Artificial Intelligence is one of the most relevant topics of the 2020s. The rise of tools like ChatGPT, MidJourney, and Stable Diffusion have made Artificial Intelligence accessible to more individuals—as a result, more people now understand AI and its effects on society.
And while AI has its impact on nearly every industry imaginable, it has had an incredibly profound impact on engineering. Today, engineering encompasses a wide variety of activities like software engineering, construction, and aerospace engineering, among many others.
In this article, we’ll go over some of the most pressing opportunities and challenges that come with an evolving AI landscape and how we can navigate some of those issues.
Artificial Intelligence: A History and Definition
Although Artificial Intelligence feels like an idea that came about within the last decade, it’s actually been around for far longer than that.
Artificial Intelligence as a concept has existed for many decades in stories and books. However, most of them were under the guise of fantasy or science fiction—until the 1950s with Alan Turing’s Computing Machinery and Intelligence.
In that paper, he theorized that if humans can use reason and available information for problem-solving, what’s stopping machines from doing the same?
Today, Artificial Intelligence and Deep Learning are pretty much used in a similar fashion as Alan Turing’s initial theory—although the technicalities are far more complex to summarize.
In essence, AI is the simulation of human processing and using already existing information to analyze new information and arrive at solutions. Using deep learning, machines can learn from existing data and use that knowledge to “think” and operate as an individual would (except without the complexities of emotion)
But AI isn’t perfect, and there are still issues with it that we are facing today. Some of the most common problems people have with AI include the following:
- Data Privacy
- Intellectual Property Theft
- Job Security
And the list goes on. But before we get to the challenges, let’s look at the positive impact AI has on modern engineering.
The Opportunities
Engineering is all about efficiency, regardless of what field you may be in. By its nature, engineering is a practice that helps develop systems that function as intended while also being efficient at the same time.
AI can help us achieve that through the following.
Big Data Opportunities
Big data refers to any data set that we cannot analyze with conventional data analysis software and must be dealt with using more advanced technology. Big data is complex, comprising a wide variety of data types, and arrives at a high velocity—especially in today’s digital age.
Our ability to analyze big data has been a crucial aspect of our growth as people. Because of big data, we can analyze trends that would otherwise never be spotted by human analysis alone. Artificial Intelligence has only made this process faster and more streamlined.
For example, AI in hospitality industry can be used to analyze big data from various sources, such as social media, online reviews, and booking patterns. This allows hotels and other businesses to better understand their customers and tailor their services to meet their needs. For example, AI can help predict peak demand periods or identify specific guest preferences, such as room temperature or pillow type, to improve the overall customer experience.
In fact, data engineers and analysts are some of the most in-demand jobs today. And thanks to AI and our ability to analyze big data, the future of engineering and data analysis has been changed invariably for life.
Data Management
In line with big data, one other opportunity AI has brought engineers is data management. All organizations utilize the power of data. And without it, most of the conveniences we have today would simply not be possible.
Good data management can contribute to engineering by:
- Improving predictive capacity;
- Reducing storage costs (more efficient storing);
- Reducing friction;
- Increasing data accessibility.
All of those mentioned are crucial to developing systems that work, and AI is a wonderful complement to human capacity in this regard. With the existence of AI, much of the menial labor associated with storing and managing data can be delegated to a machine or software.
Another useful tool for data management is a web scraping API, which can extract data from websites and deliver it in a structured format. This can be particularly helpful for gathering large amounts of data quickly and efficiently.
Improved Design
The beauty of Artificial Intelligence is that there is virtually no end to its capacity with enough time and resources. Unlike humans, AI does not forget, and it doesn’t conveniently leave out crucial bits of information.
And while AI does make mistakes (and is by no means error-free), one of the best opportunities we can capitalize on is the concept that AI can significantly help us develop better engineering design.
AI gives us the capacity to do the following thanks to improved design:
- Reduce engineering costs;
- Increase engineering efficiency;
- Delegate menial tasks to machines or algorithms;
- Increase utilization of automation;
AR VR technology is also playing a crucial role in improving engineering design. By creating immersive, 3D virtual environments, AR VR technology is enabling engineers to visualize and iterate on designs more effectively. If there is a demand for customized applications and tools for engineering design, it is worth turning to an AR VR development company.
Increased Opportunities in Construction
According to a Mordor Intelligence report, AI in the construction industry is poised to grow by an average of more than 33% on average through 2027—eventually set up to become a multi-billion dollar industry.
While construction might be the last thing on your mind when it comes to AI, Artificial Intelligence has actually been a primary factor contributing to the recovery of the industry after the pandemic.
Thanks to AI, construction companies can now do the following:
- Make more efficient project-related decisions;
- Improve cost prediction;
- Reduce waste and, in effect, cost;
- Improve employee on-site safety;
- Conduct environmental testing more efficiently.
In addition to these benefits, the adoption of the HL7 FHIR standard has enabled construction companies to integrate their AI systems with FHIR servers, allowing for more seamless data exchange and interoperability between different systems.
All those mentioned have made construction safer, more cost-efficient, and overall an improved industry. As our knowledge of deep learning grows, we’re bound to see even more enhancements in this field of engineering.
The Challenges
Despite the many wonderful characteristics of AI we mentioned above, it isn’t always what it’s cracked up to be.
AI, for its many fantastic characteristics, also faces many challenges in a modern world that loves convenience yet is still quite hesitant to change.