Role of Open Source in AI

In this Tech Barometer podcast, Red Hat’s Bev Gunn and Richard Harmon take listeners into the collaborative world of open source software and explain why it can lead to responsible AI.

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Transcript (AI generated):

Richard Harmon: The fundamental principle that’s first is around a global community trying to innovate. So it’s not a single firm, but the global community collaborating. You have people with very different backgrounds, different experiences that are heavily driving innovation overall, and much of the innovation is coming from the open source world.

Bev Gunn: We have strong partnerships with Intel, a lot of the hardware manufacturers as well from the IBM systems groups to NetApp and Dell and HP, and all of the main hardware firms, plus the APIs and chip organizations. So again, just in terms of how open source and our technologies can actually enhance what they’re doing, aligned to what Richard has said is very key to moving forward.

[Related: Can Open Source Software Help Resolve AI Trust Issues?]

Jason Lopez: This is the Tech Barometer podcast. I’m Jason Lopez on today’s edition of Tech Barometer, a look at open Source. Open Source was in the headlines quite a bit during the.com boom. And rather than develop things in the seclusion of their organizations, the idea was to collaborate across company boundaries. This model has evolved over the past two decades. There’s still a bit of controversy over it versus building software in proprietary ways, but open source proponents like the speakers you’re about to hear from Red Hat, see open source as a crucial factor in developing AI in a responsible way In this era of virtualization, hybrid multi-cloud ai, edge quantum computing, it has a vital role to enable new capabilities and engineering business and governance.

[Relate: Open Source Software Powering Business Application Boom]

Richard Harmon: The open source community also has, in some cases, it’s not always profit focused. It’s about building something that’s completely new or different. It’s also about making it accessible to the global community.

Jason Lopez: Richard Harmon is the vice president for the Global Financial Services Industry at Red Hat.

Richard Harmon: But I think, for example, AI governance, there’s a lot of effort about how to evaluate the accuracy of whatever algo that you want to utilize. It’s important not to have black boxes so you can explain what the model is doing, why is it doing and what the answers are. It’s also making sure that things are done in a fair way so that you can monitor that. There’s no bias in other things that could come from the data, come from the algo, come from all different sources.

Jason Lopez: Harmon adds that the ability to audit as well as the security and privacy of applications for consumers, businesses, and governments, is paramount. This is where open source plays a role in accountability, such as in AI responsibility.

Richard Harmon: And I think that that’s something we see with many, many of the projects, the AI based projects in the open source space. Now, I’m not saying if you go into a project that’s done by a single firm, they would also require to instill those principles, but there’s also in many cases, a profit motive behind it. So sometimes when it has a wider open source view, you have people in the community that really focus on these types of things that make AI responsible versus just making AI work.

[Relate