S4 | Ep 9 | Building Trust; The Power of Prediction with Aimee Smith, Director of Data at Metropolitan Police

Driven by Data: The Podcast

In Episode 9, of Season 4, of Driven by Data: The Podcast, Kyle Winterbottom is joined by Aimee Smith, Director of Data at Metropolitan Police (probably known as Scotland Yard by most outside of the UK), where they discuss the opportunities that Data & Analytics presents to revolutionise policing and moving to prediction for prevention, which includes;

• Tackling Organised Crime Groups
• Chairing the national police data board bringing together 43 organisations
• Being one of the most complained about organisations to the ICO
• The importance of executive sponsorship
• How investment is linked to your highest leadership level
• The biggest challenges Met Police/Scotland Yard have with data
• Why their people are genuinely their biggest asset and the challenge that creates for D&A investment
• Peelian principles; why data has always been used in policing
• What they have done to prove their value
• Using credible stakeholders within the organisations to tell the data story
• The different levels of data-led decision-making
• The opportunity to revolutionise policing through data and analytics
• The challenges of being judged based on media headlines
• Why the obsession with catching offenders could be the wrong approach
• Prioritising workload in potential life and death situations
• How the public help set the organisation's business strategy
• Why most people don’t connect data to their core role and mission
• Why their data can be valuable to UK PLC but the challenges in articulating how
• How the expectations of how data is used are different within the same organisation
• Fixing broken relationships with the black community while also trying to deploy DS/ML with biased data
• Tackling bias and ethics as an organisation that people love to scrutinise
• Using their own DS team to test for bias
• Choosing not to deploy certain solutions due to bias and ethical concerns
• Needing to build trust with the public before they can execute on predictive analytics
• A shout-out to Davin Crowley Sweet

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