Evaluating Cognitive Age Alignment in Interactive AI Agents
While agentic AI and its core multimodal large language models (MLLMs) have demonstrated remarkable promise in language and visual reasoning across domains ranging from daily life to advanced scientific research, a profound gap remains between artificial and human intelligence. Despite the integration of powerful tools and advanced MLLMs, state-of-the-art AI agents frequently fail at foundational, seemingly simple tasks that a child can resolve with ease. Inspired by the Wechsler Intelligence Sc
Record details
Published: 18 May 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Children & education · Agents & autonomy
Retrieved: 14 July 2026
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ethics.ai (18 May 2026), “Evaluating Cognitive Age Alignment in Interactive AI Agents,” evidence record 4154, https://ethics.ai/record/4154 (originally published by arXiv).
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