Enhancing Digital Equity: Connecting the Digital Underclass attempts to sketch a concept of inequalities in the digital sphere and proposes a new way to (re)think, analyse and understand inequalities in the digital age. One of the lead motifs of this book is that if traditional digital inequalities (digital divide) and new digital inequalities (algorithms divide) are not addressed, social inequalities and social exclusion will be further bolstered. In fact, in the digital society, where an increasing number of services, products, resources and activities are migrating online, those who are digitally excluded are also socially excluded. At the same time, the advent and implementation of tools relying on algorithms to make decisions has further penalized specific social categories by normalizing inequalities, in the name of efficiency and rationalization. As scholars, we should deconstruct this narrative by highlighting the risks that automated process and predictive model bring with them, specifically in terms of reinforcing inequalities.
In principle, digital technologies present an opportunity to reduce social disparities, to tackle social exclusion, enhance social and civil rights, and promote equity. However, to achieve these noble aims, it is necessary to promote digital equity through programmes and services designed to face and reduce traditional and new digital inequalities. We shall see how different levels and forms of digital inequalities are intertwined with social inequalities and how they tend to reinforce each other. We will also see how the main axes of social inequality are still influencing and determining disparities emerging with the advent of digital technologies. Furthermore, we shall see that we cannot approach the issue of digital inequalities, without tackling social inequalities, and vice versa. The position the individual holds in the network society, where economic and socially relevant information circulates, is a key factor in terms of producing and reproducing social inequalities. At the same time, algorithms, due to the ways in which they are designed, tend to penalize and discriminate those already at the margin of society. These forms of digital inequalities are giving rise to the digital underclass. This class of citizens is strongly penalized by exclusion from both the digital realmâas they are digitally invisibleâand social services, job opportunities or private services that implement biased algorithms to make their decisions.
Moving from the assumption that social and digital inequalities are deeply intertwined, this book proposes a more nuanced theorization of the links between social and digital inequalities and between social and digital exclusion. The notion of inequality identifies disparities in terms of well-being, incomes, consumption, access to health care, education and life expectancy. More recently, both the uneven access to and use of new technologies (traditional digital inequalities) and the inequalities deriving from the algorithmizing of society and the extensive use of big data in daily life (new digital inequalities) are considered forms of (digital) inequalities. These digital inequalities, as we shall see, affect those already socially disadvantaged the most, further cementing their underprivileged position in society. In fact, as it shall be clear in the chapters to come, socially disadvantaged individuals or groups tend to have limited access to resources and services and less control over life circumstances compared to the hegemonic groups in society (Wilkinson and Marmot 2003). These social groups, already discriminated against in the social realm, are at the same time in a disadvantaged position in relation to information communication technologies (ICTs ) (Mossberger et al. 2003; Gilbert et al. 2008), thus widening social, cultural, personal, economic and political inequalities (DiMaggio et al. 2001; Gordo 2003; Warschauer 2003; Barzilai-Nahon 2006; Kvasny and Keil 2006; Gilbert et al. 2008). More specifically, the ways individuals access and use ICTs is influenced by the main axes of social inequalities, such as ethnicity, socio-economic status, gender, age and geographic location (Alvarez 2003; Jackson et al. 2003, 2008; Kennedy et al. 2003; Lenhart and Horrigan 2003; Losh 2003, 2004; Prieger and Hu 2008). The types of technologies individuals adopt, the skills required to use them and the benefits obtained from them are the basis of the three levels of digital divide (Ragnedda 2017), here labelled as âtraditional digital inequalitiesâ (see Chap. 3). In addition to these, the increased reliance on algorithms and big data for high-stakes decisions brought in new forms of (digital)inequalities, namely inequalities in knowledge, in dataset and in treatment (see Chap. 4). More specifically, predictive modelling and artificial intelligence (AI) based on algorithms treat people differently (inequalities in treatment) because they learn from data that may underrepresent some social categories (inequalities in dataset) whose consequences are often unknown to citizens who do not know (inequalities in knowledge) how to protect themselves and to escape from the invasiveness of algorithms. It is exactly this different way of treating individuals based on biased algorithms that further widens social inequalities, penalizing the already marginalized individuals and social groups.
This book, therefore, focuses on how the advent of digital technologies, despite their potentialities, is reinforcing social disparities, both because some lack the resources and skills to use them fruitfully and because they perceive and treat individuals in a prejudicial way. Socially disadvantaged citizens often lack the skills and resources needed to resist this categorical suspicion and inequalities of treatment. These inequalities give rise to a social group that is utterly and negatively affected by the advent of digital technologies: the digital underclass.
In sociology, the controversial concept of underclass is associated to a group of people who, due to the lack of skills, resources or employment, live at the margin of society. Conservatives often depict the underclass not only as poorer, but also excluded, de-socialized and ignorant citizens who voluntarily choose to live in this underprivileged situation. Among them, the new right-wing theorist Charles Murray depicted the underclass as those who prefer not to work and to rely on excessive government welfare payment (1996). On the other side, progressives associate this label to a defenceless category that needs assistance and help to be included in the society. In this book, moving away from a moralistic vision, underclass is seen in reference to how socially disadvantaged individuals use and are âused byâ digital technologies. Therefore, here, the digital underclass includes not only those vulnerable populations who are infrequent or non-users of the Internet (Rubinstein-Ăvila and Sartori 2016) and are digitally disengaged (Helsper 2012, 2014), but also those who lack the digital skills to evade surveillance, protect privacy and improve security and safety, and above all to escape the stream in which algorithms embed their path. The digital underclass represents those who, being at the margin of digital society, are penalized by the rise of digital technologies, both because they are excluded by the digital arena that resources and opportunities have moved into and also because they are penalized by automatic decisions made by subtle, biased and invisible algorithms. For the digital underclass, while the advent of ICTs, in principle, can improve their life chances, it often creates an additional barrier to social mobility, further exacerbating social inequalities. For this reason, it is vital to promote digital equity, here intended as a condition in which all citizens have the skills and information technology capacity needed for full participation in our society, democracy and economy. Digital equity is, therefore, a new civil and social right, and both public and private actors should work to promote it. Everybody is born equal in front of the law. Similarly, we can say that everybody is born equal in front of digital technologies and the digital world, and we all should have the same rights to access and use it and not be discriminated by digital technologies. The first article of the âUniversal Declaration of Human Rightsâ says âYou are worth the same and...