把AI当学习者,探索它如何融入人机认知生态。
Immersion for AI: Immersive Learning with Artificial Intelligence
- 以沉浸式学习理论重构AI角色,从工具变为参与者。
- 提出系统、叙事、代理三维度设计支持AI深度参与的环境。
- 适合研究人机协作与AI自适应能力的学者参考。
本文从人工智能(AI)视角反思沉浸的含义,运用沉浸式学习理论,探讨这一新视角是否支持AI在认知生态中的积极参与。将AI视为参与者而非工具,分析人类及其他AI在具备意义交互能力的环境中需考虑的要素,并探讨其对学习环境设计的影响。基于沉浸的三个概念维度——系统、叙事、代理——重新诠释了AI在沉浸式学习场景中的角色。论文提出,应设计让AI接入外部数字服务、理解数据演化叙事,并动态响应、做出操作与战术决策的环境,以促进人机协作。最后,建议利用这些洞见推动未来AI训练的发展,使AI突破静态模型限制,具备持续演进的能力。本研究为理解AI作为沉浸式学习者及动态人机认知生态参与者提供了新路径。
原文摘要 · Abstract (English)
This work reflects upon what Immersion can mean from the perspective of an Artificial Intelligence (AI). Applying the lens of immersive learning theory, it seeks to understand whether this new perspective supports ways for AI participation in cognitive ecologies. By treating AI as a participant rather than a tool, it explores what other participants (humans and other AIs) need to consider in environments where AI can meaningfully engage and contribute to the cognitive ecology, and what the implications are for designing such learning environments. Drawing from the three conceptual dimensions of immersion - System, Narrative, and Agency - this work reinterprets AIs in immersive learning contexts. It outlines practical implications for designing learning environments where AIs are surrounded by external digital services, can interpret a narrative of origins, changes, and structural developments in data, and dynamically respond, making operational and tactical decisions that shape human-AI collaboration. Finally, this work suggests how these insights might influence the future of AI training, proposing that immersive learning theory can inform the development of AIs capable of evolving beyond static models. This paper paves the way for understanding AI as an immersive learner and participant in evolving human-AI cognitive ecosystems.
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