Artificial intelligence and identity: the rise of the statistical individual

Abstract

Algorithms are used across a wide range of societal sectors such as banking, administration, and healthcare to make predictions that impact on our lives. While the predictions can be incredibly accurate about our present and future behavior, there is an important question about how these algorithms in fact represent human identity. In this paper, we explore this question and argue that machine learning algorithms represent human identity in terms of what we shall call the statistical individual. This statisticalized representation of individuals, we shall argue, differs significantly from our ordinary conception of human identity, which is tightly intertwined with considerations about biological, psychological, and narrative continuity—as witnessed by our most well-established philosophical views on personal identity. Indeed, algorithmic representations of individuals give no special attention to biological, psychological, and narrative continuity and instead rely on predictive properties that significantly exceed and diverge from those that we would ordinarily take to be relevant for questions about how we are.

Towards a smart glasses society? Ethical perspectives on extended realities and augmenting technologies

“…Yet, it is all the more vital to ensure, that the real and immediate risks presented by smart glasses are not overshadowed by such sensationalist fears. Among the pressing risks that demand timely attention are the escalation of data collection exploitation in the era of surveillance capitalism (Zuboff, 2019), the transformation of individuals into quantified and statistical entities (Lupton, 2016;Bjerring and Busch, 2024), the progressive erosion of privacy as smart devices become more pervasive and intrusive (Véliz, 2020), and the insidious expansion of a surveillance mechanism into increasingly broader aspects of our lives (Marx, 2016).…”