arXiv:2605.27396v1 Announce Type: cross Abstract: Autonomous AI agents now plan, decide, and act on behalf of users across healthcare, financial services, and workplace contexts, often without step-by-step human approval. Existing AI literacy frameworks were built for a world in which humans evaluate AI outputs and decide whether to act; they have no vocabulary for the user who has delegated decision-making authority to an agent whose actions may not be observable, reversible, or controllable. This paper names the resulting problem agentic literacy debt: the accumulating societal deficit that
The proliferation of advanced autonomous AI agents across critical sectors necessitates a re-evaluation of existing AI literacy frameworks, which were not designed for delegated decision-making authority.
This paper identifies a critical and growing societal deficit regarding human understanding and control of AI agents, which has profound implications for trust, accountability, and risk management.
The understanding of AI literacy shifts from evaluating outputs to comprehending delegated decision-making, observability, and reversibility of autonomous agent actions.
- · AI ethics researchers
- · Regulatory bodies
- · Education technology
- · Developers of transparent AI
- · Users unfamiliar with agentic AI
- · Organizations deploying opaque AI agents
- · Traditional AI literacy programs
- · Systems with poor agent observability
Increased demand for new frameworks and educational tools to address agentic literacy debt.
Potential for new regulations requiring greater transparency and control mechanisms for autonomous AI systems.
Long-term societal trust in AI could erode if this debt is not addressed, leading to slower adoption or public backlash against agentic systems.
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Read at arXiv cs.AI