In a great old movie, Field of Dreams, a voice encourages Kevin Costner to construct a baseball field. “If you build it, they will come,” the voice tells him. Since then, virtually all of us have been told, rightly or wrongly, that if we invest the effort and expense in building a particular something, the world will flock to our door—the right organization, the right community, the right data infrastructure.
In information technology at least, I think that voice is a little off the mark. What it should have said is, “If THEY build it, they will come.” In some respects, we’ve entered the age of DIY IT at enterprise scale. Many of our most important development activities are nearly post-corporate.
When the open source movement began, it focused on operating systems and middleware; it indisputably made both fields more responsive to user demands and industry requirements. It made users more powerful, even the ones that weren’t actually doing any coding. That process hasn’t slowed down, even as the project moved into higher and higher planes.
Open source collaboration continues to be the bedrock of our most important innovation streams, including AI. And it’s post-corporate, solving problems that exist for all our largest data handlers in projects with huge pools of collaborators—projects like Linux, Hadoop, and more recently, presto. And given the increasing demand for Rapid Return on Investment, no one is going to rely less on open source anytime soon—just the opposite actually.
So whether you are IBM, an industry client, a government organization—it isn’t enough to watch open source, or to “tolerate” it. You need to invite it, to embrace it, as the foundation of an innovative approach to things like data management, data analytics, and especially AI. “If THEY build it, they will come,” after all. If you enable the secure use of the most innovative tools, data formats, and analytic techniques, your knowledge workers will come to you with the benefit of their well-crafted insights, built safely on your data.
If you block the tools your data scientist and analysts like best, they will go elsewhere—maybe not physically , but to shadow IT, where they run on their own cloud, far from any oversight or compliance. The antidote is a a system that welcomes, even invites open source and its many innovations. That doesn’t mean ignoring the risks; it means understanding and mitigating them as you build on their strengths.
At IBM we believe in open source, as contributors, as users, and as developers of technologies that extend and strengthen the capabilities of open source with enterprise support.
How are you accommodating open source in your industry or organization?
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