AI excels in coding, but there are significant limitations.

AI excels in coding, but there are significant limitations.

GitHub CoPilot

Creating and testing code at the touch of a button through generative artificial intelligence (AI) models, such as GitHub CoPilot or ChatGPT, almost seems too good to be true. So good, in fact, that there has to be a catch.

While software professionals are embracing AI as a power tool to build, launch, and update applications, there is also nervousness about its intellectual property and security implications. Is that AI-generated code scraped from someone else’s intellectual property? Does the model draw on internal corporate data that should be kept secure?

Technologists recognize that AI adoption requires attention to rights, privacy, security, productivity, and training. The majority of respondents in a GitLab survey expressed concern about AI tools having access to private information or intellectual property. Copyright concerns top the list of concerns about using AI-generated code. Close to half of the respondents cited concern that code generated using AI might not be subject to the same copyright protection as human-generated code. Another worry was security vulnerabilities.

However, despite these concerns, technologists remain optimistic and continue to forge ahead. Among respondents whose organizations are using AI in software development today, as many as 90% felt confident using AI in their daily tasks at work. AI is seen as an important investment from a software development perspective, with benefits including improved efficiency, faster cycle times, and increased innovation.

Training and skills also emerged as a common theme in the obstacles and concerns identified by respondents. As much as 81% said they need more training to use AI at work, and 87% said organizations will need to re-skill employees to adapt to the changes AI will bring. The potential to introduce a new set of skills to learn and a lack of the appropriate skill sets to use AI or interpret AI output were some of the concerns expressed.

Ultimately, AI cannot replace human oversight and innovation. More experienced professionals accept AI as a supportive tool for skill development, but don’t think it can completely replace the expertise, knowledge, and problem-solving of seasoned professionals. Leveraging the experience of human team members alongside AI is the best way organizations can address the concerns around security and intellectual property.

AI might be able to generate code more quickly than a human developer, but a human team member needs to verify that the AI-generated code is free of errors, security vulnerabilities, or copyright issues before it goes to production. With the right combination of human expertise and AI tools, developers can harness the power of AI while ensuring privacy, protection of intellectual property, and the delivery of high-quality code.

Image: GitHub CoPilot