Are Humans Evolved Instruction Followers? An Underlying Inductive Bias Enables Rapid Instructed Task Learning
arXiv:2606.29792v1 Announce Type: new Abstract: Human adults can often perform a novel task correctly on the first attempt after only receiving verbal or written instructions. This rapid instructed task learning (RITL) is a hallmark of human cognitive flexibility, yet its mechanisms and parallels in artificial systems remain under-explored across disciplines. In this position paper, we argue that humans possess an evolved instruction-following bias -- an inductive bias shaped by evolution to interpret and execute linguistic instructions which critically enables fast generalization of behavior
The accelerating development of AI systems and the increasing focus on creating more human-like intelligence make understanding human cognitive processes for instruction-following critically relevant.
This research provides a theoretical framework for developing more robust and adaptable AI agents, highlighting an evolved human inductive bias that could be a blueprint for AI architecture.
The understanding of human rapid instructed task learning shifts from a purely behavioral observation to one grounded in an 'evolved instruction-following bias,' implying new design principles for AI.
- · AI researchers
- · AI software developers
- · Robotics companies
- · AI models lacking strong generalization
- · Brute-force AI development methodologies
This paper strengthens the theoretical foundation for developing AI systems capable of rapid instructed task learning (RITL).
Improved AI RITL capabilities could accelerate the deployment of autonomous agents in complex, unstructured environments.
Extremely versatile, instruction-following AI agents might significantly reduce the need for specialized training data and manual oversight in many domains.
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