Artificial intelligence (AI) technologies are now embedded in daily life and their adoption has polarized opinions—some fear AI will replace human roles, while others see it as a means to augment human abilities. Central to this debate is the need to determine whether these technologies replace or augment human abilities and how these outcomes impact society. Despite its importance, the distinction between replacement and augmentation remains unclear and domain-dependent. To address this challenge, we propose fRAme, a framework designed to evaluate the impact of autonomous intelligent systems by analyzing both the technology and human abilities—specifically, their dispositions—within a given context and for a specific task. This approach aims to clarify the nuanced relationship between replacement and augmentation, providing a foundational tool for promoting responsible AI development, enhancing transparency, and enabling more informed decision-making among diverse stakeholders.
fRAme: an evaluation framework for human augmentation or replacement by autonomous intelligent systems
Alfieri, CostanzaMembro del Collaboration Group
;Sanctis, Martina DeMembro del Collaboration Group
;Donati, Donatella
Membro del Collaboration Group
;Inverardi, PaolaMembro del Collaboration Group
2025-01-01
Abstract
Artificial intelligence (AI) technologies are now embedded in daily life and their adoption has polarized opinions—some fear AI will replace human roles, while others see it as a means to augment human abilities. Central to this debate is the need to determine whether these technologies replace or augment human abilities and how these outcomes impact society. Despite its importance, the distinction between replacement and augmentation remains unclear and domain-dependent. To address this challenge, we propose fRAme, a framework designed to evaluate the impact of autonomous intelligent systems by analyzing both the technology and human abilities—specifically, their dispositions—within a given context and for a specific task. This approach aims to clarify the nuanced relationship between replacement and augmentation, providing a foundational tool for promoting responsible AI development, enhancing transparency, and enabling more informed decision-making among diverse stakeholders.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


