Published in Science as Culture (Ahead of Print, 2026)
The Risks of Industry Influence in Tech Research
Emerging information technologies like social media, search engines, and AI can have a broad impact on public health, political institutions, social dynamics, and the natural world. It is critical to develop a scientific understanding of these impacts to inform evidence-based technology policy that minimizes harm and maximizes benefits. Unlike most other global-scale scientific challenges, however, the data necessary for scientific progress are generated and controlled by the same industry that might be subject to evidence-based regulation. Moreover, technology companies historically have been, and continue to be, a major source of funding for this field. These asymmetries in information and funding raise significant concerns about the potential for undue industry influence on the scientific record. In this Perspective, we explore how technology companies can influence our scientific understanding of their products. We argue that science faces unique challenges in the context of technology research that will require strengthening existing safeguards and constructing wholly new ones.
The Politics of Open Infrastructures: Power, Governance, and Justice in Digital Knowledge Practices
This volume examines how openness is designed, governed, contested and lived in contemporary digital knowledge infrastructures. From open source software and internet standards, to citizen science platforms, public sector data systems and alternative computing practices, the book shows that infrastructures are never neutral technical backbones.
Who Will Keep Research Data Infrastructure Open and Running?
The scientific community must consider the longevity of open research infrastructure—why it might fail and how to prevent it.
Who Will Keep Research Data Infrastructure Open and Running?
The scientific community must consider the longevity of open research infrastructure—why it might fail and how to prevent it.
A Polycentric Governance Lens on Data Infrastructures
Funding policies for data infrastructure promote open data sharing to drive positive social impact. However, concerns regarding the long-term management of data within and across distributed infrastructures can hinder data sharing. We draw upon the concept of polycentric governance to demonstrate how collaborative practices of data curation, in preparing and maintaining data for (future) sharing, provide a solid foundation for understanding data governance within data infrastructures. Based on a qualitative case study of a distributed ecological network, we investigate the conditions under which data are managed as a shared resource by local actors to ensure the long-term (re)usability of data. We contribute to CSCW by conceptualising data curation as a complex form of governance practice with multiple centres of decision-making, each of which operates with some degree of autonomy in data infrastructures. A polycentric governance lens on data infrastructures advances the CSCW conception of data curation as a collective governance practice that can cultivate a data democracy culture within and across organisations, empower individuals to be accountable for their data, and foster a mindset shift toward decentralised data governance.
Data Feminism
Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to d...
The Drain of Scientific Publishing
The domination of scientific publishing in the Global North by major commercial publishers is harmful to science. We need the most powerful members of the research community, funders, governments and Universities, to lead the drive to re-communalise publishing to serve science not the market.
A Data Utopia for Science-of-Science
Here I want to briefly sketch out a vision for how to solve a key set of problems facing science-of-science researchers, using the relatively new idea of a ‘data trust.’ In my ideal wor…
Broadening Access to Data Science Education in High School and Higher Education through Open Source Tools, Infrastructure, and Training
Equitable data science education requires a multifaceted approach, involving high school and higher education, community involvement, and accessible tools. A renewed investment in public digital infrastructure is needed to support these efforts. Nonprofits play a crucial role in supporting these efforts, and increased representation in leadership can enhance their impact. By addressing these disparities, we can ensure a more inclusive future in data science.
Open Science Network
Reclaim scientific discourse with federated digital spaces where researchers shape their own conversations, data, and collaborations
The Current Crisis: What's Happening to Science in America
Empowering science communities with open, democratic, researcher-owned infrastructure.
We’re building communities and tech for publishing, curating, sharing, and discussing research online using ATProto and other decentralized protocols.
Empowering science communities with open, democratic, researcher-owned infrastructure.
We’re building communities and tech for publishing, curating, sharing, and discussing research online using ATProto and other decentralized protocols.
Data Feminism
A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism.
Why the Stockholm Declaration will never work
Abstract The Stockholm Declaration calls for a moral reformation of scientific publishing—replacing commercial publishers with scholar-led journals, rewarding quality over quantity and instituting independent oversight. While noble in spirit, it fundamentally misdiagnoses the disease. The crisis of science stems not from paper mills or profit motives but from systemic incentives that reward volume, novelty and prestige over validity and reliability. Non-profit ownership will not neutralize the prestige economy, sleuth-led policing cannot scale, and ‘integrity registries’ would merely replace metrics with surveillance. True reform requires rebuilding the publishing infrastructure as a public utility: publicly funded, free to publish and read, and stripped of hierarchy and financial incentives.
AI, Decomputing and the Interregnum
This paper treats AI as diagnostic for the deeper changes taking place in the existing order of things. It uses AI's alignment with both the political economy and with the dualisms that underpin it, including race, gender and anthropocentrism, to highlight the nihilistic character of the current restructuring. AI's scaling and accelerationism are taken as examples of the wider tactics being invoked by hegemonic power to maintain control under changing conditions. From this perspective, the massive build-out of data centres isn't simply a seizure of energy resources but a manifestation of an aggressive and misogynist technopolitics. The paper argues that a liberal push for digital sovereignty doesn't interrupt these dynamics but plays into the hands of emerging technofascism. It proposes instead the prefigurative tactic of 'decomputing', which draws on degrowth, deautomatisation and a convivial approach to technology. It explores decomputing as a means to mitigate both material and relational harms and as a decisive turn towards infrastructuring the common good. The paper concludes that AI is the contradiction that reveals many others, not least the gap between claims to legitimacy and the actuality of destructive violence, and proposes an alternative technopolitics of reciprocity that prioritises care and sustainability.