Intersectional Computing

other futures: tech, resistance & imagining otherwise

big tech wants to control our future, but there are other paths we can choose instead. on "other futures" we bring together leading tech researchers, organizers, critics, and storytellers to help us imagine what more liberatory and human-centered tech futures could look like—and how we can build them together. brought to you by DAIR and the All Tomorrows Institute.

Black Software

Black Software: The Internet and Racial Justice, From the Afronet to Black Lives Matter is a 2019 American book that sets out to understand Black Lives Matter through the six-decade history of racial justice movement organizing online.

Movement Data Science: Practices for Working in Solidarity with Social Justice Efforts

Although many data scientists are eager to promote social justice, their efforts often fall short, and in some cases even exacerbate existing injustices. This gap between intentions and impacts follows from issues in how data scientists conceptualize their role in social justice efforts: they typically act as technicians, aiming to develop technical tools that will produce social justice. This default role generally results in depoliticized techno-fixes that fail to produce substantive changes. In this paper, we contribute “movement data science” as a framework to guide data scientists in taking on more productive and equitable roles in social justice efforts. Our framework is inspired by movement lawyering, a practice used by lawyers to situate themselves in grassroots social movements. Movement data science suggests that data scientists should ground their efforts to advance justice in sustained and solidaristic relationships with social movements. We contribute a process with four essential practices to help data scientists build these relationships and identify roles to play within specific social justice efforts. Movement data science does not provide a simple blueprint for data scientists to follow, but it can help them support social justice movements in substantive ways that go beyond attempting to solve injustices with technical tools.

DJS F26 W03A Data Origins

DATA ORIGINS JMW Turner, The Slave Ship: Slavers Throwing overboard the Dead and Dying—Typhoon coming on (1840)

Solidarity Infrastructures

Solidarity Infrastructures is a class that brings together creative practitioners to investigate, strategize, upskill, and dream toward alternative socio-technological systems.

Origin Stories: Plantations, Computers, and Industrial Control

The proto-Taylorist methods of worker control Charles Babbage encoded into his calculating engines have origins in plantation management.

Toward People’s Community Control of Technology: Race, Access, and Education

This field review explores how the benefits of access to computing for racialized and minoritized communities has become an accepted fact in policy and research, despite decades of evidence that technical fixes do not solve the kinds of complex social problems that disproportionately affect these communities.

Challenging Ableism: A Critical Turn Toward Disability Justice in HCI

A reflection on our learnings from the CHI 2022 "Dreaming Disability Justice in HCI" workshop, and why we continue to call for disability justice, despite the limitations of how we practice it within academia and industry.

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.

Focusing on community technology — Eskahlay

A waterwheel, a protocol, and the case for technology that communities can own.

Could the Web Have Been Created in Yoruba Land?

If Not This... by lola odelola_Issue #1 Could the Web Have Been Created in Yoruba Land? “Universal access to a large universe of documents” What if the web was created in 1980s Lagos, Nigeria within markets as a way for vendors to share and access wholesale produce prices? Or what if it was c...

Could the Web Have Been Created in Yoruba Land?

If Not This... by lola odelola_Issue #1 Could the Web Have Been Created in Yoruba Land? “Universal access to a large universe of documents” What if the web was created in 1980s Lagos, Nigeria within markets as a way for vendors to share and access wholesale produce prices? Or what if it was c...

CSDL | IEEE Computer Society

Informatics of the Oppressed

An inquiry into the rich history of radical experiments to reorganize information.

Reflective design

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Algorithmic Monocultures in Hiring - Stanford Digital Economy Lab

Many employers screen job applicants with algorithms built by the same few algorithm vendors. We hypothesize that algorithmic monoculture leads to the same individuals and members of the same racial groups facing rejection. We acquire and analyze a novel dataset of 3 million applicants submitting 4 million applications where all the applications are screened by algorithms built by the same vendor.

The Web Is Being Made Accessible for AI, Not People

Jonathan Zong and Frank Elavsky critique how AI-driven infrastructure changes obscure accessibility and reveal whose needs society chooses to prioritize.