Tech News : AI Saves Police Admin Time – A Lot

Written by Pronetic

Pronetic is a leading provider of core IT support for ISO 27001, Cyber Essentials and Cyber Essentials Plus compliance.

December 21, 2023

It’s been reported that the UK’s Minister of State (Minister for Crime, Policing and Fire), the Rt Hon Chris Philp MP, has urged UK police forces to follow Bedfordshire’s example of using artificial intelligence (AI) to save time and money in carrying out admin tasks. 

Which Admin Tasks? 

The main task that Mr Philip was referring to is redacting personal data from case files that need to be sent to the Crown Prosecution Service (CPS) in order to comply with data protection laws. This is because such case files can, as part of witness statements, contain phone records (e.g. downloaded data from seized mobile phones) and other evidence, as well as personal details like addresses, phone numbers, and vehicle registrations. These personal details can’t be shared under UK data protection regulations, hence the need for redactions. 

Time-Saving 

Before AI, the task of manually sifting through all the case files to find the personal data and redact it could take days. With the help of AI, it’s been reported that this time can be reduced significantly so that it only takes a matter of minutes. 

Bedfordshire Police Using ‘Docdefender’ AI Tool 

As highlighted recently in the UK government’s Policing Productivity Review, Bedfordshire Police have been testing the Docdefender AI-assisted tool to automatically highlight the potential data that might need to be redacted. Time and motion studies have shown that using the DocDefender tool instead of the usual manual approach has resulted in between 80 and 92 per cent time savings! 

Examples 

The report highlighted some more specific examples of Docdefender’s time-saving abilities, such as: 

– The redaction of a phone download, which would have previously taken days to sort through for redactions, only taking 20 minutes with Docdefender. 

– The redaction of a 350,000 cells spreadsheet in thirty minutes using Docdefender , which would previously have taken four hours. 

– A decrease in investigator time spent redacting witness statements, with a potential efficiency savings of 18,900 police officer hours per annum. 

Other Forces Too

As suggested by the minister, Bedfordshire Police’s Police Digital Services have reported engaging with other UK forces to explore how to give them access to this AI-powered, timesaving “auto redaction” solution. Work has also reportedly begun to scope the requirements and market for audio and visual redaction, with a view to implementing it in 2024. 

Other Police Forces Experimenting 

Police forces reported to be in the process of looking at how such technical solutions could reduce time spent on reviewing and redacting case file material include Avon and Somerset Police, Cleveland Police, Devon and Cornwall Police, Dorset Police, Greater Manchester Police, Merseyside Police, the Metropolitan Police Service, Thames Valley Police and Wiltshire Police. 

The Policing Productivity Report 

The recent Policing Productivity Report highlights how the recently formed NPCC Science and Innovation Coordination Committee for national policing will help with the adoption of such innovation projects across policing. The report suggests that knowledge sharing between forces about innovative schemes (like automatic redactions), and upfront investment to implement new the technology could both help. For example, the report says that “recent investments in robotic process automation and automatic redaction have successfully addressed this problem by giving forces a short-term boost in funding to initiate a solution with the expectation the force then take on the business-as-usual running cost. This model should be encouraged.” 

What Does This Mean For Your Business? 

The integration of AI, as exemplified by Bedfordshire Police’s use of the Docdefender tool, signals a transformative era for businesses, particularly in sectors burdened with heavy administrative tasks. The substantial time and cost savings demonstrated by AI in police administrative processes could be extrapolated to various business operations, offering a glimpse into a more efficient and cost-effective future. 

For businesses, the adoption of AI for administrative tasks could mean a significant reduction in manual labour and time (and associated costs) spent on mundane activities. As seen in the case of Bedfordshire Police, tasks that once took days can now be completed in minutes with the help of AI. For businesses, this efficiency may not only accelerate processes but also saves valuable human resources, allowing staff to focus on more strategic, creative, or complex tasks that cannot be automated. The potential for AI to enhance productivity and reduce operational costs is, therefore, immense, making it an attractive proposition for businesses looking to optimise their workflows. 

However, while the benefits are substantial, reliance on AI also introduces new risks and considerations. Dependence on technology can lead to vulnerabilities such as potential system failures or cyber threats. Businesses should, therefore, invest in robust cybersecurity measures and have contingency plans in place. Additionally, AI systems, while impressively accurate, aren’t infallible (e.g. AI hallucinations). Regular oversight and quality checks are necessary to ensure that AI-driven processes meet required standards. 

Another aspect to consider is the ethical implications and regulatory compliance, especially in handling sensitive data. AI systems must be designed to comply with data protection laws, similar to the requirements for redacting personal data in police case files. This requires a balance between leveraging AI for efficiency and ensuring privacy and legal compliance. 

As illustrated by the example of Bedfordshire Police, using AI to carry out administrative tasks could, therefore, offer significant advantages for businesses and a wide range of organisations in terms of efficiency, cost reduction, and resource allocation.  

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