Neoliberal capitalism - the favoring of privatization, marketization, and deregulation of public resources - is hegemonic in education. It shapes our institutions and everyday life, including educational practices. The increasing push for market driven computing curriculum and large tech companies' involvement in research grants and educational programs are some examples of neoliberal influences in CS education. It is not only industry and industry-backed not-for-profits such as Code.org that reify neoliberal agendas, but in many cases, our very own communities, educational institutions, and curricula. Thus, a critical and reflective examination of our educational practices is necessary. In this Birds-of-a-Feather (BoF) session, we aim to conduct reflections and discussions on the role and influence of neoliberal capitalism in computing education. We will explore 1) the influence of deregulation, 2) public-private partnerships, 3) state-subsidized corporate wealth accumulation, and 4) centralization on pedagogy, research, and academic "success". We will discover reflective questions and practices that could help us critically examine our roles and responsibilities as computing educators and professionals. Eventually, we hope to begin a larger conversation and form a community to develop collective strategies and pedagogical ideologies to resist neoliberal influences, reimagine alternatives, and repair damages caused by neoliberal computing education.

Recent years have witnessed an interesting phenomenon in which users come together to interrogate potentially harmful algorithmic behaviors they encounter in their everyday lives. Researchers have started to develop theoretical and empirical understandings of these user-driven audits, with a hope to harness the power of users in detecting harmful machine behaviors. However, little is known about users’ participation and their division of labor in these audits, which are essential to support these collective efforts in the future. Through collecting and analyzing 17,984 tweets from four recent cases of user-driven audits, we shed light on patterns of users’ participation and engagement, especially with the top contributors in each case. We also identified the various roles users’ generated content played in these audits, including hypothesizing, data collection, amplification, contextualization, and escalation. We discuss implications for designing tools to support user-driven audits and users who labor to raise awareness of algorithm bias.

Algorithmic systems help manage the governance of digital platforms featuring user-generated content, including how money is distributed to creators from the profits a platform earns from advertising on this content. However, creators producing content about disadvantaged populations have reported that these kinds of systems are biased, having associated their content with prohibited or unsafe content, leading to what creators believed were error-prone decisions to demonetize their videos. Motivated by these reports, we present the results of 20 interviews with YouTube creators and a content analysis of videos, tweets, and news about demonetization cases to understand YouTubers' perceptions of demonetization affecting videos featuring disadvantaged or vulnerable populations, as well as creator responses to demonetization, and what kinds of tools and infrastructure support they desired. We found creators had concerns about YouTube's algorithmic system stereotyping content featuring vulnerable demographics in harmful ways, for example by labeling it "unsafe'' for children or families -- creators believed these demonetization errors led to a range of economic, social, and personal harms. To provide more context to these findings, we analyzed and report on the technique a few creators used to audit YouTube's algorithms to learn what could cause the demonetization of videos featuring LGBTQ people, culture and/or social issues. In response to the varying beliefs about the causes and harms of demonetization errors, we found our interviewees wanted more reliable information and statistics about demonetization cases and errors, more control over their content and advertising, and better economic security.

The Negro Motorist Green Book was a publication that offered resources for the Black traveler from 1936 to 1966. More than a directory of Black-friendly businesses, it also offered articles that provided insights for how best to travel safely, engagement with readers through contests and invitations for readers to share travel stories, and even civil rights advocacy. Today, a contemporary counterpart to the Green Book is Black Twitter, where people share information and advocate for their community. By conducting qualitative open coding on a subset of Green Book editions as well as tweets from Black Twitter, we explore similarities and overlapping characteristics such as safety, information sharing, and social justice. Where they diverge exposes how spaces like Black Twitter have evolved to accommodate the needs of people in the Black diaspora beyond the scope of physical travel and into digital spaces. Our research points to ways that the Black community has shifted from the physical to the digital space, expanding how it supports itself, and the potential for research to strengthen throughlines between the past and the present in order to better see the possibilities of the future.

The Negro Motorist Green Book was a tool used by the Black community to navigate systemic racism throughout the U.S. and around the world. Whether providing its users with safer roads to take or businesses that were welcoming to Black patrons, The Negro Motorist Green Book fostered pride and created a physical network of safe spaces within the Black community. Building a bridge between this artifact which served Black people for thirty years and the current moment, we explore Black Twitter as an online space where the Black community navigates identity, activism, racism, and more. Through interviews with people who engage with Black Twitter, we surface the benefits (such as community building, empowerment, and activism) and challenges (like dealing with racism, appropriation, and outsiders) on the platform, juxtaposing the Green Book as a historical artifact and Black Twitter as its contemporary counterpart. Equipped with these insights, we make suggestions including audience segmentation, privacy controls, and involving historically disenfranchised perspectives into the technological design process. These proposals have implications for the design of technologies that would serve Black communities by amplifying Black voices and bolstering work toward justice.