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Mapped: The Top Surveillance Cities Worldwide

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The Top Surveillance Cities Worldwide

Since the world’s first CCTV camera was installed in Germany in 1942, the number of surveillance cameras around the world has grown immensely. In fact, it only took us 79 years to go from one camera to nearly one billion of these devices.

In the above interactive graphic, Surfshark maps out how prevalent CCTV surveillance cameras are in the world’s 130 most populous cities.

Big Brother is Watching

So how many of us are being watched? China and India are the countries with the highest densities of CCTV surveillance cameras in urban areas. Chennai, India has 657 cameras per square kilometer, making it the number one city in the world in terms of surveillance.

Here’s a closer look at the world’s top 10 cities by CCTV density.

RankCityCCTVs per square kmCCTVs per 1,000 people
#1🇮🇳 Chennai, India65725.5
#2🇮🇳 Hyderabad, India48030.0
#3🇨🇳 Harbin, China41139.1
#4🇬🇧 London, England39967.5
#5🇨🇳 Xiamen, China38540.3
#6🇨🇳 Chengdu, China35033.9
#7🇨🇳 Taiyuan, China319119.6
#8🇮🇳 Delhi, India28914.2
#9🇨🇳 Kunming, China28145.0
#10🇨🇳 Beijing, China27856.2

London is the only non-Asian city to crack the list with 399 CCTV cameras per square kilometer.

Beijing ranks in tenth place. The Chinese capital has the highest number of CCTV cameras in total, at just over 1.1 million installed in the city.

Although CCTV cameras have become extremely prevalent in cities around the world, this does not mean these cameras are seeing and recognizing our every move. In most instances, cameras are in a fixed position—and some of the more invasive aspects of CCTV, like accompanying facial recognition technology, are not universal yet.

The Need for CCTV

The ubiquity of surveillance cameras can be unnerving to some, as they represent diminishing privacy. However, there are also those that feel the presence of cameras creates added safety.

While governments like China’s claim that having high amounts of surveillance cameras helps reduce crime, the actual data gets messy. For example, the Chinese city of Taiyuan has roughly 120 cameras per every thousand people and yet the city has a higher crime index than most.

Freedom vs. Security

As surveillance networks become more sophisticated and granular, there is increasing concern about breaches to personal freedoms.

China is doubling down with surveillance in its cities by pioneering the usage and exportation of facial recognition technology. This technology is integral to China’s proposed social points system. With a database of 1.3 billion pictures that can be matched to a face on a CCTV camera in seconds, troublemaking citizens can easily be identified.

In India, on the other hand, the amount of cameras can be attributed to mass urbanization, rising crime, and scarcity of urban resources. Overall, there is a rising middle class that wishes to protect itself with the use of CCTV cameras.

As we close in on one billion CCTV surveillance cameras globally by the end of 2021, we will undoubtedly continue to be monitored well into the future.

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Charted: The Jobs Most Impacted by AI

We visualized the results of an analysis by the World Economic Forum, which uncovered the jobs most impacted by AI.

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Charted: The Jobs Most Impacted by AI

This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.

Large language models (LLMs) and other generative AI tools haven’t been around for very long, but they’re expected to have far-reaching impacts on the way people do their jobs. With this in mind, researchers have already begun studying the potential impacts of this transformative technology.

In this graphic, we’ve visualized the results of a World Economic Forum report, which estimated how different job departments will be exposed to AI disruption.

Data and Methodology

To identify the job departments most impacted by AI, researchers assessed over 19,000 occupational tasks (e.g. reading documents) to determine if they relied on language. If a task was deemed language-based, it was then determined how much human involvement was needed to complete that task.

With this analysis, researchers were then able to estimate how AI would impact different occupational groups.

DepartmentLarge impact (%)Small impact (%)No impact (%)
IT73261
Finance70219
Customer Sales671617
Operations651817
HR57412
Marketing56413
Legal46504
Supply Chain431839

In our graphic, large impact refers to tasks that will be fully automated or significantly altered by AI technologies. Small impact refers to tasks that have a lesser potential for disruption.

Where AI will make the biggest impact

Jobs in information technology (IT) and finance have the highest share of tasks expected to be largely impacted by AI.

Within IT, tasks that are expected to be automated include software quality assurance and customer support. On the finance side, researchers believe that AI could be significantly useful for bookkeeping, accounting, and auditing.

Still interested in AI? Check out this graphic which ranked the most commonly used AI tools in 2023.

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