Governing Artificial Intelligence in an Age of Inequality

Abstract

This article seeks to position both AI‐based activities, and related policy developments, in the global South in light of a technology industry with desires for continuous expansion and self‐governance. The article proceeds along three themes. First, using field interviews and related information (in an anonymised manner), the article classifies expanding AI activities in several core sectors by businesses, governments and other agencies in the global South into three categories. Next, it reviews the current AI policy priorities and positions in developing countries, showing how the introduction of AI has been punctuated by considerations of digital cannibalization by large firms from the North at the expense of a full‐fledged debate on privacy and data protection. By showing how AI exemplifies structural inequality in the global South, the article identifies four critical departure points in developing countries that make the expanding use of AI a matter of concern. While many of challenges posed by AI are somewhat universal, the article argues that their ramifications can be much worse in the global South. Countering these will require policy frameworks that factor in privacy protection in a more accountable manner. It concludes with suggestions for a more nuanced debate on industrialisation, privacy protection and development.

Catching up with AI: Pushing toward a cohesive governance framework

“…There are concerns about the misuse of AI for warfare (Dauvergne, 2022; Fischer & Wenger, 2021; Greiman, 2019), cyberattacks (Greiman, 2019), privacy violations (Mohamed et al, 2012), and disruption of peace and security (Garcia, 2018). Transparency is paramount to building trust among the public, which is at once open to the promise of AI and wary of its potential misuse (Gehl Sampath, 2021). Therefore, it is necessary to establish a public policy that can provide appropriate governance; minimize public sector confusion; and protect privacy, fairness, and equity (Ingrams et al, 2021).…”

“…This is driven by the explosion of data and the need to enable automation of e-government services (Ingrams et al, 2021). Furthermore, applications for utilizing AI offer opportunities to innovate in almost every aspect of human life (Gehl Sampath, 2021). Examples include autonomous transportation (Eyert et al, 2022), health-care systems (Morley et al, 2022), international relationships (Garcia, 2018), government systems (Ingrams et al, 2021), information security, military applications (Fischer & Wenger, 2021), and private enterprise (Greiman, 2019).…”

Ethical concerns about artificial intelligence: Evidence from a national survey in Taiwan

“…Though AI increases the productivity of these tasks by speeding up the hiring process, this study indicated that the public is more concerned about transparency after nonmale cence. Concerns about transparency echo the suggestion of Gehl Sampath 49 that AI development in newly industrialized countries may exacerbate its risks and calls for greater transparency in the public sector. Policymakers have extensively supported transparency con rmation in public affairs to increase the trust and perceived legitimacy among the public 50 .…”

Artificial intelligence, algorithms, and social inequality: Sociological contributions to contemporary debates

“…The inequalities that are reproduced and reshaped through algorithmic technologies can be studied within organizations, but inequalities also play out on a global scale (Sampath, 2021), including international labor (Aneesh, 2009), and the flow of capital through colonial and extractive processes (Couldry & Mejias, 2019). Sociology's own coloniality (Bhambra, 2014) has often excluded societies of the 'Global South' from analysis, or treated societies of the North as universal (Go, 2020;Milan & Treré, 2019).…”