The field of software engineering is always evolving, and so too are the tools available to developers. The rise of artificial intelligence (AI) and natural language processing (NLP) tools is hurtling the UK towards the future, not just in technology but various other industries, including healthcare, finance, and transportation, are finding advancements from the introduction of AI to their tools and processes. The benefits and risks associated with AI, alongside the potential impact on the future of work is vastly debated. Change can be intimidating; however, we’re already seeing use cases where adopting AI into everyday work practices is improving productivity. For software engineers, utilising AI tools like ChatGPT can help to improve code quality, increase efficiency, and remove blockers leading to increased code output.
So, what are the use cases?
AI and NLP tools can be used to analyse code and suggest improvements, such as pointing out areas where code is inefficient or could be optimised for better performance. They can also help to identify potential bugs or security vulnerabilities in the code, allowing developers to fix them faster, and ideally, before they become major issues.
We’ve also seen these tools used to increase efficiency in the development process. For example, using AI to automate repetitive tasks, such as generating documentation or formatting code, can free up developers to focus on more complex tasks, such as writing new features or improving existing ones. Other use cases include streamline communication between team members, helping to reduce miscommunications and misunderstandings that can slow down development, and automating testing or generating automated responses to customer enquiries.
Additionally, AI can help to remove blockers that can slow down development. Developers can use it to better understand complex code or APIs or ask it to provide suggestions for resolving technical issues. It can also be used to provide guidance on best practices for software development, such as how to write clean, maintainable code.
With great power, comes great responsibility
ChatGPT is one of the most powerful AI tools available to software engineers and is in good company with Google's BERT or Notion's new AI function. Of course, as with any new tool, there are also potential risks associated with the use of AI in software engineering. Heavy utilisation of AI tools can lead to a lack of critical thinking or creativity if you become overly reliant on automated suggestions or solutions, particularly if you're an entry-level software engineer. Additionally, there is always the risk of bias or errors in AI tools, which can lead to unintended consequences if not properly addressed or tested.
If adopting AI tools, software engineers should use the tools in conjunction with their own expertise and judgement. AI should be viewed as a tool to assist developers in their work and be proactive in identifying potential biases or errors, rather than look to it as a replacement for human intelligence.
AI and NLP tools like ChatGPT have the potential to revolutionise the field of software engineering. By using these tools to improve code quality, increase efficiency, and remove blockers, developers can work more effectively and efficiently than ever before. However, it is important for developers to use AI tools in a thoughtful and judicious manner, taking care to mitigate potential risks and biases. With the right approach, AI can be a powerful ally in the ongoing quest to create better software.