British Police to Use Twitter to Predict Hate Crimes
British police will start using an AI developed by Cardiff University that will predict hate crimes based on comments made on Twitter.
Any comments made on Twitter that are deemed “hateful” will have their location tracked by the AI, and will then hand predictions of where hate crimes may appear to British police. The technology was developed by Professor Matthew Williams at Cardiff University; it first collected data from Twitter between August 2013 and 2014, and claimed it could prove a link between hateful tweets and actual crime existed.
The trial of the system will start on October 31st this year, and will be attached to the National Police Chief Council’s (NPCC) online hate crime hub. October 31st is the current scheduled date for when the UK will finally leave the EU; this is not a coincidence, as police believe and academics believe that Brexit will spark a rise in supposed hate crime.
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Professor Williams said the political environment after Brexit Day will likely be “toxic,” and therefore a perfect test for the AI. “Brexit is one of our test cases to see if hate speech will spike,” he said. “There has been talk of riots on the streets, and there is an expectation that tensions will bubble up around that date.”
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A spokesman for the NPCC defended their use of the technology:
It is not used to “trawl” for offences but will help us to identify early rises in tensions, informing force level operational decisions and our work with communities in seeking to reduce hostility at an early stage. Hateful abuse online can leave victims with significant psychological harm, but can also lead to more serious physical offences. Police need to be able to intervene at the earliest possible stage to reassure victims that we will act to protect them. We absolutely recognise and uphold the right to free speech even where it causes offence – but this does not extend to inciting hatred or threatening people.
The AI will be attached to the Online Hate Speech Dashboard, which has received £1.7 million in funding from the Economic and Social Research Council, as well as the US Department of Justice, hinting at the potential international relevance of the project.
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