Artificial intelligence (AI) has been piquing the interest of researchers for more than fifty years, and the significant increase in computing power, combined with the phenomenal quantity of data available, has resulted in rapidly accelerating progress. Although there are still many questions regarding the issues arising from the growing role that AI is playing in our lives, this technology has tremendous potential for increasing our efficiency in a wide range of fields, and especially in engineering.
We are all familiar with certain AI applications, including music-streaming platforms, which fine-tune their music recommendations based on our tastes, and the customer service systems at some companies, which use robotic agents to help us find solutions to our technical problems.
Simply defined, AI is a [translation] set of techniques that allow machines to perform tasks and solve problems normally reserved for humans.1 This means that, by following a predetermined program, the machine processes inputs and generates a response in accordance with a logical sequence. This process can be extended thanks to machine learning techniques, which allow the AI to learn by establishing correlations among the data and adapting its responses to an infinite number of scenarios. Subsequently, the machine can identify the best decision to be taken based on its past observations, even when dealing with a situation it has not previously encountered. It must be understood that the quality and quantity of data submitted to the machine affects the results that are obtained.
AI in engineering
There are already numerous applications of AI in the field of engineering: infrastructure monitoring, quality control, mobility (self-driving cars, drones), discovering new molecules, process automation, etc.2
By way of example, consider a concrete component installed inside a structure. Starting from a mathematical model representing the durability of the material, it is possible to predict its performance under various conditions without having to conduct expensive and time-consuming laboratory tests. The more information the database contains, the better the predictions from the model will be.
Among other applications, this makes it possible to develop an effective maintenance plan and track the condition of the structure in real time via sensors installed on the equipment. This technique reduces maintenance operations and facilitates optimal decision-making with respect to the type and timing of interventions to be carried out.
AI is also used in intelligent transportation networks, where it assists controllers in making real-time decisions aimed at ensuring optimal allocation of units of a vehicle fleet within a given territory. Based on input from sensors installed on the vehicles, along with road congestion data and other information that is analyzed, algorithms make recommendations that help to ensure more effective management of the transportation system.
AI and workplace quality of life at CIMA+
Innovation is an integral part of the organizational culture at CIMA+, and is reflected in all of our practices, including personnel management. As a Platinum Level Aon Best Employer, we listen to our employees and are working to implement a new human resources management tool known as UltiPro, which is based on AI techniques. For example, the Perception module makes it possible to conduct surveys among employees, and then uses algorithms to record and classify the emotions hidden in the collected responses. Using this new tool, it is possible to administer personalized questions and carry out an in-depth analysis of the data. Our management team can then intervene more rapidly and effectively in order to meet the needs of employees in connection with a wide range of issues, from workplace quality of life to employee benefit programs.
AI is a powerful decision-making tool that makes it possible to manage projects more effectively and reduce costs, and is quickly gaining ground in all areas of engineering. In view of this rapid evolution, in 2017, the Ordre des ingénieurs du Québec took part in a reflection exercise related to the responsible development of artificial intelligence within the context of the Montreal Declaration. Upon completion of the exercise, the Ordre issued seventeen recommendations of a technical, ethical or legal nature, eight of which apply to the profession (consult the recommendations here [French only]).
As such, [translation] regardless of the technology used (including AI), society requires of its engineers that their works be safe. Accountability and risk assessment are more than ever at the heart of engineering practice. Artificial intelligence must be used in service of the well-being of society.3
With the collaboration of:
Claude L’Archevêque, CRHA, CCP, GRP, Senior Director, HR Shared Services / Human Resources, CIMA+
Lucie Tabor, M.Sc.A., Junior Engineer / Bridges, CIMA+