Scholarlink

<p>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 <span>fRAme</span>, 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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

fRAme: an evaluation framework for human augmentation or replacement by autonomous intelligent systems

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月26日

查看全文
  • Costanza Alfieri,
  • Martina De Sanctis,
  • Donatella Donati,
  • Paola Inverardi

摘要

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.