Smart Policing: A Critical Review of the Literature

Afzal, Muhammad; Panagiotopoulos, Panos

doi:10.1007/978-3-030-57599-1_5

Cited by 10 publications

(5 citation statements)

References 50 publications

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“…By systematically integrating these smart planning approaches with cutting-edge urban planning technologies, law enforcement agencies can strategically deploy mini-police stations to enhance police visibility, deter crime, and create safer communities in areas with high crime rates (Afzal & Panagiotopoulos, 2020;Yamin et al, 2020).…”

Section: Conclusion and Recommendations For Future Researchmentioning

confidence: 99%

Smart city planning focused on the US cities in need of policing innovations and public health safety technologies and strategies

Springs

2024

HEM

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The issue of firearm-related injuries, deaths and crime in the United States is of particular relevance. Every year, about 32,000 lives are lost as a result of firearm-related incidents, including self-inflicted injuries. Other 74,000 people suffer non-fatal gunshot wounds. Addressing this multi-faceted problem is possible through a comprehensive and integrated approach that encompasses public health initiatives, law enforcement efforts, and security measures. In the context of solving this problem, the concepts of “community-oriented policing”, “problem-oriented policing”, “broken windows theory”, “smart city social sustainability initiative” (multi-system improvement and meeting the needs of marginalised residents), “feedback methodology”, etc. are thoroughly considered. The author proposes the strategic deployment of mini-police stations in areas with a high crime rate as proper centres of police visibility and a deterrent to criminals. To realise this task, it is necessary to integrate the latest approaches to Smart Urban Development with innovative urban planning technologies that would increase the influence of law enforcement agencies in the process of protecting public health and safety in cities. In particular, the article proposes the following for implementation: identifying crime hotspots by means of advanced geographic information systems, applying machine learning algorithms to predict future crime trends, using advanced real-time surveillance technologies and firearms detection systems, applying geospatial analysis to optimise patrol routes, dynamically adjusting patrol routes depending on real-time data analytics, deploying mobile command centres. As a result, law enforcement agencies can effectively communicate to potential criminals that their actions will not go unnoticed. They may achieve significant success in improving the overall quality of life of residents in such areas. Also, they will create safer communities, and reduce the number of incidents involving the use of firearms.

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Section: Conclusion and Recommendations For Future Researchmentioning

confidence: 99%

Smart city planning focused on the US cities in need of policing innovations and public health safety technologies and strategies

Springs

2024

HEM

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“…Algorithmic policing is a process that automatically collects, analyses, and interprets (big) data using algorithmic and human agents, which is then translated into real-world policing actions (Brayne 2017, Ridgeway 2018, Bennet Moses and Chan 2018, Manning 2019, Afzal and Panagiotopoulos 2020. This development also has significant implications for the policing function by replacing certain aspects of human agency with algorithms (Makarius 2020, Peeters 2020.…”

Section: Algorithmic Policingmentioning

confidence: 99%

Algorithmic policing accountability: eight sociotechnical challenges

Wessels

2023

Policing and Society

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Law enforcement agencies increasingly adopt algorithms for their policing practices, leading to new accountability challenges. However, academic literature tends to regard algorithmic applications as a single entity, resulting in broad and general statements on these risks. By introducing a sociotechnical model of algorithmic policing, this paper identifies eight accountability challenges that originate from technical, organisational and human components. It is illuminated how algorithmic policing accountability is a process that consists of multiple steps that should be considered separately to scrutinise the accountability challenges. The present study showcases how the sociotechnical context determines whether and how accountability issues might arise in algorithmic policing practices. The accountability challenges are presented as propositions that can direct future research in assessing the accountability risks of algorithmic policing applications.

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“…HaterNet is an intelligent system deployed by the Spanish National Office Against Hate Crimes of the Spanish State Secretariat for Security that identifies and monitors the evolution of hate speech in Twitter (Pereira-Kohatsu et al, 2019). Smart policing is another area that could potentially benefit from automatic detection of threats to people or nationalities (Afzal & Panagiotopoulos, 2020). As another example, PeaceTech combats hate speech by identifying inflammatory lexicons on social media and offering alternative words and phrases as a key resource for local activists and organizations.…”

Section: Applicationsmentioning

confidence: 99%

Confronting Abusive Language Online: A Survey from the Ethical and Human Rights Perspective

Kiritchenko

Nejadgholi

Fraser

2021

jair

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The pervasiveness of abusive content on the internet can lead to severe psychological and physical harm. Significant effort in Natural Language Processing (NLP) research has been devoted to addressing this problem through abusive content detection and related sub-areas, such as the detection of hate speech, toxicity, cyberbullying, etc. Although current technologies achieve high classification performance in research studies, it has been observed that the real-life application of this technology can cause unintended harms, such as the silencing of under-represented groups. We review a large body of NLP research on automatic abuse detection with a new focus on ethical challenges, organized around eight established ethical principles: privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and promotion of human values. In many cases, these principles relate not only to situational ethical codes, which may be context-dependent, but are in fact connected to universal human rights, such as the right to privacy, freedom from discrimination, and freedom of expression. We highlight the need to examine the broad social impacts of this technology, and to bring ethical and human rights considerations to every stage of the application life-cycle, from task formulation and dataset design, to model training and evaluation, to application deployment. Guided by these principles, we identify several opportunities for rights-respecting, socio-technical solutions to detect and confront online abuse, including ‘nudging’, ‘quarantining’, value sensitive design, counter-narratives, style transfer, and AI-driven public education applications.evaluation, to application deployment. Guided by these principles, we identify several opportunities for rights-respecting, socio-technical solutions to detect and confront online abuse, including 'nudging', 'quarantining', value sensitive design, counter-narratives, style transfer, and AI-driven public education applications.

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Smart Policing: A Critical Review of the Literature

Cited by 10 publications

References 50 publications

Smart city planning focused on the US cities in need of policing innovations and public health safety technologies and strategies

Smart city planning focused on the US cities in need of policing innovations and public health safety technologies and strategies

Algorithmic policing accountability: eight sociotechnical challenges

Confronting Abusive Language Online: A Survey from the Ethical and Human Rights Perspective

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