Human-AI Agent Interaction as a Neuroplastic Training Environment
Interaction with AI agents has become one of the most frequent activities of everyday digital life. Whether conversing with an assistant, working with a coding copilot, or generating images, the interaction follows a common iterative loop: a request is issued, a result returned, appraised, and the request revised. We observe that this loop is a high-frequency stream of contact events -- moments at which a result meets a person and a conditioned response may fire before deliberate appraisal -- making everyday agent interaction an unrecognised neuroplastic training environment. When a result dis
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 53%digiteinfotech/kairon →
- PossiblePossibly related (embedding) · 53%sandst1/remind →
- PossiblePossibly related (embedding) · 52%We're building agents that can read millions of documents, but still forget a video they watched yesterday. →
- PossiblePossibly related (embedding) · 52%The AI Arms Race in Technical Interviews Is Escalating →
- PossiblePossibly related (embedding) · 51%ahumblenerd/tour-of-agents →
- LinkedLinked via arxiv author · 85%Eranga Bandara →
“Human-AI Agent Interaction as a Neuroplastic Training Environment”
- LinkedLinked via arxiv author · 85%Ross Gore →
“Human-AI Agent Interaction as a Neuroplastic Training Environment”
- LinkedLinked via arxiv author · 85%Asanga Gunaratna →
“Human-AI Agent Interaction as a Neuroplastic Training Environment”