# Cognitive Spillover in Human-AI Teams

arXiv: https://arxiv.org/abs/2407.17489 · HTML: https://mlsanity.com/paper/2407.17489/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 141 references that are in the map.
- First posted on arXiv 3 Jul 2024.

## Builds on (most cited first, 13 of 13)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI](https://mlsanity.com/paper/1909.02309/) (2019)
- [Designing Creative AI Partners with COFI: A Framework for Modeling Interaction in Human-AI Co-Creative Systems](https://mlsanity.com/paper/2204.07666/) (2022)
- [Advancing Human-AI Complementarity: The Impact of User Expertise and Algorithmic Tuning on Joint Decision Making](https://mlsanity.com/paper/2208.07960/) (2022)
- [From partners to populations: A hierarchical Bayesian account of coordination and convention](https://mlsanity.com/paper/2104.05857/) (2021)
- [Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions](https://mlsanity.com/paper/2302.07248/) (2023)
- [Documentation Matters: Human-Centered AI System to Assist Data Science Code Documentation in Computational Notebooks](https://mlsanity.com/paper/2102.12592/) (2021)
- [Tell Me About Yourself: Using an AI-Powered Chatbot to Conduct Conversational Surveys with Open-ended Questions](https://mlsanity.com/paper/1905.10700/) (2019)
- [Prompting Diverse Ideas: Increasing AI Idea Variance](https://mlsanity.com/paper/2402.01727/) (2024)
- [The Placebo Effect of Artificial Intelligence in Human-Computer Interaction](https://mlsanity.com/paper/2204.04935/) (2022)
- [Improving Users' Mental Model with Attention-directed Counterfactual Edits](https://mlsanity.com/paper/2110.06863/) (2021)
- [Entrainment profiles: Comparison by gender, role, and feature set](https://mlsanity.com/paper/1805.11564/) (2018)
- [Collaboration of AI Agents via Cooperative Multi-Agent Deep Reinforcement Learning](https://mlsanity.com/paper/1907.00327/) (2019)

## Built on by (most cited first, 3 of 3)

- [A Dynamic-Semantics Framework for Grounding Human Referring Expressions in Visual Perceptual Data](https://mlsanity.com/paper/2608.08663/) (2026)
- [Deflecting the Value Compass: Interacting with Large Language Models Temporarily Shifts Human Value Priorities Toward Personal Focus](https://mlsanity.com/paper/2609.25586/) (2026)
- [Working with Agentic `Teammates': When a New Organizational Actor Collides with the Human Ecosystem of Work](https://mlsanity.com/paper/2609.29901/) (2026)

## Abstract (arXiv)

AI is not only a neutral tool in team settings; it influence the social and cognitive fabric of collaboration. Across two randomized experiments, we demonstrate that AI exposure produces causal spillover into human-human interaction -- affecting shared language, collective attention, shared mental models, and social cohesion. These spillover effects occur robustly across settings, modalities, tasks, and AI qualities, suggesting that mere exposure to AI drives the influence. AI functions as an implicit ``social forcefield,'' influencing not only how people speak, but also how they think, what they attend to, and how they relate to each other. We argue for shifting the design paradigm from optimizing ``AI as a tool'' to understanding AI as a socially influential actor whose effects extend beyond the human-AI interface.