Few innovations have shaken up industries as much as artificial intelligence (AI). Even though the term originated in 1956, it’s only been a tangible feature seen in technology in the last decade or so. These sophisticated algorithms now have a wide range of capabilities that many of us rely on daily. Web searches, social media and our mobile phones now utilise AI to make a smoother, more personalised service for their users.
However, one of the most interesting and productive applications of artificial intelligence is in engineering. All over the world, AI is evolving the role of engineers, changing what they do on a day-to-day basis but massively increasing the scope of work they can complete. But first…
Artificial intelligence is the ability for machines and computer systems to perform tasks that would typically require human intelligence. There are a number of attributes that come under the umbrella term of artificial intelligence, such as visual perception, speech recognition, problem solving, and strategising.
Artificial intelligence in engineering uses software and hardware components. Production lines are often packed with smart computers that control robots to complete their tasks.
Perhaps the most exciting offshoot of AI is machine learning. Machine learning algorithms can collate and analyse data, take action based on that data, then analyse the results of the action. Over time, the algorithm learns which actions have favourable outcomes.
It’s not one of the fastest-growing emerging technologies for no reason; AI is boosting the capabilities of engineers across the world. The technology can plough through tasks at a much quicker rate than humans, so it is often used for tasks that take a long time but don’t necessarily need much skill. Consequently, the human engineers are freed up to work on more complex tasks, which is good news across the board. This ability makes businesses more productive and time-efficient, while also operating at a lower cost. On top of that, many tasks that humans complete, like design, can be improved with the support of AI.
AI is very good at solving theoretical problems in physics and mathematics, but its greatest strength is its ability to solve real problems in practical ways. For example, Google recently announced that it is using AI to help design its chips and claims that it does the job just as well as human designers. Engineers can also ask the AI questions and it will report the most likely outcomes, greatly improving engineering judgements.
Machine learning algorithms are experts at crunching huge datasets and can quickly spot patterns in the data to gather useful insights from it. Machine learning can use these insights to predict what actions to take before the need arises. This is called predictive analytics, and it can be of huge benefit to profitability and efficiency as it typically reduces errors and helps to prevent faults.
One of the largest concerns regarding artificial intelligence is that it will put people (not just engineers) out of jobs and lead to high unemployment. So far, this doesn’t appear to be the case. What we have actually seen is that AI can be used to automate the simple and repetitive tasks and people have more time to commit to doing the more complex tasks.
In fact, a study conducted by Stanford University, titled the “One Hundred Year Study of Artificial Intelligence”, found that there was no immediate risk to workers’ jobs. It also concluded that if or when AI does significantly impact engineering jobs, the net-positive effects on society will outweigh them.
Being an emerging technology, there are still issues that need to be worked out. Privacy is one such issue that must be handled delicately. The main concern here is that AI can create new personal data without the individual’s knowledge or consent. Left unchecked, people’s security may be compromised. This can be controlled for somewhat by developing or implementing the AI with a focus on privacy in the first place, but since legislation and regulations are currently lacking, it seems probable that mistakes will continue to occur.
Remember that at one point, Computer Aided Design (CAD) was merely an additional tool for engineers to make use of. Now, it’s a central part of most engineers’ workflow. As long as a technology can prove its worth and adds real value to engineers, it will be adopted. It seems futile to resist the adoption of artificial intelligence somewhere into your workstream.
The tech will continue to get smarter and be more useful, so the sooner you capitalise on it, the more ahead of the curve you’ll be. The advantages to productivity and profitability are crystal clear, but be careful not to rush implementation.