI systems, rather than as passive data sources.”
Dr. Bastian Blankenburg, UTU’s CTO, said:
“The AIC group has proven time and again to produce research of the highest quality, from which UTU already variously benefitted via our ongoing research partnership. We’re very excited to further deepen this in the scope of Dr. Stein’s new fellowship, which with regards to content couldn’t be a better match to what UTU endeavours to build.”
UTU’s CEO Jason Eisen added:
“Dr. Stein’s commitment to rebuilding the digital infrastructure of our lives is inspiring — this Turing Artificial Intelligence Acceleration Fellowship is well-earned and critical work towards Dr. Stein and UTU’s shared vision of benevolent, citizen-centric AI that learns the preferences, needs and constraints of individuals to provide personalised services, incentivise socially-beneficial behaviour changes, make choices that are fair, inclusive and equitable, and provide explanations for these decisions.”
Other industry partners in the fellowship with whom UTU is excited to collaborate include:
EA Technology and Energy Systems Catapult to generate incentive-aware smart charging mechanisms for electric vehicles.
Siemens Mobility, Thales and Connected Places Catapult to develop new approaches for trusted on-demand mobility.
Dstl to create disaster response applications that use crowdsourced intelligence from citizens to provide situational awareness, track the spread of infectious diseases or issue guidance to citizens.
IBM Research — the development and integration of explainability and fairness tools into open source frameworks.