Collection
Updated 3mo
* I’m neither “pro-AI” nor “anti-AI.” I’ve been blocked for being perceived as both. —Actually, I’m honestly more anti-AI than pro-AI thus far, aside from specialized models and specific use cases, but I’m willing to consider information that’s new to me
Gallup Begins Research on Simulated Responses
Gallup is exploring whether AI-generated agents perform well in predicting people's responses and where they fall short.
Do AI and bogus respondents threaten polling’s future?
Courtney Kennedy, vice president of methods and innovation, answers some common questions about the current polling landscape in the U.S.
AI-generated responses are undermining crowdsourced research studies
Many answers to online research questions show signs of being generated by AI chatbots, raising doubts about the validity of behavioural data collected this way
Recognising, Anticipating, and Mitigating LLM Pollution of Online Behavioural Research
Online behavioural research faces an emerging threat as participants increasingly turn to large language models (LLMs) for advice, translation, or task delegation: LLM Pollution. We identify three interacting variants through which LLM Pollution threatens the validity and integrity of online behavioural research. First, Partial LLM Mediation occurs when participants make selective use of LLMs for specific aspects of a task, such as translation or wording support, leading researchers to (mis)interpret LLM-shaped outputs as human ones. Second, Full LLM Delegation arises when agentic LLMs complete studies with little to no human oversight, undermining the central premise of human-subject research at a more foundational level. Third, LLM Spillover signifies human participants altering their behaviour as they begin to anticipate LLM presence in online studies, even when none are involved. While Partial Mediation and Full Delegation form a continuum of increasing automation, LLM Spillover reflects second-order reactivity effects. Together, these variants interact and generate cascading distortions that compromise sample authenticity, introduce biases that are difficult to detect post hoc, and ultimately undermine the epistemic grounding of online research on human cognition and behaviour. Crucially, the threat of LLM Pollution is already co-evolving with advances in generative AI, creating an escalating methodological arms race. To address this, we propose a multi-layered response spanning researcher practices, platform accountability, and community efforts. As the challenge evolves, coordinated adaptation will be essential to safeguard methodological integrity and preserve the validity of online behavioural research.
アンケート調査「回答者」の1割がAIか 科学研究ゆがめる恐れ
【この記事でわかること】・AIが社会調査に及ぼす悪影響・科学論文の著者は本当に人間か？・AIは科学を進歩させるか？
Opinion | This Is What Will Ruin Public Opinion Polling for Good
Instead of navigating the obstacles to conduct polls with human respondents, pollsters are running A.I. simulations instead. Why?
