MyData

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...

Data Feminism

A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism.

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

Nonrivalry and the Economics of Data

(September 2020) - Data is nonrival: a person's location history, medical records, and driving data can be used by many firms simultaneously. Nonrivalry leads to increasing returns. As a result, there may be social gains to data being used broadly across firms, even in the presence of privacy considerations. Fearing creative destruction, firms may choose to hoard their data, leading to the inefficient use of nonrival data. Giving data property rights to consumers can generate allocations that are close to optimal. Consumers balance their concerns for privacy against the economic gains that come from selling data broadly.

Personal data storage is an idea whose time has come

Data Ownership as a conversation changes when data resides primarily with people-governed institutions rather than corporations.

Data Minimisation: a Language-Based Approach (Long Version)

Data minimisation is a privacy-enhancing principle considered as one of the pillars of personal data regulations. This principle dictates that personal data collected should be no more than...

Should We Treat Data as Labor? Moving Beyond “Free”

Should We Treat Data as Labor? Moving beyond "Free" by Imanol Arrieta-Ibarra, Leonard Goff, Diego Jiménez-Hernández, Jaron Lanier and E. Glen Weyl. Published in volume 108, pages 38-42 of AEA Papers and Proceedings, May 2018, Abstract: In the digital economy, user data is typically treated as capi...

What makes something data?

This is a question I posted on BlueSky on Friday 11/21/25, inspired by a talk I recently attended about evaluation of “AI” systems. I think…

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:

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.

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).

FAIRdata.ai — FAIR Data Assessment

Assess your research data's FAIRness. Automated pipeline using F-UJI + Claude AI. Free to use.

Who Even Cares About Data Ownership Anyway? - What The Function!?

Taking a look at a concept that's been talked a lot over the last few years, especially in the context of social media

FAIR Principles - GO FAIR

In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data. The authors intended to provide guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. The principles emphasise machine-actionability (i.e., the capacity of… Continue reading →

Data Refusal from Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design

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.