Artificial Intelligence (AI) and the Evolution of Digital Divides

Gaps, divides, and splits are a common feature of contemporary societies and economies. Both at the global and the local contexts, inequalities persist across multiple dimensions and interact with each other in complex ways. From income to education, to digital gaps, divides shape an uneven playing field where access to resources and opportunities are not evenly distributed. With the rapid advance of  information and communication technologies, disparities have continued to reproduce and amplify. Despite the efforts for closing the divides, their contours keep evolving in parallel to the rapid technological change. With the spread and deployment of Artificial Intelligence (AI) systems across different social domains, it is likely that social divides will continue to expand and inequalities will deepen.

Mind the Gap

The term “digital divide” entered the public discourse in the 1990s as a way of describing disparities in access to Internet and computer power among the U.S. population. Few years after the High Performance Computing Act —a U.S. bill for boosting Internet infrastructure and scaling up connectivity among the population— passed on 1991, the term started to appear in news outlets and politician speeches.  As millions of people, particularly the ones with better socioeconomic status and living in urban areas, started to have Internet connectivity at their homes, schools, and libraries, disparities among the population quickly emerged.

The “divide,” at this moment of time, was used for describing the the unevenness of  technology access, to the split between “haves” and “have-nots.” Articles in the New York Times such as “A Nation Ponders Its Growing Digital Divide” and “A New Gulf in American Education, the Digital Divide,” for instance, raised concerns about the disparities in access to computers and Internet among schools. Meanwhile, the National Telecommunications and Information Administration (NTIA) published a report in July 1995 called “Falling Through the Net: a Survey of the “Have Nots” in Rural and Urban America.

Along with a narrative of empowerment and development that highlighted “access to knowledge,” and “entering the information highway,” bridging the “digital divide” became in the 2000s a global imperative. The Declaration of Principles of the World Summit on the Information Society (2003), for instance, set up bridging the “digital divide” as a developmental goal for all nations. Governments around the world designed policies for connecting people to the Internet and to build digital infrastructure that would allow them to join the “information society” and avoid being “left behind.” Among the benefits and good intentions that were described was the possibility of accessing knowledge and education, economic growth, foster democracy and participation.

The focus on technology access and infrastructure made the “digital divide” easy to understand, to measure, and to quantify. It helped policy makers and researchers to understand the diffusion of Internet across entire populations with the idea of universal access that was used for previous technologies such as the telephone.  Researchers from different disciplines studied how the gap in access to digital technology was creating a split both at the global scale (e.g. Norris, 2001), and within nations. In North America, Europe, and Australia, for instance, researchers found that disparities in access were correlated with age, race/ethnicity, gender, education, and income (e.g. DiMaggio et al. 2001 on the U.S; De Haan 2003 on the Netherlands; Heil 2002 on the U.K. and Germany; and McLaren and Zappala 2002 on Australia).

Internet Population and Penetration 2008. Based on statistics from the World Bank. Visualization and analysis by Mark Graham and his team at OII

Researchers, governments, transnational organizations, and NGOs from Latin America, in contrast, focused their efforts in measuring Internet penetration (Fundacion Acceso in Costa Rica, CEPAL, 2003),  discussing the meaning of the “knowledge society” (Sociedade da Informação no Brasil Livro Verde in Brasil, 2000; Pasquali, 2003), and the social and cultural uses of ICT (Funredes in the Caribbean, 1995; León, Burch y Tamayo 2001; Capurro 2000; Hopenhayn  2003). However, as Trejo (2004) pointed out, research on the digital divide in the Latin American region is dispersed and lacked a common methodology. According to him, there was a “divide” on the study and theorization of the Internet, that Latin American researchers needed to bridge.

From one Digital Divide to Multiple Ones

As the access to Internet and computers spread through entire populations within a country and regions, it became clearer that the digital divide was not only related to technology access.  Beyond the gap between the “haves” and “have-nots,” researchers started to identify other dimensions of the “digital divide” such as access to skills, use patterns, and social support networks. Researchers transitioned from analyzing who has access to the technology, to investigating how the technology is being used in more advantageous or disadvantageous ways. Moreover, in an effort to update the terminology scholars proposed alternative concepts such as “digital inequality” (DiMaggio et al. 2004) and “digital inclusion” (e.g. Warschauer 2002; Livingstone & Helsper 2007). At the core of such development was an interdisciplinary effort for understanding how the rapid diffusion of digital technologies across national and global contexts was reproducing and amplifying existing social inequalities.

Theorization of the “digital divide,” therefore, has become more nuanced and complex. Instead of one divide, researchers have identified multiple ones.  A number of  studies have found that there are gradients not only in the quality of access to technology, but also in the sociocultural practices and skills that people develop (Hargittai 2011; Jenkins et al. 2006; Van Dijk 2005; Watkins 2012), the information they consume and produce (Robinson 2009; Schradie 2011;), and the outcomes of their usage (van Deursen & van Dijk 2013; van Deursen & Helsper 2015).

Although the split in access to material technology is still important (first-level divide), other digital gaps are now widely recognized. What is known as the second-level digital divide, for instance, is precisely the split in online skills and practices (e.g. Hargittai, 2002). More recently, scholars have also discussed the existence of a third-level divide, and analyzed the different tangible outcomes that come from technology usage such as the earning of social, and cultural capital (e.g. van Deursen & Helsper, 2015).

AI: A New Digital Divide? or an Amplification of  Existing Ones?

One of the latest developments in the evolution of information and communication technologies is the deployment of artificial intelligence (AI) at scale. As AI systems have started to be embedded in culture, society, education, and the economy, its deployment affects the three digital divides that researchers have been identified so far. Given the reliance of AI in big data and computer power, the spread of AI is more likely to amplify existing inequalities, increasing disparities in access to technology,  skills, and tangible outcomes of usage.  Particularly, AI might accelerate the deepening of the second-level and third-level digital divides.

Some commentators have pointed out that the diffusion of AI can create a new digital divide among companies and firms (e.g. Dans, 2016). This perspective, assumes that access to AI –and related technologies such as machine vision, machine learning,  natural language processing, and sophisticated algorithms–, gives an advantage to the companies and governments that are able to deploy this technology. The AI “haves” are able to optimize their operations, automate processes, and innovate, while the “have-nots” are being left behind in their digital evolution.

The notion of AI as a new digital divide, however, is problematic, since it force us to focus on the latest technological advances while ignoring their relationship to the other divides previously theorized. Moreover, this notion of a new divide focuses only in the disparities among companies and firms, ignoring the role of entire populations and users, who would be affected by how AI is deployed and by the decision-making processes that would be automated.

AI systems would be developed and deployed faster in the global north, enhancing inequalities among regions. As a recent PwC report shared by the World Economic Forum showed, the regions that would gain the most from AI are China, and North America. According the the report, AI could boost China’s productivity by 27% by 2035, particularly in sectors such as healthcare, retail, and ICT.  Regions in the global south like Latin America, in contrast, would only increase 5.4% of GDP.  Countries which still struggle to reduce the first and second level digital divides would likely confront situations where they would have to deploy systems developed abroad that perhaps do not adapt that well to their cultural context. Countries at the wrong side of the AI gap, furthermore,  would probably be in weaker positions to negotiate issues of data ownership with transnational corporations, as well as fight for a more culturally sensitive building of data bases and algorithms that take into account the local contexts and knowledges.

It is urgent to understand how AI reshapes the contours of the existing digital divides at the national, regional, and global scales. Researchers, policy makers, activists, and the civil society should think about how AI transforms the multiple dimensions of access to technology, skills and knowledge, and uses of it. Moreover, it is necessary to discuss how AI systems would be regulated locally and globally, within a framework of human values and rights that respects the diversity of cultures, knowledge, genders, and races/ethnicities.

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