Today’s Kitchen Essentials interview with Daniela Saderi, Executive Director of PREreview, is part of this year’s celebrations of Peer Review Week. PREreview was launched in 2017 as a resource for the collaborative review of preprints. Its mission today is “to bring greater openness and equity to research peer review by empowering all researchers and experts to participate in reviewing preprints and other research outputs with the tools and community support they need to thrive.” To date, more than 4,700 reviewers — many of them early career researchers — have contributed to nearly 2,200 reviews.

Please tell us a bit about yourself—your role at PREreview, how you got there, and why you embarked on a career in research infrastructure?

I’m the Executive Director and one of the co-founders of PREreview, a non-profit organization whose mission is to catalyze greater openness and equity in scholarly peer review. Drs. Samantha Hindle, Monica Granados, and I started the organization in 2017 while we were all still researchers in training. We shared a simple belief: preprints and other openly shared research outputs could create opportunities for more equitable and open ways of producing, sharing, and evaluating knowledge. We wanted to help make peer review something that more people could participate in by providing guidance, training, and tools that enable researchers — regardless of career stage, institution, geography, or background — to contribute constructive, public feedback.

I never imagined I would end up working in research infrastructure. I trained as a neuroscientist and fully expected to pursue an academic career. But as I progressed through my PhD, I found myself increasingly questioning whether the culture of academia reflected the reasons I had entered science in the first place. I was learning exciting methods and designing rigorous experiments, yet I often felt disconnected from the broader purpose of research and from the communities it is ultimately meant to serve.

That changed when I became involved in the Open Scholarship community. Attending OpenCon 2016 and later engaging with the Mozilla Foundation introduced me to a global network of change catalysts, people who believed that researchers themselves could reshape scholarship through openness, collaboration, and shared leadership. Many in this community were not simply putting new “open” labels on old practices; they were examining the deeper inequities underlying scholarly communication and research production, challenging the status quo, naming power imbalances, and exploring pathways toward meaningful transformation.

Those experiences deeply shaped how I think about infrastructure. What convinced me to leave academia and help build PREreview from the ground up is not the idea that the world needs yet another platform for scholarly peer review. Rather, I believe we need more spaces where people can exercise agency, where they can discover that expertise is not something granted by prestige but something developed through practice and dialogue. We need spaces where we can learn from each other, unlearn assumptions together, and support one another in becoming thoughtful reviewers and collaborators.

The software we build is important, but it is only one part of the infrastructure. Equally important is the community infrastructure: the relationships, facilitation, training, and culture that enable people to participate meaningfully.

What do you like most and least about working in research infrastructure?

What I enjoy most is that, at its best, it’s really about people. I love building relationships that go beyond transactional collaborations. They take longer to develop, but they are also where trust, creativity, and lasting change emerge. Some of the most rewarding parts of my work are spending time with our team and with community members who are curious, who challenge their own assumptions as much as mine, and who are willing to co-create solutions in messy, uncertain spaces. We don’t always know exactly where we’ll end up, but we share a commitment to learning our way there together.

What I enjoy least is that our ecosystem still too often mistakes exclusion for excellence. We continue to rely on measures of success that privilege prestige, institutional affiliation, and visibility, and then we act surprised when the same voices continue to dominate. Those metrics don’t simply measure success, they shape who gets opportunities, whose ideas are heard, and who comes to believe they belong. That’s incredibly difficult to change because many of us have internalized those definitions without even realizing it. One of the biggest challenges we face is that many people have been taught to believe they don’t have anything valuable to contribute. Academia often reinforces the idea that only certain voices count as experts, while everyone else is expected to stay on the sidelines.

Based on your own experiences, what advice would you give someone starting, or thinking of starting, a career in research infrastructure?

My biggest piece of advice is to spend more time listening than building. Before creating something new, learn what already exists. Explore projects and organizations in your own community and in those that are very different. You’ll almost always find that someone has been thinking about the same challenges from a different perspective. Understanding where efforts overlap, where gaps remain, and where partnerships are possible will save you from reinventing the wheel and will almost certainly lead to better ideas.

Talk to as many people as you can, especially people outside your immediate field. Some of the most important opportunities in my own career came from conversations I never expected to have. PREreview would probably not exist if Sam and I hadn’t decided to present an early version of our idea at MozFest to an audience we barely knew. That audience happened to include people who challenged our thinking, encouraged us to keep going, and ultimately connected us with funders who helped turn our idea into reality.

Finally, don’t try to do it alone. Research infrastructure is inherently collaborative work. The strongest ideas emerge when they are shaped by many perspectives rather than a single vision. Be generous with your ideas, invite others to improve them, and don’t be afraid if the path becomes messy. The ultimate goal should be to help create something that a community wants to build and sustain together.

What sort of infrastructure does PREreview provide, and who are your users?

From the beginning, PREreview has been about building infrastructure that enables the kind of cultural change we want to see in research rather than simply creating another platform.

Every feature we build is intended to lower barriers to participation, help people develop confidence as reviewers, and create opportunities for constructive dialogue around openly shared research. We have spent years iterating on the platform with our community, often choosing not to build features we initially thought were good ideas because conversations with community members revealed different needs. “If you build it, they will come” has never been our philosophy. We believe infrastructure should be shaped with those it hopes to support and empower, not simply delivered to them.

PREreview’s initial focus was very much on preprints. They offered an opportunity to make peer review more open, transparent, and accessible by moving it outside the traditional journal process. Over the last couple of years, through working with researchers, educators, patients, community groups, and other partners, we have come to realize that the lasting change we are trying to support is less about the object of review and more about creating a culture where communities come together to exchange constructive feedback as a normal part of doing research. Preprints remain an important entry point because they make research openly available for discussion, but they’re no longer the only place where we see opportunities to foster that culture.

That shift has also changed how we think about who we are building for. Much of scholarly infrastructure is designed for people who already know how to navigate the research ecosystem and see themselves as legitimate participants in it. We wanted to build something different.

While experienced researchers use PREreview, it’s also designed for people still discovering their place in research: early-career researchers, students, community groups, and others whose expertise often goes unrecognized or undervalued. We create pathways that help reviewers build their skills and confidence over time. So the software is important, but so are the training resources, facilitation, community programs, and opportunities to review together. If we want research evaluation to become more open, collaborative, and inclusive, then we have to build infrastructure that helps everyone who wants to offer feedback grow into those roles—not simply infrastructure for the people who are already there.

On PREreview.org anyone with an ORCID record can contribute either a structured or narrative review of preprints across more than 30 preprint servers, as well as a growing number of data repositories, beginning with Dryad and SciELO Data. Every review receives a DOI through DataCite, is openly licensed under CC BY 4.0, gets archived on Zenodo, and can be automatically added to the reviewer’s ORCID record. These aren’t just technical features — they acknowledge that peer review is a valuable scholarly contribution deserving of recognition and reward.

We recognize that openness may carry a risk for some, so reviewers can choose to publish under a persistent and unique pseudonym, allowing them to build a reviewing identity while reducing the potential for retaliation. Making participation safer for more people is just as important as making it possible.

We have also worked hard to ensure PREreview fits within the broader scholarly ecosystem, so our platform is open source and interoperates with repositories and services through initiatives such as COAR Notify. To us, the most meaningful feature is one that facilitates connections with existing communities, tools, and research objects, making it easier for constructive feedback to flow wherever research is shared.

How is PREreview sustained financially?

PREreview is a fiscally sponsored project of Code for Science & Society, a U.S.-based 501(c)(3) nonprofit. Since our founding in 2017, we have been sustained primarily through philanthropic support in the open scholarship ecosystem, complemented by partnerships and contracts for services such as training, facilitation, and the co-development of educational resources.

As we continue to grow, we are thinking carefully about our long-term sustainability. We are building a more diversified model that combines philanthropy, institutional partnerships, and mission-aligned fee-for-service work. The goal isn’t simply financial resilience. It’s also ensuring that the way PREreview is sustained reflects the values we hope to see across the research ecosystem.

One thing we are very clear about is what we don’t want to become. We will never adopt a pay-to-play model where individuals or communities have to pay to participate in peer review or access the opportunities PREreview provides. We don’t think of researchers, students, or community groups as users from whom to extract revenues. We think of them as collaborators and contributors to knowledge, each bringing valuable perspectives that strengthen the research ecosystem.

We invite institutions, foundations, publishers, research organizations, and other mission-aligned partners to invest in shared infrastructure that benefits the entire research ecosystem. Research infrastructure is ultimately a collective endeavor. If we want a more open, collaborative, and resilient system of scholarly communication, then sustaining that system also has to be a shared responsibility. We hope more organizations will join us — not simply as funders, but as partners in building the future of research evaluation together.

As one of the leaders of a research infrastructure organization, what do you think are the biggest opportunities we’ve not yet realized as a community — and what’s stopping us?

I think one of the biggest opportunities we haven’t yet realized is building infrastructure that truly distributes power rather than concentrating it.

Too often, we think about research infrastructure as something that is designed centrally and then deployed globally. I would love to see us invest much more in creating tools that local communities can adapt, extend, and govern according to their own priorities while remaining connected to a broader ecosystem through shared standards and interoperability. To me, that’s what a healthy infrastructure ecosystem looks like: not one dominant platform, but many interconnected communities exchanging knowledge, practices, and innovations in every direction — not just from the most well-resourced institutions to everyone else.

That, in turn, creates an opportunity to rethink what we mean by excellence and expertise. We often talk about decolonizing knowledge, but we still expect knowledge to conform to a relatively narrow set of norms before we consider it rigorous or valuable. I think infrastructure can help us do better. Rather than asking people to fit into existing systems, we can build systems that recognize different ways of generating, communicating, and evaluating knowledge while maintaining high standards of quality, transparency, and accountability.

I believe the biggest obstacle is that this kind of work requires us to give up some control. Decentralization is slower than centralization. It means accepting that communities will make different choices, develop different practices, and sometimes disagree with one another. But if our goal is a research ecosystem that is more resilient, more inclusive, and more innovative, then that diversity and decentralization are where the strength comes from.

Looking at your own organization, what are you most proud of — and what keeps you awake at night?

At this point in the interview, you probably won’t be surprised by my answer. What I’m most proud of is the people.

I feel incredibly fortunate to work alongside colleagues who care deeply about one another and about the communities we serve. Together, we are intentionally building an organizational culture where curiosity is valued over certainty, where feedback is welcomed, and where people feel safe to challenge assumptions — including our own.

I’m equally proud of our broader community. Our Champions, Club leaders, facilitators, and collaborators don’t simply use PREreview — they take what we have built, adapt it, translate it, improve it, and make it meaningful in their own contexts. To me, that’s one of the clearest signs that the work is succeeding.

What keeps me awake at night is almost the flip side of that. The more I learn, the more I realize how much there is to unlearn. Every system we inherit carries assumptions about who belongs, whose expertise counts, and what success looks like. Even with the best intentions, I’m sure that PREreview — and I personally — sometimes reproduce patterns of exclusion or create unintended harm that we don’t yet recognize.

The question I want to focus on is not “How do we avoid making mistakes?” I don’t think that’s possible. Rather, it’s, “How do we build an organization and a community that can recognize mistakes, learn from them, and repair harm when it happens?” If we are serious about creating a more open and equitable research ecosystem, then we also have to become comfortable with the idea that learning, unlearning, and changing course are essential parts of the work.

What impact has/does/will AI have on PREreview’s work?

AI hasn’t been a major focus of PREreview’s strategic work so far, and that’s been intentional. Our mission isn’t to advance AI adoption in scholarly communication. It’s to create more opportunities for people to participate meaningfully in the evaluation of research. So when we think about AI, we start with our values rather than the technology.

We recognize that AI can be used as a powerful ally. It can help people communicate more confidently in a language that isn’t their first, lowering barriers to participation. That’s why our policy distinguishes between using AI to improve grammar or sentence structure — which we don’t require reviewers to disclose — and using generative AI to develop the ideas or overall structure of a review, for which disclosure is required. Our goal isn’t to prohibit AI, but to preserve transparency and human agency.

We are also cautiously exploring whether transparent, auditable AI-assisted approaches could help connect people seeking feedback with individuals and communities who have the expertise and time to provide it. If AI can help people find one another across disciplines, languages, and communities, that’s worth exploring. But it should support human relationships and not replace human judgment.

I’m much more cautious when AI is presented as the solution to trust itself. Over the past year, I’ve been struck by how quickly we have started assigning trust to algorithms that very few people truly understand and that even fewer people can meaningfully scrutinize. The growing use — and misuse — of AI has sparked a search for new trust signals, but I worry we are once again trying to solve a social problem with a technical one.

Trust means different things to different communities, and many of the signals we have historically associated with trust in academia — prestigious affiliations, publication venues, credentials, citation records — are already shaped by longstanding biases and inequities. Encoding those assumptions into algorithms doesn’t eliminate the bias; it makes it less visible and much harder to question. I’d rather build systems that give people the information they need to make their own judgments than systems that tell them what and who to trust.

My biggest concern is that we drift toward a future where research is generated by AI, read by AI, and reviewed by AI. Peer review isn’t simply a mechanism for filtering research; it’s one of the ways researchers learn. It’s where we question assumptions, encounter different perspectives, refine our thinking, and sometimes change our minds. If we remove people from that process, we lose the opportunity to learn and unlearn together, and also the opportunity to connect as humans.

The broader questions matter, too. Access to advanced AI tools is increasingly unequal, many models are built through opaque and extractive practices, and the technology is concentrating power in the hands of a relatively small number of companies. That concerns me as much as the technology itself.

What changes do you think we’ll see in terms of the overall research infrastructure over the next five to ten years, and how will they impact the kinds of roles you’ll be hiring for at PREreview?

Over the last couple of years, one of the most encouraging shifts I’ve seen is a genuine desire among infrastructure organizations to work together more intentionally. Rather than solving similar problems in parallel, more of us are asking how we can connect our efforts and create better pathways for our communities to work across projects.

That’s exactly what we are exploring through the Open Science Coalition, a collaboration between PREreview, rOpenSci, The Carpentries, pyOpenSci, and OLS. We are experimenting with how independent organizations can sustain one another, share expertise, coordinate fundraising where it makes sense, and strengthen the communities we collectively serve. That work takes time, trust, shared governance, and difficult conversations about power. I hope more funders will recognize that those things are not peripheral to infrastructure — they are foundational to making it resilient.

I also hope we can continue growing our team at PREreview slowly and intentionally. Growing in alignment with our values means paying close attention to who we bring into the organization and what each person adds to the team. As we operate through self-management and collaborate extensively with others, we need people who are comfortable sharing responsibility and decision-making, moving fluidly across roles, supporting one another’s growth, and listening closely to the communities we serve. The skills we need will continue to evolve, but I hope the way we hire doesn’t.

Whether we’ll have the resources to do that is a real concern. I’m seeing funding for open science and open infrastructure becoming harder to secure. In the United States, the political targeting of equity, diversity, and inclusion is also making federal support increasingly difficult for organizations whose work explicitly centers equitable participation. I worry about what we lose if the infrastructure that supports openness, community, and participation becomes harder to sustain precisely when we need it most.

So, looking five or ten years ahead, I see both possibility and risk. I’m encouraged by the movement toward collaboration and shared infrastructure, but I’m also concerned by the temptation to treat technological development — particularly AI — as the primary path to innovation. AI will undoubtedly become more embedded in research workflows, but that makes investment in people even more important. We need to help researchers learn how to use these tools responsibly and critically, understand their limitations, and recognize when human judgment cannot be outsourced. We also need to address the additional burden AI-generated research and content can place on human reviewers, who may increasingly be asked to verify, question, and make sense of material produced at a speed and scale that humans simply cannot match.

Some of the problems we are trying to solve are fundamentally social, and faster or more automated solutions won’t necessarily make research better or more resilient. The future will depend in part on what we choose to value and fund now. I hope we invest not only in developing new tools, but in equipping people and communities to navigate them, while continuing the slower work of building relationships and the capacity to work across differences. That’s the future of research infrastructure I want to help shape.