This technology, whether you like it or not will be part of our future, in its current state it’s still new and being worked on, however, it’s already shown to be a powerful tool. To adapt and utilize this tool to augment our human abilities in ways to enhance our creativity and productivity presents both opportunities and challenges that demand our careful consideration. It’s a very exciting technology with a myriad of applications that’s here to stay and a lot of focus will be placed on expanding the application thereof.
AI is a very disruptive technology, and we need to adapt, it’s already shown to have a meaningful impact on many industries and the software industry is no different. The software development industry should not be afraid to change the way they work and incorporate AI-powered tools into their day-to-day. I want to mention however, that over reliance on AI will also be a trap as it bases all decisions on historical data and hence will have limited ability to innovate, this is the reason that the software industry will remain as we ultimately exist for our innovation and creativity.
AI won’t take over developers’ jobs, however, it is likely to cause a shift in the job, as has been the case many times throughout our history as humans, whenever new technologies developed, people often feared for their jobs and the result was adaptation instead of replacement. AI will help automate various repetitive jobs that developers face daily, which can allow the developers to spend their time more effectively on more meaningful and innovative work.
At its core, the discourse surrounding AI lies in the tools’ ability to augment human creativity and innovation with its ability to traverse vast datasets at unprecedented speeds out of reach of us, mere humans, granting access to information at a speed and precision we aren’t accustomed to. This, however, is where it remains a tool, it cannot determine whether the information it has processed and provided is accurate, and it is still at the mercy of the potentially tainted data that the model has been trained on. It’s crucial to be able to recognize that AI isn’t just a novelty; if used correctly it can be a powerful instrument to add to our existing abilities and assist in modern system design.
Generative AI presents an opportunity to enhance our iteration process in the development pipeline, reducing the time-to-market and accelerating innovation. It can prototype rapidly and respond to dynamically changing requirements and user feedback. It will require time for any developer to become proficient at it as with any other tool. If used correctly it can enable us to deliver superior quality software to our clients and ultimately their users faster than we have before.
We must also remain vigilant, as overreliance can diminish the value of human ingenuity in the design process. Software engineers remain responsible for ensuring the quality of AI-generated solutions. Care must be taken to ensure that bias from data sets fed into the AI model during training doesn’t derail the development process and that users of the tool remain responsible for not relying too much on the tool for decision-making.
One must also be cautious about unintentional feedback loops that can reinforce existing biases in the machine learning model, since it learns from historical data it will learn from them and contain those in any feedback to the tools’ user, they may inadvertently be using this information to reinforce the model with this bias. We need to take care to keep innovating, which will ultimately allow the model to be able to learn from more diverse data, which will give the tool more options for the future. An effective balance between the tool’s guidance and the user’s creativity and innovation must be maintained else it can diminish the value of our ingenuity in the design process.
As AI improves and is trained on more diverse data sets specifically relating to software, and new tools in the software industry become part of the lake of information available to the AI, more personalized solutions can be extracted from the AI to create tailored system design/solutions for clients of the software developers to effectively find balance between the input from AI as well as their own experience and expertise.
AI in the world of software development also presents automated code-generation tools to assist in the development process, existing tools are being enhanced and new tools are being developed to automate various aspects of software development. AI tools currently utilize natural language processing (NLP) to allow developers to provide the requirements to automatically generate code snippets, giving the developers space to focus on the larger problems presented in the system.
In addition to code generation, AI-powered tools have been developed/are being developed that are targeting other parts of the development process, including automated design generation, with novel features like integrating into commonly used design tools like Figma. Using the tool would still require oversight from a competent designer to get the most valuable output to achieve the client’s targets. This AI-powered tool in addition to text prompts also allows a user to submit existing designs giving suggested modifications and hence can be used for inspiration.
Another common area in software development that can benefit from the use of AI is testing, here it complements the tester’s abilities to improve delivery speed. It helps with assisting in script generation for automated testing, helping to close potential oversights for the tester, and ultimately improving test coverage and quality. An example of where this is currently being implemented is in an automation testing software called Katalon, within the testing IDE Kalaton Studio, the company released an AI-powered plugin to assist with script generation to improve the delivery speed of automation test suites for testers who don’t have a development background.
As stated above, this allows developers to streamline the development process, improving software quality. Used effectively, it can unlock opportunities for them to be more creative and innovative. As AI develops and becomes more integrated into the IDEs and other tools developers and designers use on a day-to-day basis, it will become a larger part of their toolset and build on their effectiveness of using the tool to improve the work they deliver.
While AI in its current state shows immense promise, it’s essential to remember that it’s just a tool. Like any tool, it requires guidance and expertise to use effectively. As software engineers, it’s up to us to harness the tool, to ensure it complements our abilities. AI has the potential to change the way developers approach the development process and change the landscape of system design. As the focus is on developing and improving AI its representation in the development process is likely to increase and its impact shouldn’t be underestimated, conversely also not overestimated. It should be used as a supplement to the process and not a replacement.
