As anyone who has used a smartphone or an Amazon Echo knows, software has progressed to the point of being virtually omnipresent in our daily lives. We have created machines and algorithms that turn our actions, thoughts, and emotions into raw, tangible data. This is data that software engineers can obtain, exploit and manipulate. However, the game is changing. Instead of traditional programming, in which the programmer writes step-by-step instructions that tells the computer what to do, programmers are training the computers to recognize situations and react like a human would.
One thing isn’t changing though; an ever-developing world of technology is accompanied by a demand for technologically skilled workers that is continually outpacing the supply. It’s fortunate, then, that UK’s students are increasingly turning to STEM studies as they progress towards their careers. The past 10 years has shown a 32% increase in the amount of undergraduate STEM entrants; students pursuing physics and astronomy is up 54%, chemistry and materials science is up 50% and mathematical sciences is up 32%.
It’s difficult to know what’s in store for the future of AI but let’s tackle the most looming question first: are engineering jobs threatened? As anticlimactic as it may be, the answer is entirely dependent on what time frame you are talking about. In the next decade? No, entirely unlikely. Eventually? Most definitely. However, the jobs more likely to be made obsolete soon are manufacturing jobs and anything with a service counter: groceries, retail, etc. We’ll need STEM careers to power and coach these machines that automate our lives. It’s wise, then, that more students are rising to the challenge and choosing STEM careers.
The capabilities of AI through machine learning are wondrous, magnificent… and not going away. Attempts to apply artificial intelligence to programming tasks have resulted in further developments in knowledge and automated reasoning. Therefore, programmers must redefine their roles. Programmers will take on the new job as AI coaches. Software development and engineering jobs will not become obsolete but instead more in demand and require more collaboration between humans and computers. There will be an increased need for engineers to create, test and research AI systems.
The ultimate goal of artificial intelligence for software engineers is automated programming: an engineer or user could simply state what is wanted and have a program produced to solve that need automatically. It’s worth noting, however, that automated intelligence can be categorized into two types: artificial specific intelligence and artificial general intelligence. Artificial general intelligence is based on the principle that machines can be made to think. Machines have similar functions to the human brain, operating with reason, logic, and understanding. When general artificial intelligence is mastered, software engineers will be obsolete. Don’t fret, though, general artificial intelligence is still in the budding stages with many long years of research needed to make it a functional reality. Specific artificial intelligence refers to a machine’s ability to perform specific tasks extremely well and sometimes better than a human. However, even those this version of AI is closer to reality, in many ways it is still in the nascent stages.
AI and machine learning will not be advanced enough to automate and dominate everything for a long time, so engineers will remain the technological handmaidens.
AI and machine learning will not be advanced enough to automate and dominate everything for a long time, so engineers will remain the technological handmaidens. At home, specific AI technologies like the Echo, therefore, are not necessarily leaps in the machine learning industry, but instead just represent the natural progression of technology. In other words, we still have a long way to go. And software engineers have a huge role in getting us there. We will need them to create and train new AI technologies for industries like healthcare, manufacturing, transportation, food production, customer service, finance and more. We will also need them once these AI technologies are created and in use, for flexibility, performance, and security.
Software engineers will be needed to improve adaptability and usability, incorporate integrations, and create custom features to improve the flexibility of AI solutions. Engineers will be involved on the front-end of development and the backend of development. We’ll need software engineers to maximize performance so that machines can process loads of information and still reach as many users as possible. Lastly, when it comes to the creation of new, never-before-seen technology, security is always a concern. Software engineers will be needed to create custom layers for backups, intrusion detection, prevention systems, and just simply the understanding of what humans want out of security in their AI systems.
Most importantly, programmers will need to adapt to a new world where traditional coding skills might be redundant. The regurgitation of information will be virtually unneeded. We’ll need to train the growing number of STEM students to work collaboratively with each other and with AI systems to rethink coding and innovation. Creative problem-solving, people management, and social intelligence remain significant bottlenecks to machine learning and will need to be cultivated and refined in our next generation of STEM careers. Students will need to be trained to master the skills that bridge AI with human ingenuity and match the growing tool of disruptive design. Students will need to work to collaborate with tools that that build on speech recognition, digital assistance, augmented reality, and generative design.
So, to answer the question, I don’t see software engineering jobs going away anytime soon. On the contrary, the tech industry is rapidly expanding and will continue to do so. It might be more prudent to consider the effects of automation and AI affecting jobs in industries such as sales operations, construction, maintenance, and food preparation. Those areas, and others, could be the future of what’s next with AI. It’s therefore essential to refine our educational curriculums to reflect the world of AI and educate for progress.