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Abstract Search engine algorithms are increasingly subjects of critique, with evidence indicating their role in driving polarization, exclusion, and algorithmic social harms. Many proposed solutions take a top-down approach, with experts proposing bias-corrections. A more participatory approach may be possible, with those made vulnerable by algorithmic unfairness having a voice in how they want to be “found.” By using a mixed methods approach, we sought to develop search engine criteria from the bottom-up. In this project we worked with a group of 16 African American artisanal entrepreneurs in Detroit Michigan, with a majority female and all from low-income communities. Through regular in-depth interviews with select participants, they highlighted their important services, identities and practices. We then used causal set relations with natural language processing to match queries with their qualitative narratives. We refer to this two-step process-- deliberately focusing on social groups with unaddressed needs, and carefully translating narratives to computationally accessible forms--as a “content aware” approach. The resulting content aware search outcomes place themes that participants value, in particular greater relationality, much earlier in the list of results when compared with a standard Web search. More broadly, our use of participatory design with “content awareness” adds evidence to the importance of addressing algorithmic bias by considering who gets to address it; and, that participatory search engine criteria can be modeled as robust linkages between interviews and semantic similarity using causal set relations. 

The Latin roots of the word reparations are “re” (again) plus “parere” which means “to give birth to, bring into being, produce”. Together they mean “to make generative once again”. In this sense, the extraction processes that cause labor injustice, ecological devastation, and social degradation cannot be repaired by simply transferring money. Reparations need to take on the full sense of “restorative”: the transition to a decolonial system that can support value generators in the control of their own systems of production, protect the value they create from extraction, and circulate value in unalienated forms that benefit the human and non-human communities that produced that value. With funding from the National Science Foundation, we have developed a research framework for this process that starts with “artisanal labor”: employee-owned business and worker collectives that have people doing what they love, despite low incomes. Focusing primarily on Detroit's Black-owned urban farms, artisanal textile businesses, Black hair salons, worker collectives, and other community-based production, with additional connections to Indigenous and other communities, we have introduced digital fabrication technologies, sensors, artificial intelligence, server-side apps and other computational support for a transition to unalienated circular value flow. We will report on our investigations with the challenges at multiple scales. At each level, we show how computational supports can act as restorative mechanisms for lost circular value flows, and thus address both past and ongoing disenfranchisement. 

Long before the internet provided us with a networked digital system, music exchanges had created a global networked analog system, built of recordings, radio broadcasts, and live performance. The features that allowed some audio formations to go viral, while others failed, fall at the intersection of three domains: access, culture, and cognition. We know how the explosive growth of the hip hop recording industry addressed the access problem, and how hip hop lyrics addressed cultural needs. But why does hip hop make your ass shake? This essay proposes that hip hop artists were creating an innovation in brain-to-brain connectivity. That is to say, there are deep parts of the limbic system that had not previously been connected to linguistic centers in the combination of neural and social pathways that hip hop facilitated. This research is not an argument for using computational neuroscience to analyze hip hop. Rather, it is asking what hip hop artists accomplished as the street version of computational neuroscientists; and, how they strategically deployed Black music traditions to rewire the world’s global rhythmic nervous system for new cognitive, cultural, and political alignments and sensibilities. 

Students’ lives, both in and out of school, are full of different forms of value. Wealthy students enjoy value in the form of financial capital; their fit to hegemonic social practices; excellent health care and so on. Low-income students, especially those from African American, Native American, and Latinx communities, often lack access to those resources. But there are other forms of value that low-income students do possess. Most examples of what we will call Counter-Hegemonic Practice (CHP) in the African American community involve some mixture of Indigenous African heritage, contemporary innovation in the Black community, and other influences. Moving between these value forms and the computing classroom is a non-trivial task, especially if we are to avoid merely using the appearance of culture to attract students. Our objective in this paper is to provide a framework for deeper investigations into the computational potentials for CHP; its potential as a link between education and community development; and a more dignified role for its utilization in the CS classroom. We report on a series of collaborative engagements with CHP, largely focused on African American communities. 

The food system in the US has supported growing dominance of industrial agriculture, corporate distribution chains, and other means by which power is exerted at the expense of environmental sustainability, citizen health and wealth inequality. Economic impacts have been most damaging to low resourced and racialized communities. Online purchasing creates new opportunities--particularly in the context of the covid epidemic--but barriers may arise that are also along race and class divisions. This paper examines an initial data set for two Black led collaborative Food System projects (two urban farms and a mobile farmers market initiative), all of which are primarily staffed by African American leadership and serve a diverse set of community members with Black consumers being of the majority. While issues such as government benefit payments constitute formal economic barriers, other challenges are better illuminated through the lens of the extraction of value: the loss of community connections and increased dependency on modes of production that do not return value to the community. We define “generative production networks” as those which maximize unalienated value return rather than value extraction. We utilize this framework to examine alternative online systems to overcome these barriers. 

ABSTRACT Background: As teachers work to broaden the participation of racially and ethnically underrepresented groups in computer science (CS), culturally responsive computing (CRC) becomes more pertinent to formal settings. Objective: Yet, equity-oriented literature offers limited guidance for developing deep forms of CRC in the classroom. In response, we support the claim that “it takes a village” to develop equity-oriented CS education but additively highlight the roles of cultural experts in the process. Methods: We use a case study methodology to explore one instance of this: a collaboration between a multi-racial team of researchers, a Black cosmetologist, and a White technology teacher. Findings: Three themes supported the CRC collaboration: multi-directional relationship building, iterative engagement with culture-computing, and collaborative implementation of a hybrid lesson. Implications: As opposed to orienting broadening participation around extractive metaphors like “pipelines,” our case study constructs the metaphor of an “open village” to orient CS education toward collaborations between schools and the communities they serve. 

Culturally responsive computing (CRC) frames the localized knowledges and practices of Black, Brown, and Indigenous communities as assets for working toward racial justice in science, technology, engineering, and mathematics (STEM). A key part of CRC is the role that local communities play in designing and/or implementing curricula and technologies. Yet, there is a dearth of research on collaborating with local knowledge experts and what they think about CRC. In response, this paper details a two-year-long research project on the design and implementation of one CRC program called pH Empowered. pH Empowered uses computing to bridge Black hairstyling, chemistry, and entrepreneurship. Through a mixed-methods study of one pH Empowered professional development workshop, we show how cosmetologists, urban farmers, and librarians had diverse perspectives about how to be culturally responsive with STEM and the racial justice goal of broadening participation in STEM education. 

Removing racial bias from algorithms or social process is necessary, but alone it is insufficient. The “bias” framework tends to treat race as unwanted noise; best when suppressed or eliminated. This attitude extends to classrooms, where an attempt to be “colorblind” leads to what Pollock calls “colormute”; fearful of even mentioning race. Just as feminists developed “sex-positive feminism” in the 1970s, we now need race-positive design. Thinking about race as positive presence—as cultural capital; histories of resistance; bindings between lands and peoples—can be a generative force in computing development. Here we detail the application and assessment of African fractals, Native American bio-computation; urban artisanal cyborgs and other hybrid forms in which race-positive technology design can make important contributions. These include community-based CS education; computational support for sustainable architecture; unalienated labor in human-machine collaboration, and other forms of generative justice.