artificial intelligence
GlobeNewswire
Published on : Sep 14, 2023
Application security leaders are more bullish than developer leaders on generative AI, though both agree it will lead to more pervasive security vulnerabilities in software development
New research from software supply chain management company Sonatype reveals how generative AI is influencing and impacting the work of software engineers and the software development life cycle. According to the 800 developer (DevOps) and application security (SecOps) leaders surveyed, virtually all (97%) are using the technology today, with three-quarters (74%) reporting they feel pressure to use it despite identified security risks. In fact, most respondents agree that security risks are their biggest concern associated with the technology, underscoring the critical need for responsible AI adoption that will enhance both software and security.
While DevOps and SecOps respondents hold similar outlooks on generative AI in most cases, there are notable differences with regards to adoption and productivity. Key findings among the two groups include:
“The AI era feels like the early days of open source, like we’re building the plane as we’re flying it in terms of security, policy and regulation,” said Brian Fox, Co-founder and CTO at Sonatype. “Adoption has been widespread across the board, and the software development cycle is no exception. While productivity dividends are clear, our data also exposes a concerning, hand-in-hand reality: the security threats posed by this still-nascent technology. With every innovation cycle comes new risk, and it’s paramount that developers and application security leaders eye AI adoption with an eye for safety and security.“
The licensing and compensation debate was also top of mind for both groups - without it, developers could be left in legal limbo dealing with plagiarism claims against Large Language Models (LLMs). Notably, rulings against copyright protection for AI generated art have already prompted discussion about how much human input is necessary to meet what current law defines as true authorship. Respondents agreed that creators should own the copyright for AI generated output in the absence of copyright law (40%), and both overwhelmingly agreed that developers should be compensated for the code they wrote if it’s used in open source artifacts in LLMs (DevOps 93% vs. SecOps 88%).