Artificial intelligence in mass surveillance

Introduction

The focus of this will be a look, review and discussion of artificial intelligence been used for mass surveillance across and what could be the benefit and the disadvantages of doing so. It will investigate who is the one creating, supplying, and using this technology as well as explaining exactly what technology is. But before doing those, it will be important to first explain what artificial intelligence is and what mass surveillance is.

Literature review

Artificial intelligence:

Artificial intelligence is not just one single thing, it consists of a variety of technologies like machine learning and cognitive computing. The straightforward definition of artificial intelligence is a machine to sense, comprehend, act, and learn with human-like levels of intelligence. Artificial intelligence is usually classified into two classes.

The first one is artificial narrow intelligence, this artificial intelligence that can only perform one single task then there Is general artificial intelligence. general AI is more like what you see in sci-fi films, where sentient machines emulate human intelligence, thinking strategically, abstractly and creatively, with the ability to handle a range of complex tasks.​ (Accenture, 2022)​

Mass surveillance:

Mass surveillance is the intricate surveillance of an entire or a substantial fraction of a population to monitor that group of citizens. The surveillance is often carried out by local and federal governments or governmental organizations. It involves acquiring, processing, analysing and storing information about the people it is surveying.

What this means is that mass surveillance is essentially the same as monitoring an individual and collects information about them to be able to control that individual’s behaviour but on a mass, scale including large amounts of individuals hence the term “mass” surveillance.​ (Wikipedia, 2022)​

The relation between the two:

When looking at the definition of artificial intelligence it is easy to see why it will be used for something like mass surveillance. Because the monitoring of individuals behaviours is something that is already been done with technology. In fact, the biggest use of technology today is monitoring individual’s online activities for various aims.

But more precisely when it comes to mass surveillance, although there are some private companies engaging in it mostly as a supplier, mass surveillance is used for public concerns meaning it is not something as of interest to private organization as it is to governments. The fact that artificial can learn and comprehend with human like capacity means that it can become very performant at doing one thing precisely.

Therefore, something like processing, analysing and storing specific types of information, which is what mass surveillance does, will be done far more effectively if it has been done by AI. Since this is a fully logical task, using artificial intelligence for it will deliver far better results than a human.

Main discussion and argument

Reasons and benefits of using AI surveillance

Home security:

Some of the issues with how security could be individuals having their keys lost, forgotten or stolen. Another factor about home security is human limitation, pacifically when it comes to the night. human vision ability tent to lower during such time. And AI is used in the form of smart locks connected to devices allowing for a safer means of securing your home. And AI powered night vision to be able to view clearly at night for any potential threat to home security.

However, it will not only be about security outside of the individual’s living space but also inside of the living space. One aspect of this is when it comes to little children. Because the inside of the house is full of various types of objects from small to large, soft to hard or even sharp object there is a possibility that children moving around the house could lead to them encountering those objects and the situation could result in a domestic incident. AI in this case will be used to create virtual boundary lines to detect any potential contact between children and objects that could be potentially harmful to them.​ (Giwa-Osagie, 2022)​

Expected threat from large event:

It has become an essential function for security teams to protect the public by preventing weapons and other prohibited items from being brought into the spaces where people gather for entertainment, learning, worship, and more. Security measures in places such as stadiums, outdoor venues, schools, religious facilities, convention centres, corporate campuses, and government buildings need to be efficient to safely process large volumes of people.

Traditional methods of screening such as walk-through and handheld metal detectors have been in use for decades, and while historically, they have been effective for the detection of metal weapons, they are also very prone to high false alarm rates. Additionally, they are not particularly efficient, with limited throughput and the need for patrons to remove certain clothing such as belts or to empty items from their pockets such as keys and cell phones. And even with these steps, it is often necessary to include secondary screening measures such as pat downs.

For event operators, this process can negatively impact the experience of the guests by causing delays, hassle, and unnecessary secondary screening, which can also impact the business’s bottom line by decreasing the time that the guests must enjoy the venue’s potential food, drink and merchandise offerings.

Technology advancements for data, artificial intelligence, and computing provide an opportunity for security teams to make screening both more effective and efficient. This is done by using AI and deep learning algorithms, combined with large volumes of data acquired through three-dimensional imaging, along with advanced computing power, to improve the detection of concealed weapons.

3D images can be acquired using technologies such as low-power radar that bounces off a person’s body as the person walks past sensors at a security checkpoint. This means that it is possible to have patrons move through security more quickly, with less contact, fewer pat downs, and lower false alarm rates.​ (Bhardwaj, 2021)​

Border control:

Petty stealing, international terrorism, smuggling and sea piracy are all occasional offences occurring at international borders. In most cases, human personnel are used for taking measures against these threats from happening. The result often tends to be these offences been prevented. However, there are still cases in which human efficiency fails in terms of prevention of these offences. Therefore, initiatives to make the prevention rates of these crimes higher, solutions like integrating artificial intelligence. Instead have started to be considered.

The security control at the border does not just relate to individuals but also to items. Both individuals and illicit goods are smuggled through borders. This may sound like a minor difference, however, there are different approaches when it comes to preventing the smuggling of goods and different approaches when it comes to preventing the smuggling of people. The reality is that good can come in many different forms meaning that they can be harder to trace and for these reasons some methods that are used at borders patrol against illegal good smuggling varies greatly.

One common method is the use of sniffing dogs. This is mostly common, especially in airports. However, due to all the measures been taken at borders, those offences still carry on occurring all the time. One reason for his is the efficiency of human border control. And for this reason, the main aim has been to increase efficiency when it comes to border control. These have also been adopted not only at borders but at any places where these crimes are likely to take place such as in airports. Artificial intelligence has been used for both surveillance purposes at borders and for facial recognition technology at airports. AI border security camera can be used to detect sea piracy from very far away giving the border patrol enough time to act​ (Dumbrava, 2021)​

Offshore rig threat detection:

Globally there are twelve thousand offshore oil rigs. Meanwhile, there are an estimated six to twelve oil rigs fatalities each year and about 220 human injuries. This means that security and safety on oil rigs are a huge concern. Major incidents such as oil spills, explosions, heavy objects are all offshore rigs threats. Many of these incidents have huge consequences not just for the human working on them but also for the companies that own and operate them. For example, the BP oil spill in the Gulf of Mexico that took place in 2010 cost the company a grand total of 63.4 billion dollars in both legal fees and clean up cost. This was alongside eleven people that dies due to the accident.

The main cause of this incident was a failure of cement at the rig’s well which led to toxic pollution in both the water in the form of an oil spill which polluted the surrounding water and killed multiple marine life and air pollution as large amounts of smoke was released into the air. The risk of such incidents happening is extremely likely worldwide. Therefore, there are measures taken by the oil companies. One of those is to hire oil rig consultants or drilling consultants as more commonly known. Most oil rigs have people that oversee the daily operation of the rig. And they play a role in ensuring the drilling and general operation of the rig is done efficiently and safely.

Oil companies hire those people to make sure that factors such as safety concerns are well met. However, there are several downsides when it comes to hiring oil rig consultants, which oil companies must deal with. One of those is availability. It takes around twenty to thirty years of experience in the oil sector to become an oil rig consultant. What these means effectively is that the number of oil rig consultants available is very low. And consequently, their hiring costs a lot. These two factors have led the oil sector to look for several alternatives. In March of 2019, two technology companies, Aker solution and Spark cognition partnered together to create an AI that will be used to make offshore oil and gas drilling safer

It works by monitoring topside and subsea installations for more than 30 offshore structures. The AI uses machine learning to Analyse sensor data which allows the company to identify suboptimal operations and impending failure before they occur. These will be more beneficial to the oil companies as their workers will be protected and the rigs will be just as safe for far less of the cost of hiring individuals to do the work.​ (Ali, 2019)​

Downsides and disadvantages of using AI surveillance

Facial recognition errors:

Face recognition systems can be fooled if an attacker presents a photo, a video with a certain person to the targeted camera: these are the most common types of attacks here due to the low cost and simplicity of the method. There are other possible attack vectors on surveillance systems. Smart surveillance cameras can overlook trespassers with the help of anti-detection methods. These attacks are performed by wearing special glasses, face masks and other accessories. Facial recognition cameras can misidentify wanted fugitives if malicious actors exploit deceptive masks or other tools. Audio surveillance systems can misclassify suspicious conversation in case of misleading keywords.​ (adverisa.ai, 2019)​

Privacy issue:

Reference: www.helpnetsecurity.com

Many organizations are looking for AI to make sense of tremendous amounts of unstructured data that has been collected about people, transactions, systems, and social connections. It is estimated that over 90% of all data is unstructured and not usable by normal systems. AI holds the potential to find patterns, connections, and derive the value of such telemetry and raw data.

This could provide great beneficial insights into people’s needs, desires, opportunities, and alerts when they are subject to unfair practices. But at the same time, it can aggregate data in ways that build stronger profiles of individuals. Such systems can make connections about very private or personal aspects of people’s lives that those individuals never authorized or want to be known. It could be a confidential relationship, a medical condition, personal fears, economic status, or something they are privately working through. In much of the world, privacy is recognized as an important human right, necessary for people to thrive.

Video surveillance systems are a major concern, with AI now being able to identify and track people from networks of connected camera systems. This will potentially allow governments, who install many cameras to monitor the public, to track where every person is at any time, what they are doing, and whom they are meeting with. I expect such technology will also evolve to process microphone information or effectively read lips to determine what individuals are saying to each other. Such implementations will greatly undermine privacy, free speech, and in some countries could be used to persecute individuals for simply talking about certain topics.

Government power:

Countries like the U.S. and China have deployed millions of cameras and are leading the AI-based surveillance market. According to the Artificial Intelligence Global Surveillance index, at least 75 out of 176 countries globally are actively using AI-based surveillance technologies. China is a significant player in AI-based surveillance, supplying AI-based technologies to at least 60 countries.

Autocratic or semi autocratic countries like Saudi Arabia, China and Russia are exploiting AI-based technologies for mass surveillance purposes. At the same time, liberal governments are dismissing the idea of using it on the grounds of protecting privacy. The European Commission aims to strictly control AI to reduce risk, including a ban on AI programs which humans cannot understand also known. The main objective is to develop the trust of the public and not cause chaos. AI appears to work in favour of humanity if used in ethical terms.

The fundamental question that arises amid global privacy crises is whether these advancements are counterintuitive to humans. Globally, countries are working on the ethical norms of surveillance. As AI technology get more powerful each year, it will become more essential to regulate it.​ (Nouri, 2020)​

​​References

​​Anon., 12 March 2022. Mass surveillance. [Online]

Available at: https://en.wikipedia.org/wiki/Mass_surveillance

​Anon., 2022. artificial intelligence. [Online]

Available at: https://www.accenture.com

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Available at: https://www.accenture.com

​Anon., OCTOBER 29, 2021. Artificial Intelligence. [Online]

Available at: https://www.accenture.com/gb-en/insights/artificial-intelligence-summary-index