Originally published at: F43 FESCo Elections: Interview with Máirín Duffy (duffy/mizmo) – Fedora Community Blog
This is a part of the Fedora Linux 43 FESCo Elections Interviews series. Voting is open to all Fedora contributors. The voting period starts today, Wednesday 17th December and closes promptly at 23:59:59 UTC on Wednesday, 7th January 2026.
Interview with Máirín Duffy
- FAS ID: duffy
- Matrix Rooms: My long-term home has been Fedora Design, but I also hang out in Podman, Fedora Marketing, and Fedora AI/ML.
Questions
Why do you want to be a member of FESCo and how do you expect to help steer the direction of Fedora?
I have used Fedora as my daily driver since 2003 and have actively contributed to Fedora since 2004. (Example: I designed the current Fedora logo and website design.) I am very passionate about the open source approach to technology. I first started using Linux as a high school student (my first Linux was Red Hat 5.1) and being able to use free software tools like Gimp when I couldn’t afford Photoshop made an outsized impact on my life. (I explain my background in Linux and open source in-depth in this interview with Malcolm Gladwell: https://youtu.be/SkXgG6ksKTA?si=RMXNzyzH9Tr6AuwN )
Technology has an increasingly large impact over society. We should have agency over the technology that impacts our lives. Open source is how we provide that agency. We’re now in a time period with a new disruptive technology (generative AI) that – regardless if you think it is real or not, is having real impact on computing. Fedora and other open source projects need to be able to provide the benefits of this new technology, the open source way and using open source software. Small, local models that are easy for our users to deploy on their own systems using open source tooling will provide them the ability to benefit AI’s strengths without having to sacrifice the privacy of their data.
There is a lot of hype around AI, and a lot of very legitimate concerns around its usage including the intellectual property concerns of the pre-trained data, not having enough visibility into what data is part of pre-trained data sets, the working conditions under which some of the data is labeled under, the environmental impact of the training process, the ethics of its usage. Open source projects in particular are getting pummeled by scraping bots hungry to feed coding models. There are folks in the tech industry who share these legitimate concerns that prefer to avoid AI and hope that it the bubble will just pop and it will go away. This strategy carries significant risks, however, and we need a more proactive approach. The technology has legitimate uses and the hype is masking them. When the hype dies down, and the real value of this new technology is more visible, it will be important for the type of community members we have in Fedora with their commitment to open source principles and genuinely helping people to have had a seat at the table to shape this technology.
(You can see a short video where I talk a bit more indepth about the pragmatic, privacy and open source-focused approach I take to AI here: https://youtu.be/oZ7EflyAPUw?si=HSbNhq_3NelXoX2J)
In the past I have been quite skeptical about generative AI and worried about its implications for open source. (I continue to be skeptical and annoyed by the hype surrounding it.) I’ve spent the past couple of years looking at open source licensed models and building open source generative AI tooling – getting hands on, deep experience to understand it – and as a result I have seen first hand the parts of this technology that have real value. I want FESCo to be able to make informed decisions when AI issues come up.
My background is in user experience engineering, and I am so excited about what this technology will mean for improving usability and accessibility for users of open source software. For example, we never have enough funding or interest to solve serious a11y problems; now we could generate text summaries of images & describe the screen out loud with high-quality audio from text-to-voice models for low vision users! I want open source to benefit from these and even more possibilities to reach and help more people so they can enjoy software freedom as well.
I have served in multiple governance roles in Fedora including time on the Fedora Council, the Mindshare Committee, lead of various Fedora Outreachy rounds (I have mentored dozens of interns in Fedora), and founder / lead of the Design team over many years. More importantly, I have deep Linux OS expertise, I have deep expertise in user experience, and I have a depth in AI technology to offer to FESCo. I believe my background and skills will enable FESCo to make responsible decisions in the best interest of open source and user agency, particularly around the usage of AI in Fedora and in the Fedora community. We will absolutely need to make decisions as a governing group in the AI space, and they should be informed by that specific expertise.
How do you currently contribute to Fedora? How does that contribution benefit the community?
I founded and ran the Fedora Design Team for 17 years. It was the first major Linux distribution community-lead design team, and often as a team we’ve been asked by other distros and open source projects for help (so we expanded to call ourselves the “Community Design Team.”) Over the years I’ve designed the user experience and user interfaces for many components in Fedora including our background wallpapers, anaconda, virt-manager, the GNOME font-chooser, and a bunch of other stuff. I moved on from the Fedora Design role to lead design for Podman Desktop and to work more with the Podman team (who are also part of the Fedora community) for a couple of years, and I also led the InstructLab open source LLM fine-tuning project and corresponding Linux product from Red Hat (RHEL AI.) For the past year or so I have returned to working on core Linux on the Red Hat Enterprise Linux Lightspeed team, and my focus is on building AI enhancements to the Linux user experience. My team is part of the Fedora AI/ML SIG and we’re working on packaging user-facing components and tooling for AI/ML for Fedora, so folks who would like to work with LLMs can do so and the libraries and tools they need will be available. This includes building and packaging the linux-mcp-server and packaging goose, a popular open source AI agent, and all of their dependencies.
My career has focused on benefiting Fedora users by improving the user experience of using open source technology, and being collaborative and inclusive while doing so.
How do you handle disagreements when working as part of a team?
Data is the best way to handle disagreements when working as part of a team. Opinions are wonderful and everyone has them, but decisions are based made with real data. Qualitative data is just as important as quantitative data, by the way. That can be gathered by talking directly to the people most impacted by the decision (not necessarily those who are loudest about it) and learning their perspective. Then informing the decision at hand with that perspective.
A methodology I like to follow in the face of disagreements is “disagree and let’s see.” (This was coined by Molly Graham, a leadership expert.) A decision has to be made, so let’s treat it like an experiment. I’ll agree to run an experiment, and track the results (“let’s see”) and advocate for a pivot if it turns out that the results point to another way (and quickly.) Being responsible to track the decision and its outcomes and bringing it back to the table, over time, helps build trust in teams like FESCo so folks who disagree know that if the decision ended up being the wrong one, that it can and will be revisited based on actual outcomes.
Another framework I like to use in disagreements is called 10-10-10, created by Suzy Welch. It involves thinking through: how will this decision matter in 10 minutes? How about 10 months? How about 10 years? This frame of thought can diffuse some of the chargedness of disagreement when all of the involved people realize the short or long term nature of the issue together at the same time.
Acknowledging legitimate concerns and facing them head on instead of questioning or sidelining others’ lived experience and sincerely-held beliefs and perspectives is also incredibly important. Listening and building bridges between community members with different perspectives, and aligning them to the overall projects goals – which we all have in common as we work in this community – is really helpful to help folks look above the fray and be a little more open-minded.
What else should community members know about you or your positions?
I understand there is a campaign against my running for FESCo because myself and a colleague wrote an article that walked through real, undoctored debugging sessions with a locally-hosted, open source model in order to demonstrate the linux-mcp-server project.
I want to make it clear that I believe any AI enhancements that are considered for Fedora need a simple opt-in button, and no AI-based solutions should be the default. (I’ve spoken about this before, recently on the Destination Linux Podcast: https://youtu.be/EJZkJi8qF-M?t=3020) The user base of Fedora and other open source operating systems come to their usage in part due to wanting agency over the technology they use and having ownership and control over their data. The privacy-focused aspects of Fedora have spanned the project’s existence and that must be respected. We cannot ignore AI completely, but we must engage with it thoughtfully and in a way that is respectful of our contributors and user base.
To that end, should you elect to grant me the privilege of a seat to FESCo this term:
- I intend to vote in opposition to proposals that involve bundling proprietary model weights in Fedora.
- I intend to vote in opposition to proposals that involve sending Fedora user data to third party AI services.
- I intend to vote in opposition to proposals to turn AI-powered features on by default in any Fedora release.
- I intend to vote in favor of proposals to enact AI scraper mitigation strategies and to partner with other open source projects to fight this nuisance.
My core software engineering background is in user experience and usability, and I believe in the potential of small, local models to improve our experience with software without compromising our privacy and agency. I welcome ongoing community input on these principles and other boundaries you’d like to see around emerging technologies in Fedora.