7 Digital Redlining, Minimal Computing, and Equity

Digital Redlining

Digital redlining takes its name from the historical practice in housing and real estate in the United States of redlining, meaning that primarily black residents would be denied loans, insurance policies, and other resources in their neighbourhoods, leading to depreciating values of their homes, blight, and eventually eviction, leaving the area ripe for gentrification and development. This is a distinctly American phenomenon that started during the Jim Crow era (the late 1800s to the 1960s) but by no means was limited to the South and in fact was more acutely felt in urban areas.2

Digital redlining, then, is the systematic denial or the provision of low levels of service, such as providing lower broadband speeds, charging more for the same services offered at lower prices to wealthier, whiter areas, and offering little high-quality mobile coverage (Cornish, 2015; Flahive, 2020; Jackson, 2017; Tveten, 2016). As Gilliard and Culik (2016) put it,

digital redlining is not a renaming of the digital divide. It is a different thing, a set of education policies, investment decisions, and IT practices that actively create and maintain class boundaries through structures that discriminate against specific groups. The digital divide is a noun; it is the consequence of many forces. In contrast, digital redlining is a verb, the “doing” of difference, a “doing” whose consequences reinforce existing class structures. In one era, redlining created differences in physical access to schools, libraries, and home ownership. Now, the task is to recognize how digital redlining is integrated into [educational technology] to produce the same kinds of discriminatory results. Armed with the history of redlining, and understanding its digital resurrection, we glimpse the use of technologies to reinforce the boundaries of race, class, ethnicity, and gender. Our experience is that this problem is seldom recognized as an urgent educational issue. (para. 13)

In other words, in the same way that blacks who could afford a loan to buy a home but were denied the opportunity to do so because of redlining, those subjected to digital redlining are denied services or can only access restricted services based upon the confluence of identity and geography.

This kind of restricted and unequal access disproportionately affects communities of learners already labelled the least likely to succeed in the United States: urban community college students, rural students, tribal college students, and so on. For example, when the pandemic necessitated the shutdown of tribal colleges and universities, the impact of digital redlining was felt acutely, with tribal colleges and universities facing aging infrastructure, little experience with online learning, and students widely dispersed with little to no access: “Internet providers are working with local communities like Standing Rock to expand access, but in Indian Country the starting line is far behind the rest of the country. Moreover, there’s little to no profit motive for improving connectivity on reservations that are situated in some of the poorest counties in the nation” (Shreve, 2020, para. 20).

Although students might have access to the necessary hardware (desktop, laptop, tablet, smartphone), nonetheless they are less likely to have adequate access to the underlying digital infrastructure necessary to participate fully in online or hybrid classes. A study of the success rates of online versus face-to-face courses at community and technical colleges shows that “at-risk” students do demonstrably worse in online courses, but the study barely notes that the digital divide and digital redlining might have affected students’ success rates (Xu & Jaggars, 2014, p. 636). So a student returning to her home on an Indian reservation would have limited access to the digital infrastructure necessary to participate fully in online courses.

Access to technology is not the only consideration for creating truly equitable and inclusive learning.3 Even if students do have reliable access to the internet, their experience of it is often different (see Noble, 2018). As put by Gilliard (2017, para. 7),

we might think about digital redlining as the process by which different schools get differential journal access. If one of the problems of the web as we know it now is access to quality information, digital redlining is the process by which so much of that quality information is locked by paywalls that prevent students (and learners of all kinds) from accessing that information. We might think about digital redlining as the level of surveillance (in the form of analytics that predict grades or programs that suggest majors to students). We also might think about digital redlining to the degree that students who perform Google searches get certain information based on the type of machine they are using or get served ads for high-interest loans based on their digital profile (a practice Google now bans). It is essential to note that the personalized nature of the web often dictates what kind of information students get both inside and outside the classroom.

Our policies and practices in higher education have thus reinforced racial and socio-economic stratification: we are practising digital redlining whether we mean to or not. In the following section, I outline how digital redlining is embedded in the systems in which and with which we teach.

The Technologies with Which We Teach

Institutions of higher education in the United States have invested in certain kinds of technologies over the past decade for online learning: large, complicated learning management systems, high-quality video creation and streaming platforms, invasive proctoring and other monitoring solutions, as well as agreements with data-hungry companies such as Google, Blackboard, and Panopto. For a student who lives in an area where digital redlining is prevalent, these tools do not, in fact, improve the learning experience, instead impeding it and thus engaging in digital redlining. Many of these tools share a need for bandwidth and lots of computing power. This is compounded by other circumstances that inform teachers’ decisions about how to make course materials available. For example, worries about intellectual property can mean that they turn off students’ ability to download a lecture video, meaning that some students then have to watch the lecture video in a place where they have a good signal on their phones, rather than being able to download it and then watch it at home. This has become a health and safety issue under COVID-19 since students have been forced to spend extended amounts of time outside their homes in order to participate in or access the learning materials (see, e.g., Salinas, 2020).

Another example is the sudden ubiquitous use of the video-conferencing platform Zoom for distance education in many higher education institutions in the United States. Privacy and security issues aside (but certainly not unimportant), as well as the pedagogical value of just delivering a lecture via video synchronously rather than in a classroom, students with older computers with inadequate processing capabilities have found themselves unable to select a virtual background during a class meeting and thus might have been put in revealing situations in which they are not comfortable. Recently, a black middle-school student was suspended for having what was clearly a toy gun in the background of his room while participating in virtual learning (Low, 2020). Although this was a case in the K–12 system, it highlights the danger of surveillance that racialized learners face at all levels, leaving them vulnerable to and uncomfortable with the potential policing of their surroundings. In other cases, professors require that students have their cameras on the entire time that they are meeting synchronously, so students with lower bandwidth experience constant delays and other issues during the course, significantly altering their learning experience compared with that of classmates with access to adequate hardware and bandwidth.

Students in authoritarian countries are also at risk on video-conferencing platforms such as Zoom. Recent events involving Chinese dissidents and Hong Kong residents (Soo, 2020) put in stark relief the level of surveillance and risk that Chinese students might be under and fearful of, forcing them to participate in discussions that might be interpreted as “public dissent” or creating a digital trail for documentation that can be intercepted by government officials and used against the students and their families. Although access to information is limited by the government, the students also have to worry about their and their families’ physical safety when engaging in course materials and discussions. Also, a student who returns home to China is likely to experience digital redlining because of the government’s censorship of part of the internet regularly used and assigned to students in the United States (Li & Lahiri, 2020).

These examples show how our approach to online education more generally, and our shift to distance delivery during COVID-19 more specifically, are in fact digital redlining in practice. Faculty members and administrators are reinforcing, through collective, institutional decisions, as well as individual decisions (shaped by the available technologies and the policies that institutions have put in place), the inequities that they claim to be working to overcome.

Who Else Is Being Watched?

Digital redlining also encompasses issues, as seen above, of surveillance: “Digital redlining arises out of policies that regulate and track students’ engagement with information technology” (Gilliard & Culik, 2016, para. 10; emphasis added). Communities subjected to digital redlining are also subjected to higher levels of surveillance generally through the increased presence of cameras, more police officers, racial profiling, and other forms of invasion of privacy. Most recently, for example, it has been revealed that the drugstore chain Rite Aid secretly installed facial recognition cameras and software in its stores, which primarily serve black and Latino populations (Gurshgorn, 2020).

Through our choices of ed tech tools, our universities and colleges further reinforce this mass surveillance culture in the name of accountability, disparately affecting marginalized and vulnerable populations by subjecting them to scrutiny and ingesting them into systems that lack transparency about what is done with their personal information. In his provocatively titled “Against Cop Shit,” Moro (2020) outlines all of the ways that ed tech polices students’ behaviour, ed tech that institutions and individuals have chosen to use, ed tech that students are forced to engage with, ed tech that monitors and reports their every virtual move. As Watters (2020, para. 7) puts it, “we need to dismantle the surveillance ed-tech that already permeates our schools.” COVID-19 has accelerated the adoption of enterprise solutions that specialize in monitoring students, or the use of already-present but little-known surveillance features, such as proctoring software or usage metrics (for more on this, see Chapter 3 of this volume).

Another form of digital redlining in the news because of COVID-19 is grading assigned by algorithms according to socio-economic factors as well as past performances on assessments based upon historical results of people with the same socio-economic profile. Cases in the United Kingdom, where students from underperforming schools had their A-levels downgraded (A-levels, 2020), the United States, and elsewhere when International Baccalaureate (IB) scores were determined by an algorithm that disproportionately affected low-income students negatively (Asher-Shapiro, 2020) show how algorithms are not neutral and can affect students’ future access to higher learning. It is outside the scope of this chapter to argue against high stakes testing of any form (see Hagopian, 2014), but this new form of algorithmic oppression is a clear threat that will affect students moving forward.

Another example of algorithmic surveillance and its impact on students is a student heading back home, because of remote studies, in a low socio-economic area who would receive different Google search results because of the zip code and how the student accesses the internet. The Google algorithm makes certain assumptions about the student because of those factors, which then affect the search results. Without the support of the physical library or zip code of their physical campus, such students are at risk of using less relevant resources for projects and assignments. Even while using a private or incognito window for browsing, without the use of an expensive VPN (virtual private network) (again, this assumes that the students and their families understand what these tools are and why they are important as well as how to use them), a student using public wi-fi would be subjected to greater surveillance, less privacy, and a different internet experience based upon the location and wi-fi access.

Critical digital pedagogy demands that these factors be considered when designing courses. But beyond raising questions and providing flexibility for individual students, there has been little effort to think systematically about how to address digital redlining. This is where critical digital pedagogy is confronted with the reality of the systems in which we work: the framework discourages this kind of discourse, trapped in thinking about accessibility through the lens of big ed tech. Proposed here is a completely different approach that critical digital pedagogues can take to address the issues of digital redlining.

Minimal Computing

The concept of minimal computing can be helpful in rethinking the reliance on bandwidth and computationally demanding, as well as invasive, enterprise solutions for online learning. Minimal computing (see Gil, 2015) is a movement that grows out of digital humanities, concerned with the environmental impact of large-scale computational initiatives as well as the accessibility, inclusivity, maintenance, and long-term viability of certain large digital humanities projects. How do those who do not have ready access to stable broadband and computational power access digital humanities work done with their intellectual property, history, and archives if that work is locked behind a paywall or on a platform that requires high levels of computing power and bandwidth? Such questions are focused primarily on making research accessible, but often the products can be powerful educational resources if they are more accessible.

Sayers (2016a, para. 4) takes it a step further and asks that we consider minimal design when thinking about minimal computing:

Following the Unix philosophy of DOTADIW (“Do One Thing and Do It Well”), minimal design applauds and even fetishizes simplicity; it boils practice down to necessities. The Jekyll site generator is an obvious example: “No more databases, comment moderation, or pesky updates to install—just your content.” From a technical perspective, this design strategy entails responsiveness across devices, optimization, few dependencies, and an investment in plain text, unembellished layouts, and basic templates. Changes to the style and structure of a project should be few and far between. Both conceptually and practically, design should be in the background; it should not be pronounced or assertive. Sites and software should not be feature-rich, either. While a given project may require some programming (e.g., in Ruby), technical details and configurations are rendered less significant than the message or substance of composition: “just your content.”

Sayers goes on to explain how minimal computing and design can accrue net gains on multiple fronts: maximum access, maximum accessibility, maximum justice, minimal connectivity, minimal surveillance, minimal externals, among others (see Sayers, 2016b).4

Minimal computing runs completely contrary to how institutions typically have approached online learning. There is nothing minimal about video-conferencing tools, proctoring software, a learning management system (LMS), or lectures streamed as videos. One of the most powerful aspects of a minimal computing approach is asking both creators and users (and in this case faculty members and students) to break open the black box of the software and have a better understanding of how it works as well as how to adapt, adopt, and, most importantly, become creative. Faculty members and students gain a deeper and more meaningful understanding of the tools used, embracing the learning opportunities that this approach presents and reflecting critically on our tech use and reliance, the unseen infrastructure to which some are lucky enough not to have to pay attention. Minimal computing is also minimally invasive because, when asking about what faculty members and students need, the answer is not increased violations of students’ privacy.

Why haven’t concepts of minimal computing had an impact on online learning? Unfortunately, digital humanities and online learning are rarely in conversation with one another, the two movements developing in parallel to one another but rarely intersecting. An early critique of digital humanities was that it was part of the neo-liberal turn in higher education (Allington et al., 2016) and conflated with MOOCs (massive open online courses) (Svensson, 2016). These projects were also developed in different university silos, centres of digital humanities, and offices of online learning. Digital humanists, instructional designers, and IT staff attend attended different conferences, published and read different journals, and developed independent social and professional networks. COVID-19 has provided a space in which to confront these issues critically and put them in conversation with each other and with a larger audience.

Minimal Computing and Online Learning

The old-school approach to distance online learning (using the postal service, telephones, etc.) shares a couple of important similarities with our current approach to online education: the careful building of the course ahead of time and the importance of the design. However, both approaches still disconnect the student from the making of learning, from the messiness of the process. Part of the selling points of many ed tech solutions is that they are seamless and efficient, the same promises of the slickly designed textbook. One cannot and should not ignore altogether the presence of technology, but minimal computing seeks to make the technology visible and legible. It seeks to break open the black boxes of technology; even though print is still ubiquitous, most people don’t understand the process and production of the printed work, much like an LMS elides the process and production of the course.

What is most interesting about taking a minimal computing approach to online learning is that the process and production are transparent and clear. How do faculty members make the technology more visible and accessible and, through that process, make the learning more engaging and purposeful? What do students really need? They need learning materials, engagement, and a form of assessment. How might this be done in a minimal computing environment that makes more visible the process of learning? This is another area of intersection with critical digital pedagogy in which students and faculty members have an opportunity to engage with both the how and the why of the education in which they are participating.

Although engagement with the process of learning might be easier while taking a minimal computing approach, minimal computing presents a challenge to rethink other forms of engagement: student to student, student to content, and student to faculty. How do faculty members engage with students, the materials, and each other? Taking a community-based approach can provide a balanced way for students to engage based upon their own material situations and make the material relevant and accessible through their culture and community. Have them share their stories with their classmates through letters, for example. Students become active partners in their learning by stripping down the materials to their bare essentials within their communal and cultural contexts. Minimal computing takes the end user into consideration, and in the case of education the “end user” is the community where the student lives.

This is where traditional distance education fell short: it did not take a minimal computing approach to engagement, instead focusing almost exclusively on content delivery and assessment pieces, nor did it work to make the mechanics of learning more visible. Certainly, instructors designed activities for students to engage with the materials but did not offer many opportunities for the social-emotional elements of learning that are so important. Conversely, our current efforts in distance and online learning sink billions of dollars into expensive, bloated, enterprise solutions that only simulate engagement in many cases and create barriers for some to be able to participate at all.

Using the principles of minimal computing allows students to take more control of their privacy, minimizing surveillance by the institution to monitor and in fact dictate their engagement, allowing students to decide for themselves the safest ways to engage with their communities and contexts, within the larger culture of mass surveillance of black and brown bodies. By removing the curtain, students can engage more meaningfully and evade other forms of surveillance to which they are subjected.

Taking the minimal computing approach to online learning also forces instructors to rethink their courses and pedagogical practices; one reason that many ed tech solutions are so complex and bandwidth hungry is that faculty members simply want to recreate online what they do in the classroom. What do you really need? Instead of thinking that online learning is just a transfer, they have to adapt their practices, their pedagogies, their expectations, and, for some, their egos. No longer the sole arbiters of engagement, faculty members must take a step back and enable their students to be their own arbiters of engagement. It would also require faculty to re-evaluate the perceived need to monitor their students via technology. Even as a thought experiment for faculty members, to ask if you had minimal digital tools, what would your course look like? can be a meaningful and powerful way to get them to think about online course design differently.

One important criticism of this approach is how do faculty members ensure academic integrity? That is, how do we know that our students are actually doing the work? Swauger (2019, para. 21) addresses this reliance on the surveillance, as well as the criminalization, of our students, particularly those who are victims of digital redlining. His recommendation is to “design assessments, online or in person, that draw from personal experience or require students to apply concepts in unique contexts.” Lang (2013) examines cognitive theory and concludes that, to dissuade students from cheating, faculty members should design activities and assessments that foster intrinsic motivation, aim for mastery, are lower stakes, and instill self-efficacy. As described, taking a minimal computing approach does all of these things and does them well. Although cheating and academic dishonesty might never be completely eliminated, this argument is a red herring for dismissing a minimal computing approach.

There have been a number of interesting innovations when it comes to taking such an approach during COVID-19, specifically in courses that have labs or other hands-on components. Anecdotally, I have seen and heard of instructors asking students to purchase inexpensive science kits to perform experiments at home or engaging students by asking them to perform experiments with materials that they have at their disposal at home or in their environment. Cordell (2020) took this approach with his course that was supposed to take place in a letterpress studio at Northeastern University, but instead he had students use materials that they had on hand as well as the minimal computing program Twine to create interactive publications on the web. These courses distilled their learning goals and activities using the question what do you really need? and had students use their own agency and ability to achieve the learning goals.

Other Benefits of Minimal Computing

Examples of a minimal computing approach intersecting with disability and accessibility to online learning are outlined by Friedner et al. (2020). They were inspired to write about their experiences because they “each had profound online teaching and learning experiences in the past eight weeks via text alone” (para. 3). Taking a minimal computing approach, they explore “the possibilities offered through ‘platforming down,’ or paring down the technology we use for online classes” (para. 2). The platform for one of the courses? A listserv (an email sent and received by a group of people who sign up for it). The authors emphasize that “the presumption that speech is inherently superior to other modes of communication and interaction has directly led (and often still does) to the dehumanization of disabled and neurodiverse people” (para. 27). How much of our approach to online learning, which has been facilitated by bloated ed tech platforms, actually has been informed by our internalized ableism? A minimal computing approach can also help us to understand better pedagogical biases for the benefit of all of our learners.

What would this mean to students, particularly those subjected to digital redlining? They could focus on the course materials and learning outcomes rather than on their own safety and whether or not they can engage and participate effectively in the course. If the technological barriers caused by digital redlining are removed, then students are more likely to engage in an equitable and safe educational experience.

What Would Minimal Computing Mean Institutionally?

As Gil (2015) points out, just because something is minimal for one person does not make it minimal for all people. Good-faith efforts by individual instructors to take digital accessibility into consideration through the practice of minimal computing or other approaches are nonetheless hamstrung by the infrastructure and support structures in place in our institutions. The institutions buy the high-bandwidth enterprise solutions and then provide support staff who have the expertise to support faculty members in using those solutions. Our institutions are set up to resist and discourage a minimal computing approach.

Imagine that, instead of paying millions for enterprise solutions and the people to support them, the institution invests in more and different people who are experts in learning design and minimal computing to assist faculty members in building their distance courses differently. Instructors are already struggling with the technology provided, largely because it is bloated, complex, and unintuitive, so why not embrace a more inclusive and environmentally friendly approach and support a minimal computing approach? What if institutions did not have to pay not only for the software programs but also for the server space to run them effectively, instead relying on lower-bandwidth and less complex digital and technical solutions? What if most faculty members did not require the most up-to-date and powerful computers to run their online courses (understanding that there would be those doing research and teaching courses that require more processing power) because their minimal computing courses would be accessible even with basic software programs and processors? And what if we invested in more staff who would support instructors pedagogically?

Taking this approach would mean that instructors would have to shift their thinking fundamentally about course design and that institutions would have to rethink radically how they provide hardware, software, and support. Issues of invisible labour, sustainability, and other kinds of work that go into maintaining these enterprise solutions would also be addressed. Which kinds of courses could be created and which levels of creativity could be achieved by redirecting money into hiring, supporting, and paying our faculty and staff members to do this work with the money freed up from not having to pay for access to tech that in fact is inaccessible and even dangerously invasive? Or from the money earned through tuition from students persisting and thriving in this kind of environment, in which access and privacy are not afterthoughts but at the forefront of any decision about teaching and learning?

An institution that takes a minimal computing approach to online course offerings, of course, will probably never happen.5 Our institutions and our culture are too entrenched in the narrative that more tech ultimately will save us, too heavily invested both literally and figuratively in the solutionism that technology promises us as well as the false promise and security of mass surveillance. What minimal computing teaches us, however, is that equity can be at the core of what we do as online educators, and it does not involve more and more expensive technology. It is not a solution to digital redlining but a response that acknowledges the reality that many of our students face while trying to access education, making their cultural and material contexts central to our design of remote learning environments. Thinking through a minimal computing approach to online learning can help us all to think differently about our institutions and our approaches to teaching and learning.

To repeat: taking a minimal computing approach to online learning invites us to consider closely what we need and, most importantly, what our students need. These are (or should be) central questions for any critical digital pedagogue. When designing course assignments or deciding which technologies to use, keep that central question in mind: what, pedagogically, do our students need, and how can we meet that need with minimal computational infrastructure? But we also have to start thinking more about the ed tech and digital infrastructures that we support through our institutions and institutional policies. There is space to be able to make positive change toward a more minimal computing approach, but first we have to understand the inner workings of the technology and our institutions. Because a handful of well-meaning instructors can make a difference in the lives of some of our students, if we can make institutional changes, then we will have exponentially more impact.

Key Takeaways

• We need to understand the impact of digital redlining on our students, especially during COVID-19.
• We should understand the concept of minimal computing.
• We need to apply the key concepts of minimal computing to online/distance learning as a response to digital redlining.

Notes

References