Is Generative AI Going to Replace Software Developers?

Generative AI Vs. Software Developers

Generative AI is gaining popularity this year, and many are curious about its consequences for employment in the future. Specifically, everyone is concerned now about the software development field because AI can write a large number of codes in just one blink. What if software professionals are replaced by Artificial Intelligence(AI) or Generative AI? Also, according to engineers, AI tools have already increased team productivity. Does that mean a future with fewer or more jobs?

Hence, in this Generative AI tutorial, we will analyze whether generative AI replaces software developers or not. Before that, let's see what generative AI is exactly. You can also go through our Artificial Intelligence Course.

What is Generative AI?

• Generative AI is used to create text and photos. These systems can write code in response to produce images, music, essays, and blogs.
• Programs like DALL-E and ChatGPT have gone viral all over the world.
• The language model ChatGPT, created by OpenAI, creates content based on the input it gets.
• It understands and produces writing that resembles that of a human by using its machine-learning techniques.
• The model only understood specifics about which documents were in its training set despite having been trained on a wide variety of Internet content.
• With the prompt of predicting what comes next in the text-based format, ChatGPT generates a response.

Who are Software Developers?

• Software developers are the ones who design, write, and maintain code to create software applications.
• Their role is understanding user requirements, designing system architecture, writing and testing code, debugging, and collaborating with other team members.
• In particular, Developers bring creativity, problem-solving skills, and domain-specific knowledge to their work.
• They ensure that software solutions meet the needs of users and stakeholders.

Can Generative AI Replace Software Engineers?

Now, the question is, Will generative AI replace software developers? The answer is a big no for the following reasons:

1. Generative AI has amazing tools, but despite this, these systems cannot work without some instructions. To instruct them what to do, like what code to write, for instance, they require a human to enter a prompt.
2. Large software projects cannot be created only using generative AI. When you ask ChatGPT to develop a search engine, all it can do is create a basic search engine, nothing like a fully complete Google search engine.
3. Moreover, generative AI frequently generates code that is flawed or error-prone. Therefore, a human must check it to ensure its accuracy.
4. Also, Generative AI tools do not fully understand abstract concepts, context, and the expressions of human language and requirements.
5. Additionally, they cannot create things like Software Developers do, make moral judgments, or consider how a piece of software will affect society.
6. Consequently, it is doubtful that generative AI would completely replace software developers, even though it might be a helpful tool in their toolbox.
7. Although it helps automate some jobs and increases productivity,
8. Alternatively, the job description for software engineers may change to focus on more creative, analytical, and human judgment duties.

1. Flexibility

Software developers have always to learn new technologies and techniques because the field is constantly changing. At the moment, artificial intelligence (AI) cannot match the creativity and technological adaptability of human engineers despite the fact that AI can automate important work. In this rapidly growing industry, human engineers must be good thinkers who can change course when faced with unexpected obstacles and emerging trends.

2. It takes humans to solve complex problems.

Beyond basic programming, the core of software development is problem-solving. This necessitates a thorough comprehension of complex needs and the capacity to decipher minute details that regularly differ from project to project. While AI technologies can aid in certain portions of this process, they are unable to fully comprehend or manage the intricate and frequently arbitrary elements that competent engineers routinely handle.

3. Creativity and innovation

Innovative software engineering requires technical proficiency, inventiveness, and a deep comprehension of human technology usage. Even though AI may help with automation and data-driven discoveries, human engineers are still critically needed for their creativity and intuition. These human characteristics drive innovative software solutions that consumers find engaging and intelligible. Furthermore, it doesn't appear likely that these qualities will be changed anytime soon.

4. Morality and supervision

Software development needs to handle ethical issues and be closely watched to make sure that programs are compliant with laws and ethical standards and meet the demands of users and society, as all developers are aware. However, AI can only think as it is programmed; it is incapable of moral thinking or comprehension, which is required to make decisions that respect human values and the law.

5. The technical aspect

Instead of taking the place of their abilities, many engineers find AI to be helpful in enhancing them. As previously said, most of these technologies aim to simplify particular processes so that engineers can focus more on the creative aspects of development that require human interaction.

Generative AI in Software Development

However, Generative AI does not replace Software Engineers. Still, they are beneficial assets for Software Engineers.

Some of its advantages include the following:

1. Take on challenging code translation tasks with more ease.

• The 2021 International Conference on Intelligent User Interfaces featured a study that revealed generative AI gave programmers a rough foundation for converting old source code into Python.
• Developers discovered that, despite the ideas' occasional errors, it was simpler to evaluate and correct them than to start from scratch when translating the source code by hand.
• They added that they already go through a similar procedure of examining and making corrections when working with code written by their coworkers.
• Developers using GitHub Copilot Labs can translate code into many programming languages by using the companion VS Code extension, which is independent of yet dependent on the GitHub Copilot extension.

2. Writing code more effectively.

• If we do study developers who used generative AI tools coded up to 50% faster than those who didn’t
• their productivity gains went beyond speed by 75%.
• Software developers reported that they felt less frustrated when coding with generative AI tools and were able to focus on more satisfying work.

3. It solves problems quickly

• The study also found that software developers used Generative AI tools like GitHub Copilot to find creative solutions when they were stuck and did not know where to go.
• These software developers searched for the next possible steps and relied on the generative AI coding tool to assist with unfamiliar syntax.

4. Discover solutions inside their IDEs.

• Some software developers also used GitHub Copilot's multi-suggestion window (a Generative AI tool) as a StackOverflow alternative.
• Software developers could ask GitHub Copilot to come up with ideas for achieving their goals directly.
• They could also hit Ctrl/Cmd + Enter to view a list of ten options.
• This type of exploration enabled one developer to use an unknown API effectively even though it didn't result in deep knowledge.

5. Build a better testing process.

• Some generative AI coding tools are great in pattern recognition and completion.
• Developers are using these tools to build unit and functional tests and even security tests with natural language prompts.
• Some tools also offer security sensitivity filtering, so a developer will be alerted if they unknowingly introduce a sensitivity in their code.

Advantages of Generative AI for Software Developers

The importance of learning Generative AI

The technology of generative AI is rapidly growing despite its amazing state already. Within this year, a significant advancement in capabilities is projected.Software developers and organizations should conduct proofs of concept today to familiarize themselves with the technology. This will allow them to react swiftly when more sophisticated models are published. Even with all of the difficulties and dangers that generative AI presents, the long-term benefits are still promising.

Generative AI models are becoming increasingly powerful. This graphic displays the size of major generative AI models introduced since 2018 in billions of parameters.

Comparative Analysis

The Future of Programming with AI

While it seems unlikely that AI will replace programmers in the next few years, programmers still need to develop new abilities to integrate AI into their regular workstreams. Anyone in the computer science industry is, of course, used to learning new technology.

For programmers and software engineers, the following AI concepts, abilities, and frameworks are becoming more and more in demand:

• Applying and deploying application programming interfaces (APIs)
• Prompt engineering
• Machine learning
• Deep learning
• Cloud platforms
• Natural language processing (NPL)
• AI ethics

Conclusion

Software engineers will continue to play a secure role in the future despite these developments in AI. The human work of software engineering has the capacity for comprehension, creativity, and adaptation, so AI cannot yet replicate it. Consider our brand-new Generative AI For Software Developers Training Certification for a better understanding of AI concepts.