The Use of Robotic Surveillance in the UAE in 2035: Balancing, Innovation, Regulation, and Privacy

This research explores the future of robotic surveillance in the United Arab Emirates (UAE) by 2035, aiming to balance innovation, regulatory oversight, and privacy protection. It investigates the intersection of national security objectives, ethical AI governance, and public trust within the UAE’s rapidly advancing smart city and law enforcement environments. The focus areas include regulatory gaps in current AI laws, ethical concerns such as data privacy and algorithmic bias, and the societal perception of AI-powered surveillance systems. The background of this study stems from the UAE’s ambition to lead in AI deployment, especially within public security initiatives such as autonomous patrol robots and biometric surveillance systems. However, the lack of clear, AI-specific governance policies in the UAE has created significant legal and ethical challenges, especially when compared with mature frameworks like the EU AI Act or Singapore’s AI Ethics Guidelines. The central research question guiding this study is: How can the UAE develop an AI governance framework for robotic surveillance that ensures national security while upholding privacy rights and ethical standards? Supporting questions explore regulatory deficiencies, ethical risks, public perception, and the formation of practical policy recommendations. Methodologically, the research employs a scenario planning framework within a future foresight approach. No primary data collection was conducted; instead, the study uses only secondary data such as policy reports, academic publications, foresight documents, and case studies from global examples. The analysis involved thematic coding of secondary sources and mapping these themes to four future scenarios of robotic surveillance in the UAE. These scenarios considered legal frameworks, ethical principles, public sentiment, and technology adoption trends to outline plausible policy pathways. Key findings reveal that the UAE’s existing Data Protection Law No. 5 of 2020 provides general privacy guidance but lacks provisions tailored to AI-powered surveillance systems. Ethical risks, especially around mass data collection and algorithmic discrimination, remain largely unregulated. Furthermore, public perception studies in similar regions indicate that trust and transparency are critical to citizen acceptance, yet the UAE lacks localized research in this area. These findings suggest the urgent need for UAE-specific AI governance frameworks that are both adaptive and context-sensitive. The study concludes that a strategic, foresight AI governance model is necessary to prevent misuse, ensure transparency, and build public confidence in robotic surveillance technologies. It also contributes to the broader academic discourse on AI ethics, surveillance governance, and foresight-driven policy design in emerging economies. Practical recommendations include the development of legal frameworks that mirror global best practices while respecting the UAE’s unique socio-political context. This includes the establishment of an independent AI oversight authority, guidelines for ethical AI deployment, transparency audits for surveillance algorithms, and public awareness campaigns to boost trust in AI systems. For future research, scholars should explore experimental studies on UAE citizen attitudes toward surveillance, the effectiveness of AI auditing mechanisms, and comparative impacts of surveillance technologies in different smart cities. Policymakers are encouraged to adopt a flexible, scenario-based approach to technology regulation, allowing the UAE to adapt to rapid innovation while preserving individual freedoms.

Publication Details

Journal
RIT Scholar Works (Rochester Institute of Technology)
Published
2025-04-01
Primary Topic
Magnetic confinement fusion research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Use of Robotic Surveillance in the UAE in 2035: Balancing, Innovation, Regulation, and Privacy

RIT Scholar Works (Rochester Institute of Technology)
Magnetic confinement fusion research
article

The Use of Robotic Surveillance in the UAE in 2035: Balancing, Innovation, Regulation, and Privacy

article en

Abstract

This research explores the future of robotic surveillance in the United Arab Emirates (UAE) by 2035, aiming to balance innovation, regulatory oversight, and privacy protection. It investigates the intersection of national security objectives, ethical AI governance, and public trust within the UAE’s rapidly advancing smart city and law enforcement environments. The focus areas include regulatory gaps in current AI laws, ethical concerns such as data privacy and algorithmic bias, and the societal perception of AI-powered surveillance systems. The background of this study stems from the UAE’s ambition to lead in AI deployment, especially within public security initiatives such as autonomous patrol robots and biometric surveillance systems. However, the lack of clear, AI-specific governance policies in the UAE has created significant legal and ethical challenges, especially when compared with mature frameworks like the EU AI Act or Singapore’s AI Ethics Guidelines. The central research question guiding this study is: How can the UAE develop an AI governance framework for robotic surveillance that ensures national security while upholding privacy rights and ethical standards? Supporting questions explore regulatory deficiencies, ethical risks, public perception, and the formation of practical policy recommendations. Methodologically, the research employs a scenario planning framework within a future foresight approach. No primary data collection was conducted; instead, the study uses only secondary data such as policy reports, academic publications, foresight documents, and case studies from global examples. The analysis involved thematic coding of secondary sources and mapping these themes to four future scenarios of robotic surveillance in the UAE. These scenarios considered legal frameworks, ethical principles, public sentiment, and technology adoption trends to outline plausible policy pathways. Key findings reveal that the UAE’s existing Data Protection Law No. 5 of 2020 provides general privacy guidance but lacks provisions tailored to AI-powered surveillance systems. Ethical risks, especially around mass data collection and algorithmic discrimination, remain largely unregulated. Furthermore, public perception studies in similar regions indicate that trust and transparency are critical to citizen acceptance, yet the UAE lacks localized research in this area. These findings suggest the urgent need for UAE-specific AI governance frameworks that are both adaptive and context-sensitive. The study concludes that a strategic, foresight AI governance model is necessary to prevent misuse, ensure transparency, and build public confidence in robotic surveillance technologies. It also contributes to the broader academic discourse on AI ethics, surveillance governance, and foresight-driven policy design in emerging economies. Practical recommendations include the development of legal frameworks that mirror global best practices while respecting the UAE’s unique socio-political context. This includes the establishment of an independent AI oversight authority, guidelines for ethical AI deployment, transparency audits for surveillance algorithms, and public awareness campaigns to boost trust in AI systems. For future research, scholars should explore experimental studies on UAE citizen attitudes toward surveillance, the effectiveness of AI auditing mechanisms, and comparative impacts of surveillance technologies in different smart cities. Policymakers are encouraged to adopt a flexible, scenario-based approach to technology regulation, allowing the UAE to adapt to rapid innovation while preserving individual freedoms.

RIT Scholar Works (Rochester Institute of Technology)
Peace, Justice and strong institutions
Openalex Percentile: Top 41%
Magnetic confinement fusion research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.