Robocop’s Future: Body-Worn Video in the Digital Transformation Age

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Unveiling the Power of Digital Transformation in Policing

Barnard (1921) famously quoted that, “one picture is worth a thousand words” to encapsulate the power of visual imagery to convey complex ideas or emotions.? In the context of body-worn video (BWV) cameras, commonly used by police officers, this adage takes on even greater significance.? The rise of digital technologies, in particular BWV cameras has reshaped the very essence of policing, promising greater efficiency, accuracy, and accountability.? This stands out as a symbol of modernisation, offering a real-time lens and data intelligence to inform police force operations (Rogers and Scally, 2018).? A recording from an incident scene can capture evidence highlighting the raw emotion and action in the courts in a manner that can never be documented in written statements (Graham, 2017).

A recent WBS MBA module on Digital Transformation prompted me to consider a previous role I held with the British Transport Police (BTP), as police staff and digital transformation programme manager for the BWV trial in 2014.? The role involved exploring the BWV cameras digital capabilities, executing 328 Axon BWV cameras across 23 police locations, including the railways and London Underground.

This led me to wonder, what does the police sector need to stay ahead of the digital transformation curve when it comes to BWV cameras?? Let’s explore this further…

The blog delves into the BWV evolution within the digital transformation age, exploring its disruptive capabilities, societal implications, police forces’ strategic imperatives and the future impacts.

Body Worn Video Revolution

First introduced in the UK by Devon & Cornwall Police in 2005, BWV cameras have been utilised widely across various police forces today (Eve, 2020).? BWV evolution and digital optimisation has revolutionised the policing industry for front-line police officers, with the technology implemented in many parts of the world (Bowling and Iyer, 2019).? The devices collect audio, still images and video data during police encounters with the public, which can be worn on uniforms or as headcams to highlight the incident from a police officer’s perspective (College of Policing, 2021).? They provide an invaluable tool to enhance ‘high-quality’ evidence capture to improve public confidence in the police force and of the police officer; increase productivity and improve working practices; reduce crime incidents, costs in early guilty pleas and number of police complaints received; and aids as a training and professional development tool (Jameel and Bunn, 2015; He, 2022).? A study of 2000 police officers across the UK and US found a 93% decrease in police complaints made by the public upon wearing the BWV cameras (Ariel and Sutherland, 2016). Given these key strategic benefits, BWV cameras are likely the most rapidly diffusing technology in modern police history (Lum et al, 2020).?

The Intersection of Technology and Policing

Embracing Facial Recognition

In the digital transformation age, police forces worldwide are integrating cutting-edge technologies into their operations (Gagne Mapp, 2023).? Expanding BWV capabilities much more to include facial recognition, powered by machine learning algorithms, enables the police to use still imagery or live video footage to scan and identify a person of interest (Home Office, 2023). Officers can quickly identify suspects in a crowd or track individuals with outstanding warrants with a simple scan of their faces, for example, events, such as festivals and sporting games that can become aggressive (Innefu, 2024).

Automated Number Plate Recognition (ANPR)

When ANPR is needed, the integration of the technology with BWV cameras will enable the identification of vehicles involved in criminal activities or traffic violations.? To instantly cross-reference the licence plate with police databases officers can intercept vehicles to safeguard communities and reduce a potential crime being committed (Police.UK, 2024).

Augmented Artificial Intelligence (AI) for Report Writing

Both the facial recognition and ANPR camera capabilities ultimately lead to the requirement for the police officer to package up the evidence for prosecution, including writing up the final incident report (Bowling and Iyer, 2019). Thereby taking the advancements in digital transformation within policing further, with the application of generative AI capabilities to draft the report.?

According to Christensen, Raynor and McDonald (2015), improvement of the technology will eventually disrupt industries by offering accessibility and affordability of products to the wider market.? As AI and facial recognition capabilities combined with BWV cameras continue to gain momentum, with suppliers enabling increased affordability, most police forces will invest in the technology to support its operations and address a niche or underserved market in law enforcement (ICO, 2024).? Technological advances in recent years have changed the nature of policing where many methods and tools have become obsolete, however have increased police capabilities, value proposition and affordability (Strom, 2017). Additionally, a letter from the Crime, Policing and Fire Minister, Rt Hon Chris Philp MP (2023) announced a funding commitment of ￡17.5 million to enable resilient and accurate systems that offer the potential for further innovation in this area.??

This is a positive step, considering all the recent government cutbacks, it is reassuring to read that funding is available to support innovative digital transformation within a policing environment.

Future of Work, Societal Trends and Strategic Objectives

The future of policing will be shaped by a confluence of technological advancements and societal trends.? Police forces must adapt their recruitment and training strategies to attract tech-savvy individuals capable of harnessing the power of emerging technologies (Connon et al, 2022).? For existing police officers, there will be a growing need to adapt their skills or risk falling behind. However, deskilling police officers is a significant risk and a major outcome of automation (Joh, 2018).? The digital transformation of the policing sector will significantly streamline various aspects of the roles, such as security surveillance and incident reporting, which will possibly generate new forms of police work (Bowling and Iyer, 2019).? The resulting benefits will include increased efficiency, and productivity to focus on more complex cases, including increased visibility of the police officers within the community (Juryala, 2023).? Consequently, the possibility of automating a wide range of manual processes could impact on limited expertise, human interaction, and creativity at the detriment to the public (Ellingrud et al, 2023).??

Harnessing the full potential of BWV technology requires a holistic approach encompassing the following strategic objectives: Firstly, reduce crime; implementing predictive AI algorithms to analyse historical crime data, determine patterns and forecast potential crime hotspots in high-risk areas to deter criminal activity in real-time.? For example, identifying known suspects or stolen vehicles, or behaviour recognition before an incident occurs prompting further investigation (Mohindroo, 2023).? This will enable officers to address emerging crime trends and ensure resource optimisation. Secondly, empowered data-driven decision making; evaluating the effectiveness of policing strategies and interventions by analysing data collected from the BWV camera, enabling continuous improvement and refinement of operational tactics (Strom, 2017).? Finally, enhanced evidence collection and documentation; leveraging generative AI to automate detailed incidents reports based on captured footage providing more time for visible community-based policing (Bowling and Iyer, 2019).

Innovative Business Models and Value Proposition

To capitalise on all aspects of the BWV camera technology, police forces must embrace innovative business models that go beyond traditional procurement and deployment strategies. One such model is the concept of a "policing-as-a-service" platform as a cloud-based service to serve the community, where BWV technology is offered as part of a comprehensive suite of digital policing solutions (Zargari and Smith, 2014). By developing strategic partnerships with technology suppliers, data analytics firms, healthcare and education institutions, police forces can leverage BWV data through an integrated system to examine an incident, as part of a National Knowledge Hub to support vulnerable victims (Kimbell, 2021).? This would provide police forces with access to unprecedented levels of data and analytical information.? In conjunction with automating the documentation process, generative AI will increase capacity and resource allocation, provide cost optimisation and enhance crime prevention, enabling officers to focus efforts on proactive policing initiatives (Kimbell, 2021).

Responsible Digital Transformation

Having previously delivered on the BWV trial project, privacy concerns, data security and bias are still key considerations for usage, if not more elevated especially with facial recognition, ANPR and automated incident reporting capabilities to factor in and is not without controversy (Kawamoto, 2018). Concerns around ethical uses and potential for misuse, along with rights to privacy will need to ensure that legal and regulatory policies are in effect for appropriate use of technology (Strom, 2017).? The sensitive nature of the data collected will risk potential bias embedded within the algorithms leading to discrimination, invasion of privacy and societal implications (Connon et al, 2022).? As such, mitigating data privacy risk and ensuring AI algorithms transparency is paramount for data integrity and privacy protection (Mohindroo, 2023).? Ethical training will also become more important than ever to understand the ethical limitations of when to rely on machine learning and when human judgement should prevail (Bremer, 2023).? Furthermore, police forces and technology providers need to ensure that these capabilities are utilised ethically throughout the end-to-end supply chain process.? Policymakers must establish robust frameworks to ensure transparency, accountability and fairness in AI applications, safeguarding the rights of both public and officers, while building their trust and confidence in the technology.? Any current governance policies will need to be reassessed, with public stakeholder engagement to ensure compliance (Kawamoto, 2018).

Bridging the Gap: Generative AI for Enhanced Report Writing Efficiency in Policing

Imagine a scenario where officers no longer spend hours documenting incidents and writing reports.? Consider the cumbersome task of documenting a traffic accident. Traditionally, officers spend valuable time jotting down details, often prone to errors and gaps in key information. However, with the integration of generative AI, this process has undergone a seismic shift (Bowling and Iyer, 2019). Officers can now dictate the sequence of events, vehicle descriptions, and witness statements directly into their BWV cameras or write a brief prompt into the specialist AI software, using BWV video footage, live facial recognition and ANPR, as an integrated evidence package. The AI algorithms analyse this data, generating meticulously crafted reports in a fraction of the time, while written in the persona of a police officer (Bowling and Iyer, 2019).? The police officer will be expected to continue to review and verify the accuracy of the information.? Thus, reducing the time spent to complete a report from possibly weeks or months for humans to write up fulfils a need within minutes by applying AI capabilities (PERF, 2023).

Streamlining ‘Tasks, Technology and Work Process’ Operations

This innovative approach accelerates the reporting process. By embracing the power of predicative AI and generative AI, police forces can allocate resources more efficiently, redirecting valuable time towards proactive policing initiatives. Furthermore, the standardised nature of AI-generated reports enhances interoperability and data sharing across police forces, fostering collaboration and synergy (NPCC, 2023).

Generative AI could revolutionise the process of report writing for police officers through multiple channels (NPCC, 2023).? By leveraging natural language processing (NLP) or large language models (LLMs) algorithms, officers can dictate incident reports ‘on-the-go’ during field engagements allowing for efficient documentation of critical information (Hsiung, Chen and Horowitz, 2023).? This not only streamlines administrative workflows, however also ensures accuracy and comprehensiveness of incident reports, therefore enhancing the evidentiary value and facilitating court proceedings (Rafiq, 2019). Examples, like Chat GTP or Copilot can act as an educational tool, summarising or listening to evidence, producing transcripts, and creating a report (Filipsson, 2024).?

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Business Opportunity: Unlocking Operational Efficiency

Response within the National Policing Digital Strategy 2020 - 2030, has stated that the opportunities and challenges that the digital disruption presents to policing are rapidly becoming defining issues for the police service and must be addressed (NPCC, 2023).

The adoption of predictive AI and generative AI presents a compelling business case for police forces worldwide (Chiancone, 2023). Beyond the immediate gains in productivity, this technology heralds a paradigm shift in operational efficiency.? By automating mundane tasks, officers can focus on high-value activities, such as community engagement and crime prevention (Bowling and Iyer, 2019). Moreover, the standardised documentation facilitated by AI streamlines court proceedings, expediting the court administration process (Miller and Toliver, 2014).??

Navigating the Roadblocks

While the promise of AI capabilities in policing is undeniable, its implementation is not devoid of challenges. As with any disruptive technology, several hurdles must be addressed to realise its full potential.

Technological Limitations

Despite significant advancements, generative AI is not immune to limitations (NPCC, 2023; Strom, 2017).? Complex scenarios that require nuanced interpretation and context may challenge current algorithms that systems like Chat GTP do not understand.? While the system is capable of emotional intelligence, this would need to be monitored closely, especially in relation to any sensitive cases e.g., involving children, domestic violence, or sexual assault (Bashar, 2023; Potts, 2024). Moreover, ensuring the accuracy and reliability of AI-generated reports demands ongoing refinement and validation, necessitating substantial investments in research and development.

Cultural Shift

Embracing AI-powered solutions entails a cultural shift within police forces. Officers accustomed to traditional reporting methods may resist change, viewing automation as a threat to their autonomy and expertise. Effective change management strategies, coupled with comprehensive training programs, are essential to instil confidence and foster adoption across all levels of the organisation. Finally, ensuring strong leadership buy-in is needed to pave the way for purpose-led digital innovation (NPCC, 2023).

Budgetary Constraints

Integrating generative AI solutions into policing operations requires significant financial investment.? Procuring cutting-edge technology and implementing infrastructure upgrades incur high capital costs (Strom, 2017).? This can be off-set against declining revenue costs to continue the running of the system year-on-year.? From my time within the police force, contracts were negotiated over a 5-year period, with a break-clause after 3 years to ensure value for money.? Police forces must navigate around these constraints, prioritising key initiatives that deliver key benefits, particularly when accountable to the public taxpayer (Connon et al, 2022).?

Embracing the Future of Policing

What does the future look like for digital disruption within the police force?? It looks like there is more to come and it seems that the police forces are embracing it with open arms.? Whilst BWV cameras are a means to capture evidence, with the rise in social media and use of public capture, police officers will additionally appeal to crowdsourcing for evidence (NPCC, 2023).

AI in law enforcement is a game-changer from the traditional policing methods and to fall behind the curve comes with many pitfalls to the detriment of both the profession and the community.? This cannot be ignored and can surely only enhance police operational capabilities and improve public safety outcomes.??

Delivering on the BWV trial was a project very near and dear to my heart.? I revel in the opportunity to discuss my experience of executing project outcomes and its successes with future employers.? The benefits to be realised from embracing the innovative technology integrated with AI capabilities brings me reassurance as to where BWV cameras can go from here and they by far outweigh the challenges encountered in project execution and I’m very excited to see what is ahead for BWV cameras technology.

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Useful Articles in the Domain of Digital Transformation and Policing:

Ariel, B. and Sutherland, A. (2016). Use of body-worn cameras sees complaints against police ‘virtually vanish’, study finds. [online] University of Cambridge. Available from: https://www.cam.ac.uk/research/news/use-of-body-worn-cameras-sees-complaints-against-police-virtually-vanish-study-finds.? [Accessed 01/04/24].

Britannica. (1921).? The Editors of Encyclopedia. "Frederick Barnard".?Encyclopedia Britannica. [online]. https://www.britannica.com/biography/Frederick-Barnard. [Accessed: 29/03/24].

Bowling, B. and Iyer, S. (2019). Automated policing: the case of body-worn video. International Journal of Law Context. 15(2), pp140-161. Available from: https://www.cambridge.org/core/journals/international-journal-of-law-in-context/article/automated-policing-the-case-of-bodyworn-video/921E811F147249D1699B59471CDC4B94. [Accessed: 31/03/24]

Bremer, Jr, T. (2023). How Artificial Intelligence Will Transform the Role of the Patrol Officer. [online] www.dhirubhai.net. Available from: https://www.dhirubhai.net/pulse/how-artificial-intelligence-transform-role-patrol-bremer-jr-/ [Accessed 05/04/24].

Chat GTP. (2024). Traffic violation by John Doe.? [online] www.chat.openai.com. Available from: https://chat.openai.com/c/e1b7d2e4-07c8-42fe-9920-bd11b97b692b. [Accessed: 23/04/24].

Chiancone, C. (2023). The Role of Artificial Intelligence in Law Enforcement. [online] www.dhirubhai.net. Available from: https://www.dhirubhai.net/pulse/role-artificial-intelligence-law-enforcement-chris-chiancone/ [Accessed: 07/04/24].

Christensen, C.M., Raynor, M.E. and McDonald, R. (2015). What is Disruptive Innovation? [online] Harvard Business Review. Available at: https://hbr.org/2015/12/what-is-disruptive-innovation. [Accessed: 04/04/24].

College of Policing. (2021).? Body-worn cameras.? Available from: https://www.college.police.uk/research/crime-reduction-toolkit/body-worn-cameras.? [Accessed: 01/04/2024]

Connon, I, L, C, Egan, M, Hamilton-Smith, N, MacKay, N, Miranda, D, and Webster, C, W, R. (2023).? Review of emerging technologies in policing. University of Dundee. [online].? Available from: https://discovery.dundee.ac.uk/ws/portalfiles/portal/98288751/review_emerging_technologies_policing_report_1_.pdf.? [Accessed: 6 Apr 2024]

D’Agostino, S. (2024). Facial Recognition Heads to Class. Will Students benefit? [online]. www.insideed.com.? Available from: https://www.insidehighered.com/news/tech-innovation/teaching-learning/2024/02/27/facial-recognition-heads-class-will-students. [Accessed 23/4/24].??

Du Bashar, S. (2023). Chat GPT AI and Emotional Intelligence: The Art of Empathetic Conversations. [online] www.dhirubhai.net. Available from: https://www.dhirubhai.net/pulse/chat-gpt-ai-emotional-intelligence-art-empathetic-sahea-dul-bashar/ [Accessed: 07/04/24].

Ellingrud, K., Sanghvi, S., Singh Dandona, G., Madgavkar, A., Chui, M., White, O. and Hasebe, P. (2023). Generative AI and the Future of Work in America | McKinsey. [online] www.mckinsey.com. Available from: https://www.mckinsey.com/mgi/our-research/generative-ai-and-the-future-of-work-in-america [Accessed: 0424].

Eve, C. (2020). How Devon and Cornwall Police body worn video is making life safer for everyone.? PlymouthLive.? Available from: https://www.plymouthherald.co.uk/news/plymouth-news/police-bodyworn-video-camera-bwv-4437226. [Accessed: 30/03/24].

Filipsson, F. (2023). Microsoft Copilot and ChatGPT – A Comparative Analysis. [online] redresscompliance.com. Available from: https://redresscompliance.com/microsoft-copilot-and-chatgpt-a-comparative-analysis/ [Accessed: 03/04/24].

Gagne Mapp, M-R. (2023). Byte and Badge: Policing in the Digital Frontier.? Irish Tech News.? [online].? Available from: https://irishtechnews.ie/byte-and-the-badge-policing-in-the-digital-frontier/.? [Accessed: 02/04/24]

Graham, O. (2017). Body worn cameras to be rolled out to 2,800 British Transport Police officers. MyLondon. Available from: https://www.mylondon.news/news/uk-world-news/body-worn-cameras-rolled-out-13655920. [Accessed: 30/03/24]

Hazlegreaves, S. (2020). Police Departments Turn to Digital Transformation to Lower Costs. [online] Open Access Government. Available at: https://www.openaccessgovernment.org/police-departments-turn-to-digital-transformation-to-lower-costs/95914. [Accessed: 04/04/24].

He, E. (2022). Exploring Benefits of Body Worn Cameras. Kocchi’s.? Available from: https://www.kocchis.com/blog/body-worn-cameras/. [Accessed: 31/03/24]

Home Office (2023) Police use of Facial Recognition: Factsheet. Home Office in the media [blog]. 29 October. Available from: https://homeofficemedia.blog.gov.uk/2023/10/29/police-use-of-facial-recognition-factsheet/.[Accessed: 02/04/24].

Hsiung, C., Chen, F. and Horowitz, A. (2023). Exploring AI for Law Enforcement. [online] Policechiefmagazine.org. Available from: https://www.policechiefmagazine.org/exploring-ai-law-enforcement-interview/ [Accessed: 03/04/24].

Information Commissioner’s Office. (2024).? Additional considerations for technologies other than CCTV. ICO. [Online].? Available from: https://ico.org.uk/for-organisations/uk-gdpr-guidance-and-resources/cctv-and-video-surveillance/guidance-on-video-surveillance-including-cctv/additional-considerations-for-technologies-other-than-cctv/?q=children. [Accessed: 02/04/24]?

Innefu (2024). How Artificial Intelligence In Policing Helps Crime Detection. [online] Available from: https://www.innefu.com/blog/how-artificial-intelligence-in-policing-helps-crime-detection#:~:text=An%20Important%20Part%20of%20AI [Accessed 03/04/24].

Jameel, L. and Bunn, S. (2015) Body-Worn Video in UK Policing. Houses of Parliament.? Available from: https://researchbriefings.files.parliament.uk/documents/POST-PB-0014/POST-PB-0014.pdf.? [Accessed: 31/03/24]

Joh, E. (2018). Automated policing. Ohio State Journal of Criminal Law. (15), 559–563. [Accessed: 5/4/24]

Juryala, A. (2023). How AI is changing the way police fight crime. [online] Medium. Available from: https://medium.com/@jsaiaarthi/how-ai-is-changing-the-way-police-fight-crime-c49926f20224 [Accessed: 05/04/24].

Kawamoto, D. (2018). If Facial Recognition Comes to Body Cameras, How Will Government Respond? [online] GovTech. Available from: https://www.govtech.com/public-safety/if-facial-recognition-comes-to-body-cameras-how-will-government-respond.html [Accessed 06/0424].

Kimbell, J. (2021). The Growth of Digital Policing: Enhancing Efficiency and Safety through Technology. [online] blog.govnet.co.uk. Available from: https://blog.govnet.co.uk/justice/the-growth-of-digital-policing [Accessed: 06/04/24].

Lum, C., Koper, C.S., Wilson, D.B., Stoltz, M., Goodier, M., Eggins, E., Higginson, A. and Mazerolle, L. (2020). Body‐worn cameras’ effects on police officers and citizen behavior: A systematic review. Campbell Systematic Reviews, [online] 16(3). Available from: doi:https://doi.org/10.1002/cl2.1112. [Accessed: 07/04/24]

Miller, Lindsay, Jessica Toliver, and Police Executive Research Forum. (2014). Implementing a Body-Worn Camera Program: Recommendations and Lessons Learned. Washington, DC: Office of Community Oriented Policing Services.? Available from: https://www.justice.gov/iso/opa/resources/472014912134715246869.pdf.? [Accessed: 7 Apr 2024]

Mohindroo, S. (2023). Harnessing Generative AI in Law Enforcement: A Vision for Smarter, Safer Communities. [online] www.dhirubhai.net. Available from: https://www.dhirubhai.net/pulse/harnessing-generative-ai-law-enforcement-vision-safer-mohindroo--xwsxf/ [Accessed: 6/04/24].

National Police Chief's Council (2020). National Policing Digital Strategy. [online] Available from: https://pds.police.uk/wp-content/uploads/2020/01/National-Policing-Digital-Strategy-2020-2030.pdf [Accessed: 12/04/24].

Philip MP, R.H.C. (2023).?Letter to Police AI Enabled Facial Recognition Searches. [online] GOV.UK. Available at: https://www.gov.uk/government/news/letter-to-police-on-ai-enabled-facial-recognition-searches [Accessed 2 Apr. 2024].

Potts, J. (2024). What are the benefits of ChatGPT for police report writing? [online] Police1. Available from: https://www.police1.com/tech-pulse/the-impact-of-large-language-models-on-police-report-writing-and-beyond [Accessed: 07/04/24].

Police Executive Research Forum (PERF). (2023).? Body-worn cameras a decade later: what we know.? [online]. Available from: https://www.policeforum.org/assets/BWCdecadelater.pdf.? [Accessed: 04/04/24].

Police.UK. (2024). Automatic Number Plate Recognition (ANPR).? [Online].? Available from: https://www.police.uk/advice/advice-and-information/rs/road-safety/automatic-number-plate-recognition-anpr/.? [Accessed: 03/04/2024].

Rafiq, M. (2019). Beyond body-worn video: The future of digital evidence management. [online] Policing Insight. Available from: https://policinginsight.com/news/beyond-body-worn-video-the-future-of-digital-evidence-management/ [Accessed 03/04/24].

Rogers, C.?and?Scally, E.J.?(2018), "Police use of technology: insights from the literature",?International Journal of Emergency Services, Vol. 7 No. 2, pp. 100-110. [online]. Available from:?https://doi.org/10.1108/IJES-03-2017-0012.? [Accessed: 02/04/24].

Strom, K. (2016). Research on the Impact of Technology on Policing Strategy in the 21st century, Final Report. [online] Available from: https://www.ojp.gov/pdffiles1/nij/grants/251140.pdf [Accessed 02/04/24].

Zargari, S.A. and Smith, A. (2014). Policing as a Service in the Cloud. Information Security Journal: A Global Perspective, 23(4-6), pp.148–158. Available from: doi:https://doi.org/10.1080/19393555.2014.931490. [Accessed 12/04/24].