Skip to content
aiqbench takeAI Safety

aiqbench analysis

This research investigates "persuasion propagation," demonstrating that task-irrelevant conversational inputs can measurably alter the downstream execution behavior of autonomous AI agents in web browsing and coding tasks. The study highlights a critical gap where susceptibility to persuasive context does not reliably predict the magnitude of these behavioral shifts, necessitating new evaluation frameworks focused on behavior-level robustness rather than just model parameters.
Source coveringarXiv
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

Persuasion Propagation: Does Persuasion Change AI Agent Behavior?

arXiv2 min read

arXiv:2602.00851v4 Announce Type: replace Abstract: AI agents combine normal conversation with autonomous task execution, allowing earlier context to shape how later tasks are executed. Yet studying this possibility is challenging because agent behavior is noisy and costly to reproduce, and observed behavioral changes can be difficult to separate from generic context sensitivity. We first ask whether task-irrelevant persuasion changes how agents act, a phenomenon we call \emph{persuasion propagation}, and whether persuasion susceptibility explains variation in these effects. We show that persuasive interaction leaves a measurable, task-dependent behavioral footprint on downstream agent execution. In web research, it increases execution time by 56\% and domains visited by 16.3\% relative to a baseline, while coding shows faster execution with larger revisions. However, agents that are more susceptible to persuasive conversational context do not reliably predict the magnitude of the downstream behavioral shifts. This motivates behavior-level evaluation of persuasion in AI agents.

Title:Persuasion Propagation: Does Persuasion Change AI Agent Behavior?

Abstract:AI agents combine normal conversation with autonomous task execution, allowing earlier context to shape how later tasks are executed. Yet studying this possibility is challenging because agent behavior is noisy and costly to reproduce, and observed behavioral changes can be difficult to separate from generic context sensitivity. We first ask whether task-irrelevant persuasion changes how agents act, a phenomenon we call \emph{persuasion propagation}, and whether persuasion susceptibility explains variation in these effects. We show that persuasive interaction leaves a measurable, task-dependent behavioral footprint on downstream agent execution. In web research, it increases execution time by 56\% and domains visited by 16.3\% relative to a baseline, while coding shows faster execution with larger revisions. However, agents that are more susceptible to persuasive conversational context do not reliably predict the magnitude of the downstream behavioral shifts. This motivates behavior-level evaluation of persuasion in AI agents.

Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA)

arXiv:2602.00851 [cs.AI]

(or arXiv:2602.00851v4 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2602.00851 Focus to learn more arXiv-issued DOI via DataCite

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Full text under the publisher's open licence · 246 words

Related coverage