“AI for all” is a matter of social justice

Abstract

Artificial intelligence (AI) is a radically transformative technology (or system of technologies) that created new existential possibilities and new standards of well-being in human societies. In this article, I argue that to properly understand the increasingly important role AI plays in our society, we must consider its impacts on social justice. For this reason, I propose to conceptualize AI’s transformative role and its socio-political implications through the lens of the theory of social justice known as the Capability Approach. According to the approach, a just society must put its members in a position to acquire and exercise a series of basic capabilities and provide them with the necessary means for these capabilities to be actively realized. Because AI is re-shaping the very definition of some of these basic capabilities, I conclude that AI itself should be considered among the conditions of possession and realization of the capabilities it transforms. In other words, access to AI—in the many forms this access can take—is necessary for social justice.

The digital divide in action: how experiences of digital technology shape future relationships with artificial intelligence

“…If these digital disadvantages spill over into people's perceptions, experiences and attitudes towards AI technology, the AI revolution risks leaving behind the same groups of people who today, already find themselves on the wrong side of the digital divide [72,84]. To undertake this exploration, we created a novel measure capturing a lived experience of digital exclusion.…”

“…It is a highly debated topic across both scholarly circles and applied settings [66], but the pillars of AI responsibility are generally agreed to be inclusivity, transparency, explainability, and accountability [67][68][69]. While there is no consensus definition or framework around how to deliver responsible AI, mechanisms such as governance, regulation, ethical design, risk control, and literacy are often cited [63,[70][71][72]. More broadly, the notion of responsible AI sits within a wider approach known as Responsible Innovation [73], in which new science and technology is articulated as an inclusive practice, designed and delivered 'for and with society' [74].…”

“…More broadly, the notion of responsible AI sits within a wider approach known as Responsible Innovation [73], in which new science and technology is articulated as an inclusive practice, designed and delivered 'for and with society' [74]. Today, as we navigate the early days of AI's roll-out, we have the opportunity to apply a more nuanced understanding of the diverse nature of societal differences in AI attitudes, perceptions, and behaviours, and to use what we know about digital exclusion to help shape our understanding and delivery of a truly responsible and inclusive AI [1,[68][69][70][71][72].…”

The Digital Divide in Action: How Experiences of Digital Technology Shape Future Relationships with Artificial Intelligence

“…It is a highly debated topic across both scholarly circles and applied settings [66], but the pillars of AI responsibility are generally agreed to be inclusivity, transparency, explainability, and accountability [67][68][69]. While there is no consensus definition or framework around how to deliver responsible AI, mechanisms such as governance, regulation, ethical design, risk control, and literacy are often cited [63], [70][71][72]. More broadly, the notion of responsible AI sits within a wider approach known as Responsible Innovation [73], in which new science and technology is articulated as an inclusive practice, designed and delivered 'for and with society' [74].…”

“…More broadly, the notion of responsible AI sits within a wider approach known as Responsible Innovation [73], in which new science and technology is articulated as an inclusive practice, designed and delivered 'for and with society' [74]. Today, as we navigate the early days of AI's roll-out, we have the opportunity to apply a more nuanced understanding of the diverse nature of societal differences in AI attitudes, perceptions, and behaviours, and to use what we know about digital exclusion to help shape our understanding and delivery of a truly responsible and inclusive AI [1,[68][69][70][71][72].…”