arXiv:2606. 04150v1 Announce Type: new Abstract: Public discourse and emerging policy typically assume that AI emotional support is a deliberate act: a lonely user consciously seeking comfort from a dedicated companion chatbot.
arXiv:2608. 04205v1 Announce Type: new Abstract: Human evaluation of AI systems and digital products is costly, slow, and difficult to scale.
arXiv:2607. 25057v1 Announce Type: new Abstract: As conversational AI systems become increasingly integrated into daily life, their potential effects on user well-being require ongoing attention.
arXiv:2608. 02046v2 Announce Type: replace-cross Abstract: LLM companions are deployed at scale in personally consequential settings, yet poorly evaluated.
LLM companions are deployed at scale in personally consequential settings, yet poorly evaluated. Existing benchmarks use hand-authored scenarios and prompted simulators, aggregate empathy into one score, and overlook judge biases such as same-family favoritism and scale drift.
InterviewPlayground is a simulation environment designed to evaluate AI interviewers by using simulated participants whose behaviors are grounded in social theory. The platform generates an InterviewReportCard that assesses AI interviewers across validated measures. Empirical validation shows that performance in InterviewPlayground predicts human study outcomes with a Pearson correlation of 0.86, supporting its use for assessing AI interviewer performance and failure modes.
The paper introduces ImpactBench, an open, expert-guided platform designed to measure the multi-dimensional impact of generative AI on users. It evaluates AI models across psychological, physical, and social wellbeing metrics derived from domain experts and existing benchmarks, using simulated multi-turn conversations with teen and adult scenarios. Ten leading LLMs were tested on 48,540 conversations, showing 68.7% promotion of desirable behaviors but only 53.1% avoidance of harms, with an 83.3% agreement rate between automated judges and expert reviewers.
arXiv:2605.12894v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) agents are increasingly deployed in settings where they interact with diverse users, including those who are uncle...
arXiv:2606. 04867v1 Announce Type: new Abstract: As AI companion platforms such as Replika and Character.
InterviewPlayground is a simulation environment designed to evaluate AI interviewers by using simulated participants whose behaviors are grounded in social theory. The platform generates an InterviewReportCard that assesses AI interviewers across validated measures. Empirical validation shows a strong correlation (average Pearson 0.86) between simulation results and real human studies, confirming the environment’s predictive validity.
arXiv:2610.16946v1 Announce Type: cross Abstract: Descriptions of how people use AI are becoming training data for the next generation of models. We ask whether what a model reads about its users cha...
arXiv:2608. 10672v1 Announce Type: cross Abstract: Social interaction has become one of the most common uses of LLMs, yet research on emotional bonds with AI has focused largely on how users experience these systems, leaving the systems' role in relationship formation poorly understood.