Amidst calls for public accountability over large data-driven systems, feminist and indigenous scholars have developed refusal as a practice that challenges the authority of data collectors. However, because data affect so many aspects of daily life, it can be hard to see seemingly different refusal strategies as part of the same repertoire. Furthermore, conversations about refusal often happen from the standpoint of designers and policymakers rather than the people and communities most affected by data collection. In this article, we introduce a framework for data refusal from below —writing from the standpoint of people who refuse, rather than the institutions that seek their compliance. Because refusers work to reshape socio-technical systems, we argue that refusal is an act of design and that design-based frameworks and methods can contribute to refusal. We characterize refusal strategies across four constituent facets common to all refusal, whatever strategies are used: autonomy , or how refusal accounts for individual and collective interests; time , or whether refusal reacts to past harm or proactively prevents future harm; power , or the extent to which refusal makes change possible; and cost , or whether or not refusal can reduce or redistribute penalties experienced by refusers. We illustrate each facet by drawing on cases of people and collectives that have refused data systems. Together, the four facets of our framework are designed to help scholars and activists describe, evaluate, and imagine new forms of refusal.
Indigenous Data Sovereignty (DDN3-A11)
This article explores Indigenous data sovereignty, identifies some of the data-related challenges faced by Indigenous Peoples and highlights the work done to overcome these challenges.
Feminist Data Manifest-No
1. We refuse to operate under the assumption that risk and harm associated with data practices can be bounded to mean the same thing for everyone, everywhere, at every time. We commit to acknowledging how historical and systemic patterns of violence and exploitation produce differential vulnerabilities for communities.
Data Feminism
A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism.
Information Access of the Oppressed: Freirean Design for Emancipatory Information Access
Online information access (IA) platforms are targets of authoritarian capture. We explore the question of how to safeguard our platforms and ensure emancipatory outcomes through the lens of Paulo Freire's theories of emancipatory pedagogy. Freire's theories provide a radically different lens for exploring IA's sociotechnical concerns relative to the current dominating frames of fairness, accountability, and transparency. We make explicit, with the intention to challenge, the technologist-user dichotomy in IA platform development that mirrors the teacher-student relation in Freire's analysis. By extending Freire's analysis to IA, we critique the technologists-as-liberator frame where it is the burden of (altruistic) technologists to mitigate the risks of emerging technologies for marginalized communities. Instead, we advocate for Freirean Design whose goal is to structurally expose the platform for co-option and co-construction by community members in aid of their emancipatory struggles.
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...
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.
Preventing AI extractivism: the case for braiding indigenous data justice with ABS for stronger AI data governance
Artificial-intelligence systems are rapidly reproducing colonial extractivism by harvesting Indigenous linguistic, biometric, geospatial, and ecological data without consent, compensation, or accountability. Biotechnology offers a blueprint for curbing such practices: the Convention on Biological Diversity and its Nagoya Protocol obligate users of genetic resources to obtain Prior Informed Consent, negotiate Mutually Agreed Terms, and share benefits fairly. No comparable framework restrains the digital appropriation that underpins many AI products. Consequently, corporations and states monetize Indigenous knowledge systems under the banners of “open data” and “scientific neutrality,” eroding rights affirmed in the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP). In response to this rising risk of AI extractivism, we make the case for a binding, sui generis ABS protocol for AI data governance. First, through a series of case studies we demonstrate that AI extraction mirrors the colonial and biopiracy controversies that originally triggered Access‑and‑Benefit‑Sharing (ABS) rules in biotechnology. Second, we translate those rules into a digital register by braiding two Indigenous data‑governance frameworks—OCAP® (Ownership, Control, Access, Possession) and the CARE Principles (Collective Benefit, Authority to Control, Responsibility, Ethics)—inside the ABS triad of consent, terms, and benefit‑sharing. The resulting model grounds technical safeguards in relational accountability and Indigenous legal orders. Such an instrument would compel transparent negotiations with Indigenous rights‑holders, assign enforceable authority over data across the AI lifecycle, and require equitable redistribution of the economic value generated by models trained on Indigenous data. Embedding ABS principles into AI governance offers a decolonial pathway that centers Indigenous epistemologies, promotes ethical foresight, and transforms AI from a vehicle of digital colonialism into a space for algorithmic justice.
Indigenous Knowledges and Data Governance Protocol — Indigenous Innovation Initiative
Between March 2020 and March 2021, the Indigenous Innovation Initiative co-created the Indigenous Knowledges and Data Governance Protocol with the community, to guide how we collect and use Indigenous Knowledges and Data. Click on the image below to learn more about this Protocol. Since then, t
Living in Data: A Citizen's Guide to a Better Information Future (Paperback)
Jer Thorp’s analysis of the word “data” in 10,325 New York Times stories written between 1984 and 2018 shows a distinct trend: among the words most closely associated with “data,” we find not only its classic companions “information” and “digital,” but also a variety of new neighbors—from “scandal” and “misinformation” to “ethics,” “friends,” and “play.”To live in data in the twenty-first century
MyData
The human-centric approach to data is aimed at a fair, sustainable, and prosperous digital society. In such a society, people get value from their data and set the agenda on how it is used. And for organisations, the ethical use of data is always the most attractive option.
The Limits of Data
Policymakers want to make decisions based on clear data, but important factors are lost when we rely solely on data. A philosopher writes:
Governing by dismantling: tech oligarchy and the stifling of public data infrastructure
Published in Science as Culture (Ahead of Print, 2026)
Animikii: Indigenous Technology for an Equitable Future
Animikii empowers Indigenous communities with culturally informed technology solutions like Niiwin—our groundbreaking tool for Indigenous data sovereignty and community empowerment.
Can “Conscious Data Contribution” Help Users to Exert “Data Leverage” Against Technology Companies?
Tech users currently have limited ability to act on concerns regarding the negative societal impacts of large tech companies. However, recent work suggests that users can exert leverage using their role in the generation of valuable data, for instance by withholding their data contributions to intelligent technologies. We propose and evaluate a new means to exert this type of leverage against tech companies: "conscious data contribution" (CDC).
‘No & ...’ : A Forum on Technological Refusal - Home
This forum begins from the idea that refusal is, among other things, a rejection of one’s current relationship to technology (as an individual and/or as part of a collective) and a simultaneous commitment to another way of being in the world. The ‘no’ is accompanied by a ‘yes’ to another path. In this sense, refusal demands a careful articulation of what needs to change as well as a vision for a future that can (and should) be worked towards.
Treating data like land — data sovereignty in the AI age - ICT
Artificial intelligence front and center at North America’s largest Indigenous tech conference
