lwasser · Nov 3, 2026 · Oct 28, 2026 · Nov 3, 2026 · Nov 3, 2026 · Nov 3, 2026
@@ -0,0 +1,206 @@
+---
+title: 'When the Human Disappears: What Maintainers Told Us About AI Contributions at EuroPython'
+date: '2026-12-08'
+type: blog
+excerpt: >
+  At EuroPython 2026, fifteen maintainers talked for more than two hours about
+  how AI tools are changing open source. The conversation kept returning to
+  the loss of human connection.
+description: >
+  At EuroPython 2026, fifteen maintainers talked for more than two hours about
+  how AI tools are changing open source. The conversation kept returning to
+  the loss of human connection.
+author: Leah Wasser
+reviewed_by: ["Carol Willing"]
+blog_topic: community
+toc: true
+comments: true
+url: "/blog/when-the-human-disappears-europython.html"
+lastmod: '2026-11-03'
+highlight_image:
+  src: images/events/Felipe-moreno-leading-sprint-pyconus-2026.png
+  alt: Three people at PyCon US 2026 gather around a laptop, including Advisory Council member Felipe Moreno. Felipe stands and points at the screen while two sit and look on.
+---
+
+{{< figure src="images/events/Felipe-moreno-leading-sprint-pyconus-2026.png" alt="Three people at PyCon US 2026 gather around a laptop, including Advisory Council member Felipe Moreno. Felipe stands and points at the screen while two sit and look on." caption="Contributors working with pyOpenSci Advisory Council Member, Felipe Moreno, at our PyCon US 2026 sprint." >}}
+
+At EuroPython 2026, the largest Python conference in Europe, pyOpenSci
+facilitated a pilot focus group on how AI tools are changing open source
+work. Fifteen maintainers from core scientific Python and Linux projects
+joined a discussion that ran more than two hours. The maintainers in this
+group steward core open source projects that many researchers depend on.
+Their experiences with how contributors and others are using AI tools are
+critical to understanding both the benefits and the strains AI tools bring to
+open source projects.
+
+We expected to hear about the time it takes to review AI-assisted code.
+Instead, the conversation kept returning to something else: **the loss of
+human connection.**
+
+The group covered the full range of AI tool use. Some refuse to use the
+tools and, in some cases, have left tech because of the strain. Others have
+fully embraced them, including people in start-up environments where
+adoption feels like the "only option" to keep up.
+
+*This pilot focus group was larger and more open-format than the small groups
+planned for our [research on how AI tools are changing scientific open
+source](/blog/ai-tools-research-sloan-funding.html). This post covers the
+human side. All contributions to the discussion are anonymous.*
+
+## The loss is relational
+
+> We need to see the human on the other side.
+
+Maintainers described real joy in helping and mentoring contributors. Someone
+finds a bug and files a fix. The maintainer helps that contributor get it
+merged and, along the way, mentors them and builds their open source skills.
+That interaction fuels many maintainers. It's also important to remember that
+contributors have traditionally been users of a project and so they also
+influence the direction that the project takes. This dynamic changes
+drastically when you have agentic GitHub users making batch contributions to
+projects simply to gain "credit."
+
+AI-assisted contributions are eroding these personal, fulfilling
+interactions. That leads to drain and burnout in the expert community. When
+maintainers lose the part of the work that sustains them, fewer stay, newcomers
+lose mentors, and the open source ecosystem that researchers depend on grows
+weaker. We heard similar concerns at our [PyCon US roundtable on AI
+tools](/blog/pycon-us-2026-generative-ai-open-source.html). At EuroPython,
+three patterns came up repeatedly.
+
+### Not knowing who is on the other end
+
+The tension runs in two directions. Sometimes a maintainer really is talking
+to an agent or bot. Other times, it is a legitimate human.
+
+One maintainer shared a story about suspecting a contributor was an agent.
+When they pressed further, the contributor turned out to be a person. The
+strain lands on both sides: the maintainer can't tell who they are talking to,
+and the contributor, who was just trying to help, is suspected of being
+deceptive.
+
+> "Hey, this looks like AI wrote this."
+>
+> "Um, I wrote this last night."
+>
+> "Oops."
+
+No one in our session had a solution, but many of us experience this new and
+confusing exchange.
+
+### False empowerment
+
+A contributor working with an AI tool or agent can feel fully self-sufficient
+and never realize they need to engage with the maintainer. They keep making
+contributions, sometimes large ones, without pausing to connect with the
+humans maintaining the project. Meanwhile, the maintainer, who wants to
+engage with a human, is trying to reach someone who isn't listening.
+
+We also wonder whether visibility plays a role here. People doing core project
+work may not be seen by contributors the way they once were. Contributors used
+to see maintainers answering issues, reviewing code, and shaping the project.
+Now maintainers can fade into the background, and contributors may reach for a
+tool before they think to reach out to a person. The new norm risks treating
+maintainers as infrastructure instead of people that contributors engage with
+carefully and considerately.
+
+### Shifting motivations
+
+Maintainers see contributors who are chasing resume bullet points or trying to
+get past automated hiring filters. Some employers also encourage open-source
+contributions to demonstrate technical skill. The extreme version of this
+behavior is called "karma farming": opening many pull requests on
+high-profile projects to build up a GitHub profile. This isn't new, but it now
+makes up a much larger share of incoming work.
+
+Credit is part of this too. One maintainer redid minor bot-generated fixes
+themselves rather than merge them, to avoid crediting an agent. Small,
+externally driven agent pull requests can generate more work for maintainers,
+and it remains unclear who deserves credit.
+
+Beyond the focus group, we have heard stories of people setting up agentic
+accounts that first build karma and trust through valid contributions, then
+are deployed autonomously in harmful ways. I saw a version of this on the
+[all-contributors bot](https://github.com/all-contributors/app), which I
+maintain. I recently banned an account that was clearly an agent. It commented
+frivolously on issues and pull requests in an attempt to "review" them, and it
+submitted dozens of pull requests for issues that hadn't yet been triaged for
+viability. All of this happened within hours. Building that kind of standing
+normally takes weeks to months.
+
+## Don't just call it AI slop
+
+It is easy to dismiss a low-quality pull request as "AI slop." Some
+participants pushed back on that label. One maintainer said the real question
+is whether the contributor is willing to invest their energy in engaging with
+the project.
+
+If maintainers assume AI was used, they create a problem by misjudging a
+newcomer who wants to get involved. Rejecting their work outright as "slop"
+doesn't help either party. The contributor may simply need guidance on using
+AI tools thoughtfully. The maintainer can miss the chance to connect and help
+a well-intentioned contributor build real skills.
+
+**There is a real tension at this crossroad.** Many AI-fueled contributions
+strain maintainers, and that strain can understandably leave them shorter and
+less patient with new contributors. It is hard to know where to invest limited
+time, and whether the person on the other end is a human who cares about the
+process and learning, or an agent building credibility. But dismissing
+contributions too quickly risks turning away someone who genuinely wants to
+help.
+
+## What projects are trying
+
+**Participants unanimously agreed on one point: banning AI tool use altogether
+is the wrong approach.** A ban doesn't stop people from using these tools. It
+pushes that use out of sight, and contributors become less likely to disclose
+it. That makes the community less open, honest, and secure.
+
+The maintainers in our group prefer flexible guidelines to strict rules and
+policies. Approaches include:
+
+<<<<<<< HEAD
+* Open an issue before opening a pull request, so a human conversation happens before any contribution. As a human, connect first with other humans.
+=======
+* Open an issue before opening a pull request, so a human conversation
+  happens before any contribution. Connect first with other humans.
+>>>>>>> faea5734 (docs(blog): copy edits from Erika)
+* Disclose AI use, including when the output hasn't been fully reviewed.
+* Hold quality constant. The standard is the same whether or not a tool was
+  used. If an AI-assisted contribution is high quality, maintainers accept it.
+  Licensing is a separate consideration that came up only briefly in this
+  conversation.
+* Verify a human who cares about the project. One maintainer described asking
+  contributors to attend a meeting to show they are a human who cares about the
+  project. Talking to someone in real time is one of the few remaining ways to
+  build accountability.
+
+That last approach has a cost. Maintainers have spent years lowering barriers
+to contribution and are now forced to raise new checkpoints in order to
+validate inputs. Protecting maintainers and welcoming newcomers pull in
+opposite directions.
+
+Participants also noted that contributions aren't only code. Outreach,
+documentation, and community work are meaningful, and they are harder to
+measure.
+
+## What pyOpenSci is taking forward
+
+This pilot gave us questions to test at scale:
+
+* How common is it to not know whether a human is on the other end?
+* Do contributors and maintainers see the same interaction differently?
+* Which policy approaches reduce strain and which just move it?
+
+Behind each of these is the need we heard at the beginning: to see the human
+on the other side.
+
+If we drain the ecosystem of its maintainers, newcomers lose their mentors
+and the software science depends on gets harder to sustain. Working toward a
+resolution now protects both the people and the research that relies on them.
+
+If you maintain or contribute to open source, [sign up for the survey and
+upcoming focus groups](https://forms.gle/yTNXwQWQC4dLvErB7). That signup is
+part of the [Sloan-funded research](/blog/ai-tools-research-sloan-funding.html)
+this pilot belongs to. Our next post covers why people adopt these tools and
+where their views split.
@@ -29,6 +29,6 @@ For Leah Wasser's keynote and other pyOpenSci sessions during the conference
 week, see [pyOpenSci at EuroPython 2026](/events/2026-07-13-europython/).
 
 <figure>
-  <img src="/images/events/europython-sprint-2026.png"
+  <img src="/images/events/Felipe-moreno-leading-sprint-pyconus-2026.png"
        alt="Three contributors collaborating around laptops at a pyOpenSci development sprint">
 </figure>