How Is Artificial Intelligence And Machine Learning Used In Engineering?
Just like with many other industries, artificial intelligence and machine learning are changing engineering. Even though these technologies are now seemingly “everywhere,” we shouldn’t overlook how truly incredible they are and the remarkable things they enable us to do today and will allow us to do tomorrow. For engineers, artificial intelligence and machine learning might cause the tasks they do to evolve, but it can also help them do things they weren’t capable of before.
What is artificial intelligence and machine learning?
First, let’s get clear about our definitions of artificial intelligence and machine learning.
The field of artificial intelligence (AI) was begun in 1956, but it has been only in the last decade that significant progress has been made to allow the technology to be widely used and experienced by many outside technology circles. Today, artificial intelligence is one of the fastest-growing emerging technologies and describes machines that can perform tasks that previously required human intelligence.
Machine learning takes it a step further. It’s one of the latest artificial intelligence technologies where machines can learn by taking in data, analyzing it, taking action, and then learning from the results of that action.
How are artificial intelligence and machine learning used in engineering?
Artificial intelligence that’s used in the engineering sector uses software and hardware components. As machines become more sophisticated, they will be able to support not only smart production lines and complex manufacturing tasks, but will also be able to design and improve tasks over time—with little or no human intervention—through machine learning. Robots have been used by automobile manufacturers on the production line for quite some time and have gone from completing simple engineering tasks to now handling many precision moves required for some of the most intricate parts of the process.
Many of the tasks engineers are responsible for, such as design and simulation, can be enhanced with the support of artificial intelligence tools. Consider how Computer Aided Design (CAD) was once just a supplemental tool to engineering, and today it is a fundamental part of the daily workflow. These tools will help improve the capabilities of engineers and make it possible to explore design and weight-saving options that weren’t ever possible before.
Another way artificial intelligence can support engineering tasks is to break down silos between departments and help to effectively manage data to glean insights from it. AI programs can provide automation for low-value tasks freeing up engineers to perform higher-value tasks. By using machine learning to discover patterns in the data, machines will be incredibly important to help with engineering judgment.
What happens to the role of an engineer?
While there are many benefits of artificial intelligence and machine learning in engineering, some engineers are concerned their jobs will be taken over by machines. Automation has and will continue to take over jobs humans have done historically; however, that can free humans to do higher-level tasks as well as take over jobs that require the unique skills of humans that don’t even exist yet. In one study by Stanford University, “One Hundred Year Study of Artificial Intelligence,” there’s nothing imminent about the threat to jobs, and even when or if we get there, it will be balanced out by the positive impacts on society and the increased capabilities technology offers. A report from the University of Oxford states that science and engineering professions are the least threatened and will experience great benefits from artificial intelligence tools.
In order for engineers to prepare for Industry 4.0, when factory automation, big data, artificial intelligence, and machine learning transform the way we work, engineers should prepare to adapt to the latest tools available to them and learn how to work alongside robots and machines advising them. Engineers must optimize the work that needs to be done so that the interactions between humans and robots are as good as they can be.
This article originally appeared on forbes.com To read the full article and see the images, click here.
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