“AI is everywhere!” Artificial Intelligence appears in articles from multiple news outlets, in every industry advertisement, especially the software development industry. Does AI spell doom for life as we know it? Will it replace our jobs? Can it be controlled before it threatens human existence?! Can AI cross ethical boundaries? Will creativity atrophy? Will relying on AI bias decision-making, risk violating privacy regulations, expose proprietary data to the cloud? These questions express valid concerns. Despite these risks and unknown ones, can AI be useful, especially to software developers? It can.
AI, a Useful Tool
The key here— “tool,” not “original creator.” AI excels at taking in large volumes of data, recognizing patterns, and making connections. It understands the way we talk, so it operates as a highly intelligent search engine that accepts normal questions and returns relevant answers that a knowledgeable human expert might give you.
- Having trouble with an Excel calculation? Ask an AI search engine, like OpenAI’s SearchGPT or Microsoft’s Copilot, and it can write your calculation for you rather than just give you a link to exhaustive Excel documentation.
- Wrestling with JavaScript? AI can give you a complete, working block of code that you can paste into to your projects after adequate testing, of course.
- AI can give you a three-session training outline based on the key principles from a productivity book. (ChatGPT gave us three great sessions to discuss and apply Cal Newport’s excellent book Deep Work.)
- Stuck on a sensitive letter to a client about a past due invoice? AI can suggest wording for writing the letter which you can then tweak to add your own voice.
Removing repetitive tasks, while increasing productivity and efficiency within your workflow, leaves the developer more time for more complicated problems to solve.
But what are some concerns and benefits of AI use?
Fears of AI in Software Development: Valid or Exaggerated?
The concern most often raised about AI is job displacement. Will AI replace developers? The short answer is no.
“But robots replaced humans in many industries!” In the 20th century, car manufacturing started using robots to replace manual labor. According to World Economic Forum, “Assembly-line tasks such as welding and spray-painting were among the first jobs to migrate from people to robots.” However, automation opened additional job opportunities since robots needed oversight and maintenance.
AI cannot replace creativity or problem-solving for client-specific solutions. AI has limits. Resolving difficult issues quickly is challenging if AI is used. Imagine you are a software developer working on a complex web application, and suddenly, a confusing error pops up in your code—a unique bug you have not encountered before. You try asking an AI tool for help by describing the problem in general terms.
However, the AI might struggle to provide a precise solution because the bug is highly specific to your unique codebase, environment, or setup. Even if AI can give you general suggestions, like “check the syntax” or “verify dependencies,” it typically will not be able to identify the exact root cause. These problems require expertise, human thought, and experience.
In addition, AI raises ethical concerns about its dangers. Christina Pazzanese from The Harvard Gazettestates, “AI presents three major areas of ethical concern for society: privacy and surveillance, bias and discrimination, and perhaps the deepest, most difficult philosophical question of the era, the role of human judgment…”
Use of AI demands accountability with the help of human guidance due to a lack of transparency or the “black box” nature of AI systems that could risk unchecked biases or vulnerabilities.
The “black box” nature of AI refers to the idea that many AI systems (especially deep learning models like neural networks) make it impossible to fully understand how decisions or predictions are made. In other words, the inner workings of AI are opaque or “hidden” where we can see information going in and out, but what happens in between is inaccessible or incomprehensible.
At the end of the day, users of AI need to be held accountable, and AI used cautiously, especially with overly complex and sensitive issues in software development.
How AI Makes Developers More Efficient Without Replacing Their Expertise
For starters, AI can address mundane tasks for developers, such as code suggestions, auto-completion, bug detection, and testing, and thus speeding up workflow.
A few of our developers use AI as a helpful resource. For example, Scott Howard, CEO of Moss Rock Solutions, needed help with auto-completion. “I needed to write a complicated Excel formula, and it was escaping me, so I tried ChatGPT, and it gave me the perfect calculation in seconds.”
IBM also uses AI to improve development workflow. IBM developers wanted to reduce the time spent on repetitive code review tasks and maintain high-quality standards across projects. They integrated Watson AI Ops into their development workflow. Watson can analyze code and detect potential issues, recommend best practices, and suggest improvements. The AI-powered code review process checks for common issues like security vulnerabilities, syntax errors, and code inefficiencies.
Use of AI allows developers to catch problems faster and spend less time on repetitive processes. By automating parts of the code review process, developers focus on elaborate tasks, leading to higher-quality code and faster project completion.
Ethical Concerns of AI in Software Development and How Companies Are Addressing Them
Many governments are implementing data protection regulations to ensure that AI systems handle personal data responsibly. Examples include the General Data Protection Regulation (GDPR) in the European Union, which sets strict guidelines for data privacy and the processing of personal information. AI systems that handle personal data must comply with these laws, which mandate transparency, consent, and data protection measures.
Some countries are creating regulations specifically focused on AI. For example, the European Union proposed the AI Act, a comprehensive set of regulations aimed at managing AI risks based on their use. The Act categorizes AI applications into risk levels (low, limited, high, and unacceptable) and imposes restrictions or requirements accordingly. High-risk applications (e.g., biometric identification) face stringent compliance requirements, while low-risk applications are less regulated.
Europe appears ahead of the game when it comes to regulating AI. But U.S. Organizations, like the IEEE (Institute of Electrical and Electronics Engineers) and ISO (International Organization for Standardization), have also developed ethical standards and guidelines for AI development. These standards aim to ensure transparency, accountability, and fairness in AI systems.
The Brighter Future or The Out-of-control Future? AI and Software Development as a Symbiotic Relationship
With the help of healthy and solid regulations regarding ethical concerns, AI can be abundantly useful to improve workflow and reduce mundane tasks like testing and code suggestions. Replacing software developers is a nonissue since development requires human interaction to solve complex issues.
As Scott Howard says, “One key thing to remember is that AI is not always correct, so you need to check its answers.” Without human intervention, AI can have inaccurate information and unethical biases.
With clear regulations, transparent practices, and human oversight, AI can help shape a more productive and innovative development landscape. So, while the concerns about AI are valid, its potential to transform software development for the better is undeniable.
In the end, AI is not here to take over but to become a useful collaborative tool —opening doors to new possibilities and a brighter future.