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Digital EHS
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Maxime Ouellet, ing.

Democratizing Artificial Intelligence in EHS

If we believe everything that’s in the media, artificial intelligence poses the next big threat to humanity. Evil electronic brains and rebellious robots frequently appear in our collective imagination and on our screens, reducing the contribution of technology to a distant and vaguely problematic danger. Although ethical and social issues must evolve rapidly in order to keep up with the pace of technological advances, AI should not be confined to this vision straight out of science fiction, but rather be seen as a tool that has a place in the development of various world economic spheres. 
 
The main players in the marketing sector have clearly understood the possibilities of this digital transformation. If the ethical side is sometimes put aside, investors in this field of work have nevertheless managed to convert information into real value. By finding answers to such simple questions as what your potential customer is doing right now and where he is, experts got their hands on information that is now selling at a high price. If the concept seems easy—create value based on questions and then sell them to the highest bidder—the complexity of the system needed to answer those questions is harder than it seems.  


 
Are Artificial Intelligence and Sustainable Development compatible? 


 
While current technology has evolved significantly to simplify data collection, it’s also required to process all this data in real time while developing an algorithm for the system to be able to extract diamonds from these mines of knowledge. This is where artificial intelligence comes into play. 
 
Besides this enthusiasm for new technological solutions, investors, big and small, are also increasingly looking for responsible investments. Environment is instinctively associated with sustainable development, but health, worker safety, product quality, supply chain impact and community considerations are also unavoidable components of social driving choices. Considering customer demands and market pressure for organizations to perform when it comes to sustainable development, combined with the organizational agility that the digital transformation provides to business leaders, EHS experts have no choice but to develop a data culture and to familiarize themselves with AI tools and techniques, catalysts in extracting value from all this data. 
 
So what are these simple questions that are relevant to sustainable development? Once again, we need to look to marketing experts for inspiration: where are the workers, what are they doing and at what moment, are the suppliers meeting their certification commitments, what is the impact of my company’s raw materials and the transformation process, etc. 
 
Once the questions that are critical to the functioning of your business have been identified, they must, of course, be answered. Many companies have astronomical amounts of data from the ’80s to the 2000s, blown into Microsoft Excel and Word files, forgotten and unused in a corner. Usually, the problem is not about finding the data, but rather organizing it in a system while extracting useful information that will add value. 
 

The Sooner, The Better 

 
It is in your best interest to start as quickly as possible. The more information you gather, the more material you will have to give to your artificial intelligence system, as it will learn to differentiate patterns and trends allowing your system to acquire knowledge. The industry is full of inspiring examples, including the history of this small manufacturing company that asked its employees five years ago to photograph different stages of the assembly line. The objective was to build up a bank of photos to refer to in case of assembly line related defaults and to improve the product’s quality in general. Years later, there are now enough photos to visually compare products and detect defects using an image recognition algorithm. The company finally has the ability to systematically analyze quality through this lessonThere is a lot of value extracting data without being able to predict its purpose. The important thing is to make assumptions and to see the potential of this information in the long term. 


Find the Ideal Algorithm 

 
The biggest challenge lies in structuring the information. As soon as the data begins to pile up, the feeling of helplessness gains ground among companies. Fortunately, thanks to the analysis system models derived from artificial intelligence, it is now possible to attempt a first pick among this clutter to make it all intelligible and above all, useful. The industry has never been so advanced in data processing. It is now a necessity to identify interesting data for short- and medium-term use, as well as technology tools that represent an appropriate minimum investment that will ultimately create long-term value. 
 
Thanks to artificial intelligence, restructuring the information is facilitatedAll it takes is choosing the right technological partner. A technological partner will allow the implementation of supervised learning, that is to say the creation of a database supervised by humans, thus allowing the system to improve its data analysis to perfection, so that the whole is reproduced at an unsupervised data level. To do this, however, there is no magic solution other than investing in the culture of data, the latter now being the new black gold and an opportunity to seize as quickly as possible. 
 
In Canada, the phenomenon is gaining momentum, mainly thanks to superclusters specializing in AI. CONFORMiT, well aware of the potential of this specialization, is more than proud of its association with Wear It Smart and SCALE.AI, two partners connected to the challenges of sustainable development, data capture and artificial intelligence.