For civil society, rights advocacy is no longer confined to physical spaces, legislative negotiations, or the streets. As algorithmic decision-making systems, predictive data models, and computational infrastructures shape public life, rights, and visibility, we must also intervene in data and code. At İhtimam Association, this is why we embrace algorithmic advocacy for care as an essential field of practice.
We approach care not merely as an individual burden shouldered within households, but as the foundational infrastructure that sustains people, institutions, and living ecosystems. From this foundation, we raise a central question: What happens when care is missing from datasets and computational models?
To open this question to dialogue, highlight invisible labor, and imagine alternative data futures, our first quarterly zine issue, “If care is missing from the data?”, is out now.
What Does Data Actually Record?
Artificial intelligence and automated systems do not begin with a blank page; they learn from what societies have historically chosen to record, measure, and institutionalize. Yet the vast majority of life-sustaining care unfolds quietly in daily rhythms, away from official dashboards: a midnight support message, holding space during grief, cooking a meal, mutual neighborhood aid, or the uncounted emotional labor holding teams together.
Digital systems effortlessly document salaries, job titles, patents, transaction volumes, and financial indicators. However, they struggle to record who checked in, who mediated tension, and who repaired relationships. This absence in data is not an accidental technical bug; it mirrors institutional, economic, and social choices that have long devalued care work.
The Care Data Paradox
When care is missing from data, a technocratic reaction often emerges: “Let’s turn every act of care into data!”
Yet care is contextual, relational, and deeply human. Forcing every relational gesture into KPIs, metrics, and tracking databases risks subjecting care to market extraction and surveillance.
Algorithmic advocacy for care does not seek to quantify every human encounter. Instead, it demands that data models, technology, and economic systems be redesigned around interdependence, vulnerability, and an ethics of care.
First Issue: “If care is missing from the data?”
The inaugural issue of our quarterly zine explores the structural absence of care across data worlds through a relational visual narrative. We are also glad to share that this edition is featured in two international archival selections:
MozFest Zine Library (October 28–30): Selected for the collaborative collection curated by AIxDESIGN and the Mozilla Festival in Barcelona.
National Library of the Netherlands (KB – Koninklijke Bibliotheek): Exhibited as part of a physical showcase in The Hague from October 29 through January 31.
Practicing Algorithmic Advocacy Together
Algorithmic advocacy cannot stop at mitigating technical harms after deployment. We must actively intervene in the narratives, archives, and datasets that train AI systems today. We focus on these actionable practices:
Developing open, community-governed alternative datasets with care awareness.
Archiving lived experiences and oral histories before they fade.
Creating shared vocabularies and taxonomies that reflect care realities rather than market metrics.
Recognizing the invisible contributions that hold communities and systems together within a rights-based framework.
