Artificial intelligence (AI), its utilization, and its future impacts have been widely discussed in recent years. However, towards the end of 2022 and especially in the beginning of 2023, this became tangible to all of us through new platforms, with ChatGPT being perhaps the most prominent. We have marveled at AI-written essays, recommended LinkedIn posts, the construction of various legal documents, as well as code review and optimization. For some, AI has quickly become a daily tool that significantly enhances operations.
Machine vision breaks down and streamlines processes efficiently
have also implemented solutions based on machine vision, for example. One of the solutions we offer to our customers is Chemical registry designed to support and improve our customers’ chemical safety. An important part of this solution is the availability of up-to-date safety data sheets (SDS) in the chemical registry.
However, the chemical registry does not only contain SDSs in PDF format, but the information has also been broke down within the system into quick guides, hazard statements, and hazard icons, among others. Machine vision is utilized at Kiwa Impact for this breakdown process. Through machine vision, we have significantly streamlined our process to provide our customers with better, faster, and higher-quality service. The information processed by machine vision also serves as a basis for chemical risk assessments, labels, and a chemical inventory that can be conveniently extracted from the system for regulatory purposes.
Does AI then take away our jobs?
In my opinion, it does not take away our jobs, but it can significantly support us in achieving more efficient operations. We can directly engage in decision-making and focus on corrective and developmental actions. In other words, we can better utilize our time for genuinely productive and impactful work.
Regarding the future, I see AI as a significant part of safety management, for example. AI is highly capable of handling large amounts of data and identifying correlations between different pieces of information. What if AI could search for correlations in our safety data, inform decision-makers about how active participation in safety sessions, for instance, correlates with lower incident rates, and even highlight teams where participation in safety sessions has been declining, thus indicating a higher likelihood of accidents occurring? I strongly believe in this direction, and at Kiwa Impact, we want to be involved in promoting such developments.
Erkki Mäkelä
Head of Business Unit, Digital Services
