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Does the rise of AI precede the end of code?

(Image credit: Image Credit: Amedley / Shutterstock)

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 recognise situations and react like a human would. As this Artificial Intelligence continues to grow, questions should be raised about its future and what it means for programmers.   

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 timeframe you are talking about. In the next decade? No, entirely unlikely. Eventually? Most definitely.   

The kicker is that engineers never truly know how the computer is able to accomplish these tasks. In many ways, the neural operations of the AI system are a black box. Programmers, therefore, become the AI coaches. They coach cars to self-drive, coach computers to recognise faces in photos, coach your smartphone to detect handwriting on a check in order to deposit electronically, and so on. In fact, the possibilities of AI and machine learning are limitless. 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.   

Essentially, software development jobs will not become obsolete anytime soon but instead require more collaboration between humans and computers. For one, there will be an increased need for engineers to create, test and research AI systems. 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.   

A certain portion of the software development community will become automated to some extent. This is always the case when certain jobs and elements become repetitive and could be bundled together to increase efficiency, lighten workload and increase revenue. However, much of the software development industry isn’t going anywhere. So much of the desired AI innovation does not exist yet, is simply inefficient or at a very juvenile phase.   

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 categorised 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 though this version of AI is closer to reality, in many ways it is still in the nascent stages.   

A clear example of this is the push to incorporate AI into home living as exemplified by the voice-controlled Amazon Echo, which is powered by Alexa software that was released in 2015. While the Echo might be classified by some as ground-breaking AI innovation (and it might be), it is also equipped with some serious limitations. The Echo has, arguably, state-of-the-art voice recognition technology, the ability to play music on command, and convenience factors like the ability to iterate your calendar for the day. However, in many ways the Echo is more annoying than convenient. Alexa is virtually incapable of taking follow-up commands, it’s difficult for her to know the majority of facts that could be Googled via a smartphone, and she often misinterprets basic voice commands forcing humans to adjust their tone and pitch.   

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 maximise 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.   

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.   

Jason Cohen, Co-Founder and CTO of WP Engine 

Image Credit: Amedley / Shutterstock

Jason Cohen
Jason Cohen is CTO and co-founder of digital experience platform WPEngine. He’s a serial entrepreneur, book author and bootstrapped and built four startups all reaching more than $1M in revenue.