Consumers and businesses alike are concerned about artificial intelligence (AI). The more they question it, however, the more obvious the solution becomes: The antidote to public distrust of AI is transparency — and no one does transparency better than developers of open source software.
“Transparency is essential for building trust in AI systems,” Nikhil Vadgama, co-founder of the DLT Science Foundation, a London-based nonprofit dedicated to advancing blockchain technology, wrote in a 2024 op-ed.
“Users can scrutinize the underlying mechanisms, which helps mitigate the risk of unintended consequences and promotes responsible AI development.”
For exactly that reason, open source software is already popular amongst a large contingent of business, government, and academic users, a growing number of whom have adopted it over the past 40 years. Its fans cite its low cost, increased flexibility, and highly collaborative nature as its biggest benefits, all of which encourage innovation.
“History has proven that openness fosters innovation rather than hinders it,” Vadgama continued. “If AI projects are open-source, a global community of developers, researchers and enthusiasts can contribute their expertise, ideas and improvements. By making AI tools freely available, developers and organizations with limited resources can leverage state-of-the-art algorithms without the need for substantial financial investments. This inclusivity facilitates the widespread adoption of AI, benefiting a broader range of industries and applications.”
What makes the fruit of open source software possible is the open source community. Because it’s built on trust, it’s perfectly positioned to shepherd the development of AI. By applying the open source principles of the past to the technology of the future, it can help create the guardrails that are necessary to make AI safe, secure and successful.
Open Source Software Benefits
According to OpenLogic’s “2024 State of Open Source Report,” which tracks open source software usage and market trends, 95% of those who work with open source software say their organization has either increased or maintained its use of open source software in the past year. One-third say their organization has increased its use “significantly.”
According to OpenLogic, what makes open source software most appealing to enterprises is its affordability. 36.64% of open source users cite the lack of a licensing fee and overall cost reduction as their greatest benefits. Also valuable is its ability to improve development velocity, cited by 30.71% of open source software users.
Rounding out the top five reasons why organizations use open source software: its stability and available support (27.64%), the access it affords to innovations and new technologies (26.86%), and its ability to reduce vendor lock-in (21.29%).
The last decade of open source software has been “incredibly transformative,” Richard Harmon, vice president and global head of financial services at Red Hat, told The Forecast.
He said there are now more than a million open source projects worldwide, spanning government organizations, businesses, and academic institutions.
“It’s a global community,” said Harmon.
Democratizing AI
Open source in AI development is helping to democratize AI by making it more accessible, according to Harmon.
“Many of the most advanced algorithms are in the open source space,” he said, adding that there are free libraries and tools that can help people code more efficiently — including generative AI tools that can make code writing easier.
Bev Gunn, global FSI ecosystem manager at Red Hat, added that open source software allows developers from different organizations and communities to contribute to emerging AI technologies, develop new talent, and improve productivity.
“The extensive open source ecosystem provides exposure to niche areas while at the same time breaking down silos across industries,” she noted. She explained that the ecosystem collates many contributions around open source and AI development, making them work in a more structured, programmatic way.
Yet open source isn’t just about accessibility. Equally important is governance, according to Harmon, who said regulated industries, in particular, must be able to audit their next-generation AI capabilities.
Consider the banking sector, for example. Harmon said banks are combining open source software with AI to automate processes in ways that make them more efficient, effective, secure and resilient. Layered on top of this intelligent automation is the ability to monitor systems, identify problems and correct errors.
SWIFT, a global payments system jointly owned by 11,000 banks, describes it as leveraging open source in AI development to build “financial transaction intelligence at scale.”
Although it’s a compelling vision, realizing it will require the financial services industry to overcome key hurdles in AI development, such as licensing and data usage.
Creating Impact with Innovation
Alan Clark, a spokesperson for the Open Enterprise Linux Association (OpenELA), said the biggest reason companies are using open source software is that it has become the breeding ground for innovation.
“People are throwing things out there and seeing if they stick,” said Clark, who leads the Industry Standards and New Initiatives Program at open source software company SUSE.
The global collaboration that’s inherent in the open source software movement draws together people with different backgrounds and experiences to drive innovation.
Gunn said this spirit of community and collaboration is exemplified by Red Hat OpenShift’s family of containerization software. In the last five years, major cloud providers like Microsoft and Amazon Web Services have embraced Red Hat OpenShift.
“Building out managed service offerings within their own organizations with our technologies is kudos to the value that they see” in open source, Gunn said.
But innovation isn’t just about generating revenue. Often, it’s also about generating impact, according to Harmon, who noted that Red Hat — the largest open source company in the world — employs many passionate engineers who are focused on solving challenges in various industries.
“It’s not just about building a piece of software,” he said. “It’s about trying to make something better.”
To get a sense for the positive impact open source can have when it’s coupled with AI, consider its influence on global issues like climate change, suggested Harmon, who cited as an example OS-Climate (OS-C), an open source collaboration community whose members — including Red Hat — are rallying together to build a data and software platform that will boost the flow of global capital into climate change mitigation and resilience.
“Our goal is to build analytical tools and a data commons platform that enables the access, generation and structuring of relevant, global datasets. The platform, data and tools work in combination to generate vital information that can inform climate-related decision making,” OS-C explains on its website.
“All of our infrastructure and tools are produced at a pre-competitive layer with open source end-to-end models.”
‘Trust and Meritocracy’
At its core, what makes open source work is its “survival of the fittest” mentality.
“Open source projects are built on trust and meritocracy,” Clark said. “I can bring ideas, and people will evaluate those ideas. As the trust builds, they give me more rights and access to do more things.”
In the early days of open source software, people were unsure about the code being generated and who had the rights to it. If that sounds familiar, it’s because AI is currently facing those very same challenges. According to Clark, it can overcome them by relying on the same meritocracy that ultimately endeared people to open source.
“The way AI is going to fit in is using the same open source model that we have today,” he continued, noting that current large language models (LLMs) are not as deterministic as some enterprises need them to be — especially in regulated industries like finance and healthcare.
“There’s a lot of model refinement that needs to happen.”
Although AI seems to be everywhere, its adoption is still in its infancy. By applying to AI the same models and processes that helped open source build trust over decades, the open source community can establish itself as a leader in responsible AI.
Therein lies the future of open source software.
“Open source is not just an innovator," Clark concluded. “It’s also going to help … enterprises build … trust to consume AI in the future.”
Gary Hilson has more than 20 years of experience writing about B2B enterprise technology and the issues affecting IT decisions makers. His work has appeared in many industry publications, including EE Times, Embedded.com, Network Computing, EBN Online, Computing Canada, Channel Daily News, and Course Compare. Find him on X.
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