The progressive implementation of this technology in the internal administration of companies, allows to significantly reduce the rate of accidents and occupational diseases, as well as exponentially increase competitiveness and strategic positioning.
During the last few weeks, public opinion has been shocked by the level of “perfection” of the texts written by the Chat GPT app.
A stunning progress that forced to extreme control methods in universities and high schools, in order to prevent students from using this digital tool to falsify their own work.
However, beyond the malicious uses of point technologies, what would a world look like where a “simple” work safety software stops by itself, and without direct human intervention, the operation of an entire company, because it “knows” that a fatal accident will occur within the production line?
This scenario, which seems to be taken from a science fiction movie, is no longer so far from reality, precisely thanks to the advancement of industrial digital transformation.
One of the most concrete examples of this new reality is the increasingly relevant contribution of Artificial Intelligence (AI), to implement increasingly efficient and accurate risk management and control systems.
A decisive characteristic, which not only translates into greater productivity, but also into a significant improvement in the health and physical integrity of workers.
What is Artificial Intelligence?
From a technical point of view, Artificial Intelligence is defined as the combination of algorithms specifically developed to create machines or computer systems with the same cognitive, analytical, and problem-solving capabilities of human beings.
In other words, Artificial Intelligence gives machines the ability to learn to make decisions based on the agile, timely and efficient collection, analysis and classification of large amounts of data.
Although for most people this technology still seems distant and somewhat mysterious, its presence in the work and productive environment of many companies dates back almost a decade.
Not only within the field of Information and Communication Technologies, IT, but also in other productive, industrial and service sectors.
This is because Artificial Intelligence has the potential to exponentially boost a company’s competitiveness and market positioning. In other words, it allows its managers to make more efficient decisions in line with the constant changes that an increasingly agile, dynamic and competitive market is experiencing today.
Why is AI so important to business success?
Most of the known examples of AI applications – from computers that play chess to software that writes essays and controls sophisticated autonomous vehicles – rely on deep learning and natural language processing.
Both technologies allow computers to be “trained” to perform specific tasks, based on the dynamic processing of large amounts of data and the recognition of certain patterns among this data.
For example, a food and beverage company can use Artificial Intelligence software to analyze the evolution of population consumption trends, based on the comparison of data collected within a representative sample.
By applying a deep learning model, this AI could, for example, compare the consumption trends of the last 30 years and draw a sales projection in the medium and long term, with a high percentage of certainty.
Consequently, this would allow the executive management of the company to design new positioning strategies based on the launch of new products, the restructuring of its marketing campaigns, or a new segmentation of its target audiences, among many other initiatives.
As a result, the company could lower costs, optimize its production, retain its customers and conquer new segments. That is, it would be much more efficient, successful and competitive.
Although recent advances in AI have only been limited to very specific tasks, such as processing large volumes of information, optimizing the development of new products (in multiple business areas) or foreseeing future scenarios, the impact of its contribution is already being felt in other sensitive areas for companies such as the following:
- Boost efficiency through the automation of processes.
- Improve the agility of response to customer requirements.
- Adapt products and services to changes in scenario or trends.
- Analyze customer behavior to improve decision making.
- Discover and exploit new business opportunities.
Artificial Intelligence as a pillar of Health and Safety at Work
All this set of concrete benefits also positions Artificial Intelligence as a decisive tool to significantly improve the safety and health of workers.
This advantage derives directly from the ability of AI to learn from the data obtained. In other words, the more data is collected, the more precise and accurate are the conclusions obtained.
If this is applied directly to the field of Health and Safety at Work, we can obtain the following advantages:
- Improvement of activities surveillance and monitoring tasks.
- Analyze more accurately the different risk scenarios.
- Optimize the ability to anticipate crises or contingencies.
- Eliminate risk situations.
- Reduce the rate of occupational accidents and illnesses in the personnel.
- Maximize the performance of company’s assets.
In this way, thanks to its great capacity to analyze data and cross variables, AI can help to correlate the nature of the various productive or industrial activities (such as mining, construction, logging, transport and logistics, among others), with the different types of incidents or accidents that occur in them.
This efficiency provides, without a doubt, decisive support to improve risk analysis within companies, and thus make decisions that protect the integrity of workers and even save lives (such as the seen example of software that paralyzes production, because it “knows” that an accident will happen).
Furthermore, experts estimate that AI will also allow, in the short term, companies to have all their Occupational Health and Safety information consolidated in “data lakes”.
These lakes, structured from deep learning, will contain a wide variety of valuable information, both for the general operational continuity of the company, and for the implementation of new security programs.
This information will highlight aspects such as:
- Systems for recording and reporting accidents at work and occupational diseases.
- Measurement guidelines and validation of preventive tasks.
- Scheduling of equipment and machinery maintenance processes.
- Planning and implementation of agile security protocols adapted to different realities within the company (for example, office tasks, operational tasks and field work).
Intelligent software will then be able to organize all this information in a single repository and filter it to determine which situations are efficient and which involve the risk of accidents.
In this way, it will be possible to carry out a better analysis of the progress achieved in personal safety and health, which is essential to determine priorities and improve the design of the respective prevention strategies.
And it’s not just a theoretical assumption. In fact, a recent report by the Australian organization Safe Work estimates that the widespread adoption of automated systems at work (including AI and robotics) will reduce workplace accidents by approximately 11% before the end of this decade.
How can AI be used in occupational health and safety plans?
As we have seen, AI platforms operate on the basis of constantly collecting huge volumes of data.
In a company, this data collection can be done through the application of mobile research forms, the use of sensors in machinery and/or the installation of cameras at critical points. All of these systems can operate simultaneously and send the information obtained to a “computer brain” loaded with AI software.
Through specific algorithms that analyze the information and compare patterns, this program could detect and identify, for example, “risky actions” within the behavior of workers.
These actions can range from the misuse of Personal Protection Elements (PPE), to the incorrect operation of machinery.
If the system detects any risk situation that could lead to incidents or accidents, it will send an alert in real time to the company’s security managers, who can take the respective corrective actions.
Simultaneously, all the data collected during this process will be saved in the company’s dashboard, which allows for better future decisions, reducing operational costs and preventing both accidents and their consequences.
However, for the application of these new technologies to be fully successful, it is also essential to promote a profound cultural change within companies.
Only in this way workers will understand and internalize the advantages of these new technologies, which in turn will allow them to count on their support to work together to improve health and safety in work environments.
Concrete examples of AI in Occupational Health and Safety
Currently, the technology market offers various AI platforms and solutions that are used for tasks such as:
- Monitor the use of Personal Protective Equipment.
- Detect fire or chemical emergencies.
- Alert the presence of hazardous materials.
- Identify dangerous behaviors of workers.
However, AI is also being used to automate dangerous tasks (using robots and drones) such as welding, handling explosives, transporting material in mining sites and working at heights, among others.
Likewise, AI helps to improve safety in transport and in the management of hazardous waste.
In turn, in the area of people management, AI is used, for example, to analyze historical accident rates, detect patterns and alert both workers and supervisors about possible risks associated with specific behaviors.
AI systems are also used to monitor variables such as:
- Worker fatigue
- Stress level and concentration
- Abnormal behaviors that indicate health problems or security risks.
In addition to increasing safety, AI also helps improve worker health. For example, it is currently used to detect early symptoms of occupational diseases, which makes it possible to provide timely medical advice.
AI systems are also used to detect patterns indicative of work-related injuries, illnesses or mental health problems.
Although Artificial Intelligence provides multiple benefits for occupational health and safety, it also presents challenges and ethical complexities that need to be addressed.
One of these challenges is ensuring the protection of workers’ personal data, since AI systems can collect large amounts of information, which can pose occasional privacy and security issues for both companies and individuals.
Likewise, it is also very important to verify that Artificial Intelligence does not generate conflicts of bias and discrimination during automated decision making.
For example, that their attribution of personal errors is not understood as prejudiced acts against certain social groups.