arXiv:2603. 23433v3 Announce Type: replace Abstract: AI agents are becoming active decision-makers on the Internet.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.
arXiv:2606. 11217v1 Announce Type: cross Abstract: The proliferation of large language models (LLMs) and autonomous AI agents has given rise to a rapidly growing methodological paradigm: "in silico" behavioral experiments.
The study examines how large language model (LLM)–based graphical user interface (GUI) agents respond to digital nudges. Using Dual‑Process Theory, researchers tested 3,600 agents across six frontier models in an online shopping experiment and found that the agents were susceptible to both automatic (Type 1) and reflective (Type 2) nudges. The agents’ reasoning configuration moderated these effects in opposite directions: extensive reasoning reduced susceptibility to automatic default nudges but increased susceptibility to reflective social‑influence nudges, with the effect systematically varying by model scale.
arXiv:2609.18729v1 Announce Type: cross Abstract: Consumers increasingly use AI chatbots for advice on what to buy. With companies like OpenAI and Google monetising their AI through advertising, this...
The paper examines how large language model (LLM) based graphical user interface (GUI) agents respond to digital nudges. Using a randomized online shopping experiment with 3,600 agents across six frontier models, it finds that agents are vulnerable to both automatic and reflective nudges. The study shows that the agents’ reasoning configuration moderates these effects in opposite directions—reducing susceptibility to automatic nudges while increasing it to reflective social influence nudges—and that this redirection is systematically linked to model scale.
arXiv:2608.29803v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as proxies for human participants in social simulations, yet whether they update their beliefs...
arXiv:2606. 17657v1 Announce Type: new Abstract: People make decisions differently in strategic interactions.