RUSI partners with the Centre for Data Ethics and Innovation


RUSI is delighted to announce our new partnership with the Centre for Data Ethics and Innovation, a recently-launched Government advisory body, established to investigate and advise on how Government can maximise the benefits of data-enabled technologies and artificial intelligence (AI).

The Centre is currently undertaking a review into bias in algorithmic decision-making in the Crime and Justice sector. As part of this review, the Centre is developing a code of practice for the design, development and trialling of predictive policing technology, which will help mitigate algorithmic bias and address wider ethical concerns. The Centre has commissioned RUSI to undertake an independent research study into how algorithmic tools are currently being used by police forces in England and Wales, along with the potential for biased outcomes for certain individuals or groups. The research will consist of interviews and roundtables with local police forces, technology providers, civil liberties groups and others.

 

The Centre and RUSI are focusing on predictive policing as previous RUSI research has identified significant gaps in the existing policy framework for the police‚Äôs use of machine learning, and there is currently no national guidance for how these tools should be developed. Moreover, there is evidence that technology of this kind can be subject to bias, if not carefully designed and implemented. A new code of practice will provide clear guidance on how police forces should trial and implement predictive algorithmic tools while addressing issues of algorithmic bias and wider ethical concerns.

 

An interim Briefing Paper will be published in autumn 2019 summarising the emerging findings of the research, alongside a draft code of practice which will be circulated for consultation. The final RUSI research paper will be published early 2020.

 

For more information please contact Alexander Babuta, AlexanderB@rusi.org


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Alexander Babuta

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Dr Marion Oswald

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