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Exploring Public's perception of safety and video surveillance technology: A survey approach

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  • Ardabili, Babak Rahimi
  • Danesh Pazho, Armin
  • Alinezhad Noghre, Ghazal
  • Katariya, Vinit
  • Hull, Gordon
  • Reid, Shannon
  • Tabkhi, Hamed

Abstract

Addressing public safety effectively requires incorporating diverse stakeholder perspectives, particularly those of the community, which are often underrepresented compared to other stakeholders. This study presents a comprehensive analysis of the community's general public safety concerns, their view of existing surveillance technologies, and their perception of AI-driven solutions for enhancing safety in urban environments, focusing on Charlotte, NC. Through a survey approach, including in-person surveys conducted in August and September 2023 with 410 participants, this research investigates demographic factors such as age, gender, ethnicity, and educational level to gain insights into public perception and concerns toward public safety and possible solutions. Based on the type of dependent variables, we utilized different statistical and significance analyses, such as logit regression and ordinal logistic regression, to explore the effects of demographic factors on the various dependent variables. Our results reveal demographic differences in public safety concerns. Younger females tend to feel less secure yet trust existing video surveillance systems, whereas older, educated individuals are more concerned about violent crimes in malls. Additionally, attitudes towards AI-driven surveillance differ: older Black individuals demonstrate support for it despite having concerns about data privacy, while educated females show a tendency towards skepticism.

Suggested Citation

  • Ardabili, Babak Rahimi & Danesh Pazho, Armin & Alinezhad Noghre, Ghazal & Katariya, Vinit & Hull, Gordon & Reid, Shannon & Tabkhi, Hamed, 2024. "Exploring Public's perception of safety and video surveillance technology: A survey approach," Technology in Society, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:teinso:v:78:y:2024:i:c:s0160791x24001891
    DOI: 10.1016/j.techsoc.2024.102641
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    References listed on IDEAS

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    1. Choung, Hyesun & David, Prabu & Ling, Tsai-Wei, 2024. "Acceptance of AI-powered facial recognition technology in surveillance scenarios: Role of trust, security, and privacy perceptions," Technology in Society, Elsevier, vol. 79(C).

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