An Interview with Anne Lee Steele, STUDIO SANSHIN [Systems Leadership Series #4]

Anne Lee Steele is the founder of STUDIO SANSHIN, a creative research studio for community-centered practitioners. Previously, she was the Research Community Manager for The Turing Way at the Alan Turing Institute, where she stewarded an open-source, community-driven resource for reproducible data science. Approaching her work as an ethnographer first and a community-builder second, Anne examines how social, technical, and political systems intersect, and how communities can foster more ethical, collaborative forms of digital practice. She has worked on a variety of projects in the open ecosystem, including at the Internet Society, Wikimedia Deutschland, and Open Knowledge Foundation, and is passionate about the capacity for open source practices to support public interest technology, culture, and research.

I have the great pleasure of speaking with Anne Lee Steele, an anthropologist, facilitator, open knowledge advocate, and critical public interest technologist. Jumping right in with our first question: How do you define the system you’re engaged with and trying to change? You might speak to the system’s functions or niches, inputs and outputs, and key feedback loops or patterns you pay attention to. You might also touch on external forces and their impacts.

I’d call myself a practitioner in what we might think of as public interest technology, which for me translates into the open ecosystem: a mix of actors and sectors that interpret “open knowledge,” “open source,” “open access,” and “open science” in sometimes radically different ways, yet remain united under the broader umbrella of openness.

I first entered the open ecosystem in 2015 as a user and contributor to the Ushahidi project, a mapping initiative developed in response to humanitarian crises that emerged alongside the rise of Twitter. In 2020, I became more deeply involved as an anthropologist studying OpenStreetMap (OSM) and the use of humanitarian maps. I spent two years with that community, exploring its dynamics, tensions, and evolving role in the broader technology ecosystem, especially as OSM data began to serve as training material for AI systems.

That research later informed my work as Community Manager for The Turing Way at the Alan Turing Institute, the UK’s national institute for data science and AI, where I’ve been based for the past three years. Since then, I’ve engaged with multiple interpretations of openness — facilitating mapathons (the very phenomenon I once studied), guiding public tours for the Open City festival in London on internet infrastructure and the history of telecommunications, and co-organizing the Open Research Room at FOSDEM, Europe’s largest open source conference in Brussels.

Through these lenses, I engage with what I think of as the open ecosystem, each part with its own tensions, questions, and politics. What unites them, especially looking back to their early roots in the 2000s, is the question of how access to information, spaces, and participation shapes how we engage with the world around us: our communities, universities, politics, and families. You can see this reflected in the apparent dichotomy between something like WikiLeaks and Wikipedia: who releases information, how it’s shared, and in what context. That tension has long driven my curiosity and shaped my role as an ecosystem actor.

Lately, after several years immersed in scientific communities, I’ve been thinking about what it might look like to engage with publics outside academia, with artists, practitioners, and others who work more directly in public-facing or civic spaces. STUDIO SANSHIN, named after mountain spirits in Korea, is my institutional home for this experimental, intersectional work.

Just to follow up on that first question: in your role as Community Manager at The Turing Way, how would you describe the specific slice of the open ecosystem you’re most focused on right now? What patterns or feedback loops are you noticing, and how do they connect to broader forces — economic uncertainty, political shifts, and changes in how people consume and process information? In short, could you draw a tighter circle around the part of the open ecosystem you’re most deeply engaged with and tell us what that looks like?

When I joined The Turing Way, I entered what I’d describe as a wiki-like project founded by neuroscientist Kirstie Whitaker and international collaborators — a kind of Wikipedia built by and for research data scientists to address the reproducibility crisis in science. Under conjoined leadership with Malvika Sharan, an open research practitioner and bioinformatics-trained researcher, the project soon broadened its scope, expanding from a single guide on reproducible research to five guides on project design, communication, collaboration, data management, and ethical research. Together, these reflected how deeply the reproducibility challenge extended across scientific practice.

As part of what I’d call the third generation of the project, my role as an anthropologist and sociologist was to help the community reflect on how to incubate, support, and sustain itself after rapid growth. Much like in humanitarian development work, my goal was ultimately to make myself redundant – to help build a community capable of sustaining itself without me, which was both strange and exciting.

Coming from the open access and open source worlds I was curious about how “open” was being used in the context of open science. What did it actually mean to people in practice? To explore this, I conducted interviews with contributors, asking what was happening in open research, what tensions existed, and what role The Turing Way played.

What I found was a community deeply aware of the politics of technical infrastructure – for example, that building on JupyterBook means relying on the broader Jupyter ecosystem, and that single points of dependency (like libraries maintained by one volunteer) carry real risks and responsibilities to contribute upstream. Alongside this came increasing awareness of power dynamics within open-source spaces broadly, such as dominant voices in GitHub threads or community calls.

At the same time, I encountered many isolated researchers who were looking for community – people trying to advocate for open practices within universities or companies, often without institutional support. They wanted to publish on GitHub, share reproducible workflows, or use The Turing Way resources, but faced bureaucracy or unsupportive supervisors. Many came to the community seeking solidarity and connection.

Compared to other parts of the open technology ecosystem, I noticed that some open science communities were less familiar with the deeper politics of the platforms they relied on – for instance, Microsoft’s relationship to open source, or the influence of large philanthropic networks in shaping “open” agendas. As a researcher trained in science and technology studies, I saw my role as helping make those underlying politics visible and providing language to unpack them.

In practice, my role as Community Manager centered on three main areas. First, I worked on the project’s governance systems, helping to build structures for shared decision-making. Second, I stewarded convening spaces, like our fireside chats and other public discussions, to bring together diverse contributors. Third, and most importantly, I learned the art of facilitating shared spaces and rituals – practices that help communities bridge differences and build trust.

That last part, the practice of shared facilitation, is what stays with me most as I move into other parts of the open ecosystem. What I learned from The Turing Way is that we can only bridge across our differences in the open ecosystem if we share space together.

Picking up on the art and practice of shared ritual – how to be together, how to create space, and how to build containers for people to be in conversation with each other. In connecting systems-level change with day-to-day work: how do you design processes for collaboration that make that connection? What strategies do you use to build trust so that people can act collectively? How does your design of convenings, interactions, and rituals help others see and engage with the system as you do? Finally, how does storytelling fit into that?

When you join any system, as I did with The Turing Way, you inherit existing systems, rituals, and culture. When I joined, there were already a few established rituals. One was a bi-monthly community call called the Collaboration Cafe, structured from the beginning around the Pomodoro-style working model. Over my three years with the project, it was fascinating to see how that ritual evolved and how central it continued to be for the community.

Among many other things, what I learned from that call was the tension between going to a space to work and going to a space to share. Initially, Turing staff – whose paid roles included contributing to The Turing Way – were encouraged to join the Collaboration Café to do co-working and writing together. At the same time, volunteers from different institutions and geographies would join out of curiosity. Some found the call on (then) Twitter or LinkedIn and dropped in to see what the community was about.

Very quickly, I realized those two intentions (productivity and curiosity) were in tension. Some people wanted to adhere strictly to Pomodoro sessions to maximize productivity within their paid time. Others came seeking connection and discovery. I had to create a container that held both, to set expectations differently for productivity while keeping curiosity central. It took a lot of trial and error to find a facilitation style that worked both for me and for everyone attending.

That experience taught me that when you enter an existing system, you’re never starting from scratch. Much of my work as Community Manager focused on recognizing and formalizing what already existed – setting the groundwork for another stage of growth and change.

When I came in around 2022, there were people already translating and localizing resources, often self-organized. I’d say, “Hey, maybe this is a team, let’s gather resources here.” Others were maintaining the infrastructure, metaphorically cleaning door handles and shining floors,  and I’d suggest, “Maybe this is a working group.” Over time, this became a working group model, which formalized ongoing community efforts.

In order to make this happen, people needed to trust me, and trust that they would retain their autonomy as self-directed contributors. That trust-building process was slow. Anthropologists know this well, and The Turing Way itself draws on frameworks like adrienne maree brown’s Emergent Strategy, which emphasizes “moving at the speed of trust” (something Kirstie integrated into the founding principles). Moving at the speed of trust means moving slowly – through many one-on-one conversations, trust-building exercises, and facilitating rather than directing community leadership. I expected governance formalization to happen much faster, but when you move at the speed of trust, it takes time.

I came to see my role as a facilitator for community leaders rather than as a leader myself. That distinction mattered: to hold trust, I had to be able to balance differing opinions and tensions without inserting my own agenda. Maybe that reflects my background in development and humanitarian work, and how the Geneva Conventions and international law think about the idea of neutrality. But for me, that neutrality was essential to sustaining trust and supporting collective action.

I’ll go back to one of our recent conversations, where you talked about the interdisciplinary makeup of the community – people entering from very different positionalities and backgrounds, each holding their own set of questions. How do you help them start to see themselves inside a system called Open Science? Or more specifically, inside The Turing Way community? How do you shift from “we’re convening and building trust” to “we have a shared identity”?

Something I learned early was that researching a community is not the same as facilitating and supporting one. The act of being that reflective mirror – of openly sharing what I was observing – became a trust-building practice in itself. It was a gesture of openness. I began publishing a weekly post on the GitHub platform, which, I quickly noticed, was a key gathering and discussion space for the community. People would respond, “Oh, I hadn’t thought about our work that way,” or “It’s interesting to see this through a researcher’s lens.”

As someone coming from the social sciences, I also realized that “openness” looks different across disciplines. I wouldn’t, for example, release raw ethnographic interview data the way a physicist might release a dataset. Our ethics, our relationships to data, are very different. But in publishing those weekly reflections, I was opening the research process, and that openness helped build credibility and care within the community.

I also learned to appreciate the lurkers. Lurkers are often undervalued, yet they occupy this important middle space between passive observation and active engagement. The Turing Way, like any large community, has many of these latent members. A big part of my role was figuring out how to support that middle space, how to make it safe and inviting, so that those folks felt a sense of belonging even if they weren’t visibly active.

Part of that came from direct invitations to join our twice-yearly ritual: the Book Dash. It’s like a hackathon or write-a-thon focused on contributing to the book (in whatever form that took). We’d identify participants and invite them: “Would you like to join the organizing team? Facilitate a session? Bring this conversation into another space?” 

But even among highly engaged members, I noticed something striking: people often didn’t see themselves as leaders or as “qualified” to take on responsibility. I’d hear, “I’m not sure I know enough to do that,” from people who had already led sessions or contributed for years. So a big part of my job was constant reinforcement: reminding them that they did belong, that their contributions mattered.

This kind of positive reinforcement is vital, especially in academia. Researchers often feel isolated in their daily environments, and that isolation can make it hard to see themselves as part of a collective. In academic systems, I think there’s a kind of intergenerational trauma, passed down through disciplines, that shapes how people see their worth, their creativity, their place in the system. Talking to physicists, computer scientists, neuroscientists, they all carry disciplinary baggage that affects how they approach openness and collaboration.

So, on the surface, The Turing Way might look like an open knowledge project – a collaborative book, a bit like Wikipedia. But beneath that, what keeps people engaged is much deeper: “I’ve found people who make me feel seen.” “I’ve learned a new skill I didn’t know I could learn.” “I can express myself differently here.” The book is just the visible expression of that deeper transformation. And that’s why the project keeps growing – because every generation of contributors understands that it’s about the people first, and the product second.

Are there examples of interventions or projects where you’ve incorporated elements of systems leadership as it’s been described in the resources that we’ve shared so far?

In reviewing the resources you shared – especially the UK Government materials on systems leadership – I was struck by how much emphasis there was on noticing interconnection. That made me think of a class I attended recently that was organised around the poet Ocean Vuong’s feedback model, what he calls the ‘structure of recognition’.

In Vuong’s MFA courses at NYU, for the first five weeks no one is allowed to critique any poem. Students can only describe what they notice. When critique begins after that period, it’s offered with a much deeper sense of observation and care because everyone has first practiced description. I loved that approach. It immediately made me think: this is how I want to structure any critical or collaborative system.

So much of academic work, especially in the social sciences, is about deconstruction and critique. You’re trained to identify gaps, contradictions, and what’s missing. I came into facilitation with that same mindset: I could diagnose problems easily, but I didn’t know how to fix them. I was excellent at identifying what wasn’t working and terrible at repairing it.

Reading about systems leadership through that lens was fascinating. The framework takes inspiration from sustainable development and ecosystems – recognizing interconnection, thinking about mycelial networks and other living systems, even the commons. Malvika’s approach to the leadership in the project actually integrated these principles. But for me, it ultimately comes down to cultivating presence and trust. You can design all the systems, frameworks, and structures you want, but without trust, they’ll fail.

Maybe that’s part of why ecosystemic thinking resonates so strongly right now. Our social fabric feels fractured, and trust is scarce. Frameworks have become substitutes for the soil of shared presence that we’ve depleted for so long.

How do you measure or evaluate your effectiveness in driving systems change when your primary lever is building trust and presence? How do you know when trust has been established? What does it look like in practice, and how do you recognize it?

One approach is recognizing that while the goal is always trust, systems themselves don’t operate on that goal. That creates a gap between reporting and understanding real community change. Quantitatively, you can track metrics like number of conversations, connections made, network mapping, citations, or mentions on social media. These give a sense of presence, though not always depth or trust. Qualitative measures, like interviews or observation, are crucial for assessing real impact.

A concrete example comes from planning for my own obsolescence as a community manager at The Turing Way. My metric for success has always been: what happens when the community no longer needs me? Starting in 2025, I began incubating a Community Management Working Group, identifying participants interested in developing leadership skills and creating a space for peer learning. Our funding was limited, so the goal was to ensure the project could continue without paid support and without me as the default person for most questions.

Measuring success involved observing the types of work people took on and gradually stepping away. At first, I would step back for short periods, then longer, answering only occasional questions. Over time, the community began to operate independently. That, to me, was the clearest signal of success: another generation had stepped in and taken ownership.

This process also required ego death – recognizing that my way of doing things wasn’t the only or best way, and that others could improve on the systems I had built, which themselves had been built on systems that had existed before me. Learning to step aside and let the community evolve is, I think, one of the most important lessons for stewarding any open ecosystem or collaborative practice.

What feels important to you about systems-engaged leadership practice in moments like the one we’re living through right now?

I’d add to my previous answer that much of academic work and culture carries intergenerational trauma. If we replicate the same structures, management systems, and ways of engaging that we were exposed to, we end up reproducing those patterns in any system we join, whether counter movements or mainstream institutions. 

For me, openness has become an ethos: to advocate for open practices, I must understand what openness looks like for me personally, recognize where I keep things closed, and consider how that tension translates to the systems I’m part of. How do I approach spaces where others want to keep things private, and how do I do so with compassion rather than critique? This is crucial to avoiding the replication of interpersonal and intergenerational trauma, especially in times of political pressure, austerity, and constraints on academic freedom.

Planning for your own obsolescence is another key element I’m still grappling with. James Baldwin’s observation that the world is held together by very few people resonates deeply here. Many projects, for example, are headed by a BDFL – a benevolent dictator for life – or by a super-engaged core with little wider participation. When I approached that from a critical lens, I might have thought, “Oh, this is a closed community, not open to others.” But read through Baldwin’s lens of passion and dedication, it’s clear these people are deeply committed to the community or cause they’re part of. Maybe there’s a hunger for power or a need for control, maybe an important sense of belonging, maybe other things, but through a compassionate lens, how would you approach that community differently?

I’m still trying to understand the tension between stewarding, supporting, and celebrating the generations that came before us, while urgently bringing in new blood – without repeating the same questions over and over. It’s interesting to talk to folks who have been in the Open Knowledge ecosystem longer than me; they often say: “I’ve seen this question cycle through again and again. People ask the same thing, it dies down, and then comes back five or ten years later.” I actually think you can only ask those questions in a cyclical way and get closer to real change if new people are asking them. The older generation plays important roles, but if they keep asking the same questions, the ecosystem stagnates, because the soil has been depleted after years of the same cycles.

And maybe one of the problems now, given changes in the job market and political times, is that newcomers have a harder time entering many spaces such as conferences. In retrospect, the move to remote work enabled by COVID-19 enabled many meetings to be globally accessible in a way that they hadn’t been before, and that in turn enabled career connections and progressions that might not have been possible otherwise. I was absolutely a beneficiary of this in 2020. 

But as many groups have reversed their policies in the years since, this has meant that voices that could lend new perspectives or ask the same questions differently are no longer present. I think that is actually incredibly alarming, because it’s an unnatural contraction of the digital meeting ecosystem after an expansive couple of years.

Given everything we’ve discussed so far, does the framework of systems leadership as presented in these publications resonate with you? If the framework resonates with you, why? If not, why? Are there other frameworks that feel more resonant, especially for doing systems change work?

It was very interesting to read the piece from the Stanford Innovation Review about Nelson Mandela. I found it an interesting lens to start with, because as I read it, I thought, “Oh, I’d never thought of him as an ecosystems leader.” As I kept reading, I realized that ecosystems leaders are leaders of many differences – they are bridgers across difference. They can see the massive picture, then zoom in to facilitate action at the micro level, without losing the vision that, for example, guided South African politics into a new dawn.

I really struggle with this, honestly, because of the times we live in. I noticed that much of my language, my canon, and my influences come from a very specific place. I have a shared ecosystems language with people aligned with me, but I come from a different media and influence landscape than, say, an ecosystems leader in defense and security work, who has a different canon.

I saw this in real time in graduate school. My school – a small institution in Geneva that specialised in international affairs and development often felt like it was split in half.  On one hand, there were ecosystems of people discussing liberatory politics, especially after the decolonization movement of the mid-20th century, and a very specific language learned together to enact its ideals. And then there were the people who embraced realpolitik and the kind of post-war, game theory, Cold War approaches to politics that have dominated since World War II. These are completely different ecosystems of thought, both talking about international politics, but with completely different canons and frameworks for evaluating change.

Reflecting on your question, yes, systems leadership resonates with me. But the difference now, compared to the examples in the piece, is around shared foundational frameworks.

Today, institutions often host multiple frameworks within the same school – you can be trained in either or both – but usually, you specialize. So educational institutions are producing people with training that lacks a shared language or framework for understanding how the world works. That makes bridging these gaps far more difficult than in earlier periods.

Nowadays, the fracturing is evident: so many critical thinkers have sought refuge in the academy alongside their critics, but their students in turn haven’t shared the same experiences that constitute a shared social fabric. I’m left wondering what it looks like to bridge that, when education has historically been the force through which we socialize, normalize, and find bridges.

What advice would you give to emerging leaders, in any position or role within a system, who are focused on driving systemic change?

I think the oldest answer in the book to this question is: find allies. Find allies you can be open and honest with, who allow you to feel seen and heard as you fight whatever fight that might be. 

Alongside that, I’d say it’s crucial to do the inner work around clarity of self. As someone responsible for stewarding a community, I felt responsible for what I would call a “third space” – a space for people that was neither work nor home, but a communal space, like what might previously have been a community center, a church, a pub, a bar, a gym. The Turing Way was a third space, and I was its facilitator. That came with enormous responsibility, but it took me a long time to realize that facilitators of third spaces themselves need a “third space” – a place where you can exist outside of the role, and be seen and engaged with in a different way.

Part of that work is also recognizing that to steward collective and individual voices around you, it’s important to disentangle your own voice from the community. For me, that meant entering different ecosystems – turning toward computational artists, freedivers, people completely outside of the academy. In those environments, I found a version of myself separate from the ecosystems I was trying to change. That helped me uncouple my ego from whether change happened, which was extremely important.

Ecosystem work is long, difficult, and slow. I realized that if I got caught up in the needs of the people I was supporting – or attached myself to controlling particular outcomes – it would make me deeply unhappy. And if I were unhappy while trying to steward a happy community, that cognitive dissonance could have made me implode. So, the tactics I learned were: find allies, do the inner work, separate your voice and ego from the system, and give yourself space outside the ecosystem to sustain yourself.