The complete guide to AI safety in the workplace

How can AI help protecting your workforce? In this guide, we cover all aspects of workplace safety, and provide insights as to how Health and Safety managers can rely on AI and computer vision to ensure every worker can operate safely.

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November 3, 2022
5 mins


Section 1: Introduction to AI Safety

Workplace safety is an important consideration for modern businesses. According to a report by the National Safety Council, the number of preventable work deaths in 2020 was 4,113. 

This was a 10% decrease from the prior year, and the Council attributed it largely to the economic disruption caused by the global pandemic. The highest number of preventable work injuries were in the construction sector, which further outlines the importance of instituting safety measures in the workplace. 

Depending upon the industry and the nature of work, there can be hundreds of hazards that pose varying levels of risk, including: 

  • Harmful chemicals
  • Physical hazards like falling objects 
  • Ergonomic hazards
  • Noxious gases
  • Sharp objects

As you can imagine, this isn’t an exhaustive list. In order to improve workplace safety, many companies are now using artificial intelligence to their advantage. 

The popularity of AI safety is largely fueled by significant advances in deep learning algorithms, which are now capable of “learning” by simply processing large volumes of data. 

Previously, companies had to hire safety officers to ensure that workers on site took safety standards seriously. These safety officers would monitor the use of PPE (personal protective equipment) and alert employees to different dangers in the environment. 

However, human error is a very real possibility. It’s also quite difficult for organizations to employ safety officers to carefully monitor hundreds of workers across a larger area, such as a construction site.

That’s where AI safety comes in. AI safety tools are capable of processing information much quicker, and can be used to identify risks or hazards in the workplace

Section 2: AI Safety – A Technical Overview 

Artificial intelligence, in its very basic form, is any algorithm or machine that can mimic the workings of the human brain. It is the use of algorithms and processes to simulate human intelligence in a machine. 

However, this can be considered an abstract definition. Practically, AI is considered an ability of a machine to perform a simple cognitive function: learning. AI machines can be fed large amounts of data, and by processing it, these machines learn to recognize patterns. 

AI safety tools use deep learning, a subset of machine learning, to analyze hundreds of thousands of images. AI safety tools work by breaking the images into millions of pixels, and then analyzing subtle differences between each. 

Over time, they are able to detect various objects. For instance, an AI powered workplace safety tool can be “trained” to detect the use of hard hats on a construction site. 

They can be connected to a company’s existing CCTV network, thus offering real-time monitoring. AI safety tools rely on the use of technologies such as computer vision and video content analysis to detect PPE usage in real-time. 

They can then send alerts, including notifications or even a text message to employees, or the department, about safety protocols. While all of this happens within seconds, there’s a complex web of technologies that make it happen. 

Here are some key technologies that play an important role in AI safety.

Computer Vision

Computer vision involves the use of artificial intelligence to enable systems and computers to extract critical information from digital imagery and videos, much like how a human sees. 

Machines that use computer vision can be trained to detect objects with the help of a camera. Once a data source is connected, systems can “learn” by inspecting different images. 

They rely on complex technologies, including convolutional neural networks, which allow machines to analyze images. Every pixel is labelled and tagged before the system starts running convolutions to determine if its predictions are accurate. 

In the beginning, accuracy is generally low, as the system is only capable of identifying simple shapes and prominent outlines. However, as it continues to evaluate new images, it begins to get more and more accurate, until it’s capable of recognizing objects with extreme precision.

Convolutional Neural Networks

A convolutional neural network is an algorithm used for deep learning. It takes an image, assigns specific biases to the objects within, and then learns to distinguish between different input images. 

The name is derived from the way neurons are connected within the brain, as the architecture of a convolutional neural network follows a similar architecture. 

Convolutional neural networks simply capture temporal and spatial dependencies from an image by applying different filters, allowing them to identify things that might not be obvious to the human eye. 

Over time, convolutional neural networks become much faster and more accurate than the human eye, as they can be deployed in larger areas and can focus on many objects at once.

Video Content Analysis

The footage captured by a conventional CCTV camera can be processed through video content analysis. With the help of VCA, companies can implement specific safety rules, such as identifying if anyone crosses into restricted areas. 

Objects in the footage can be detected and tracked through video content analysis, as it can identify spatial and temporal events in real-time. VCA can also be used for face recognition and object discovery, classification, and segmentation. 

Video content analysis allows companies to gather important analytical information about work processes, and it can help safety personnel identify patterns they hadn’t previously focused on. 

Section 3: The Benefits of Using AI to Improve Safety in the Workplace 

Many companies are already using AI safety tools to make workplaces safer and to reduce the burden on their safety personnel, while also being compliant with regulations. 

Here are some of the many benefits that AI safety tools offer. 

1. Automation

Arguably the biggest benefit of using AI tools in the workplace is automation. This doesn’t just mean automating high-risk tasks which pose a greater threat of injury, but many others. 

For instance, AI safety tools can be used to monitor all workers and ensure that they wear protective equipment. AI safety tools can also be used to prevent people from walking into an exclusion zone, by observing behaviour and sending alerts when someone approaches within a defined limit. 

2. Reduced Risk of Human Error

AI safety systems get more accurate and smarter as more and more information is fed into the system. There’s a risk that a human may miss a minor detail, but AI safety systems aren’t prone to human error. 

This means that your workplace will only get safer as time passes and the system continues to process and analyse new data.

3. Improved Equipment Control 

Safety personnel can define specific rules for taking appropriate steps before using dangerous machinery. Equipment control can ensure that only specific employees with proper training are allowed to use certain machines. 

More importantly, they can be configured to operate based on certain rules, such as if a qualified individual is present for supervision. This ultimately helps improve safety outcomes and prevents any mishaps.

4. Improved Employee Monitoring

Employers have a responsibility to ensure that they regularly train and educate employees about the importance of using proper safety equipment. However, if these standards aren’t enforced, there’s a risk that employees may not take it seriously. 

Safety officers in fast-moving environments, such as a construction site, can only do so much. It’s virtually impossible for them to monitor every employee on the site without causing disruptions. 

This also increases the risk of human error, as a safety officer may miss key details. With AI systems, this isn’t an issue. 

AI safety systems simply connect with existing CCTV networks. They can process multiple streams of data in real-time, and send alerts whenever rules are breached. 

AI safety systems can be used to monitor:

  • Employee location 
  • Use of PPE
  • Presence of environmental hazards
  • Exclusion zones
  • Fatigue monitoring

5. Improved Decision Making

AI safety systems help break down complex data into easily understandable insights. They empower safety teams with the information that they require to make key decisions. 

Companies don’t need to bring on a data scientist to understand important information. AI safety systems highlight specific changers and allow safety managers to isolate trends that could dictate the company’s safety guidelines. 

It offers an unparalleled insight into the level of risk in the workplace, allowing EHS (environment, health, and safety) teams to make decisions based on quantifiable data and then analyze their outcomes. 

This also allows companies to conduct more effective safety audits, including using video evidence to determine specific trends and patterns. Over time, this information can help businesses determine how safety performance has evolved in the company. 

Section 4: AI Safety – The Risks

While AI safety offers many advantages, it’s also equally important for companies to analyze the downsides and make sure they mitigate the risks. 

These are sophisticated systems, and it’s important for employers to ensure they understand the risks. Here are three main areas of concern.

1. Human Controlled with Benign Intent

Human-controlled AIs can be configured for specific purposes, such as detecting the use of PPE in the workplace. AI systems with benign intent are primarily used for supervision. 

Such AI systems are used primarily for evaluating safety performance, and the data gathered can be used to improve decision-making.  These can be further divided into:

  • Non-robust: This is a possibility if the AI system works well on test data, but there’s a significant difference in performance on other data sets. 
  • Privacy violating: AI systems must be designed to ensure that they do not violate the privacy of stakeholders, including exposing any private or identifying information.
  • Biased: The risk of biases is possible, where the AI system exhibits bias towards specific objects.
  • Inability to explain: The algorithm should be easy to interpret, with defined rules that govern its performance.

2. Autonomous Learning, Benign Intent

AI safety tools are intelligent and autonomous, and they learn as more data is fed into the system. It’s often difficult to determine how such systems will respond in practice, especially if a supervisor isn’t present. 

In certain cases, an interrupting agent may affect the ability of the system to be able to detect objects. It’s often difficult to predict how the system might respond in dynamic environments.

There’s also the risk of the system being hacked and tampered with, affecting its ability to perform tasks.  

3. Human Controlled, Malicious Intent

AI can be used for malicious purposes, which is why it’s important for companies to take appropriate steps for data safety and security. Policies must be instituted to ensure that the data gathered is not misused.

Malicious intent, for instance, mass surveillance, does pose a risk as it can be misused in many ways. It’s important to devise specific governance policies and for companies to take steps to prevent this. 

Section 5: How to Integrate Artificial Intelligence in the Workplace to Improve Safety

Companies have various options to integrate artificial intelligence in their workplaces. For instance, they can consider the use of IoT (Internet of Things), which deploy micro-sensors to monitor machines, production lines, and even employees.

However, this requires a significant upfront investment, and may cause disruptions in work environments. In certain cases, workplaces might have to be adapted before these sensors can be fully deployed. 

Instead, the best way to integrate AI into workplace safety is to connect an AI safety solution with your existing CCTV infrastructure. A video processing box can be connected to the feed, allowing for simple plug and play usage. 

This ensures secure processing on premises, allowing companies to take important steps to ensure the safety and security of the data. Once integrated, companies can define specific safety rules to start monitoring. 

Section 6: The Best AI Safety Solution

Protex AI is a workplace safety solution that leverages the power of artificial intelligence to help EHS teams make effective safety decisions. 

It connects seamlessly with all modern camera systems, and can be customised based on your requirements, letting you define risk in the workplace. 

It’s plug and play nature means that it can easily work with CCTV networks big or small. Protex AI empowers EHS teams by providing them important insights about safety performance. 

Safety events or rule breaches are recorded, tagged, and stored for review by teams, offering them evidence-based insights about the performance of safety protocols. 

It auto-generates safety reports, and can automatically tag stakeholders or specific team members. The storyboard functionality also allows EHS teams to create automated email workflows, add documents, or even record commentary to brainstorm and implement corrective actions. 

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