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相关论文: Commercial Persuasion in AI-Mediated Conversations

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Today's large language models (LLMs) are trained to align with user preferences through methods such as reinforcement learning. Yet models are beginning to be deployed not merely to satisfy users, but also to generate revenue for the…

人工智能 · 计算机科学 2026-04-10 Addison J. Wu , Ryan Liu , Shuyue Stella Li , Yulia Tsvetkov , Thomas L. Griffiths

The development and popularization of large language models (LLMs) have raised concerns that they will be used to create tailor-made, convincing arguments to push false or misleading narratives online. Early work has found that language…

计算机与社会 · 计算机科学 2025-05-21 Francesco Salvi , Manoel Horta Ribeiro , Riccardo Gallotti , Robert West

There are widespread fears that conversational AI could soon exert unprecedented influence over human beliefs. Here, in three large-scale experiments (N=76,977), we deployed 19 LLMs-including some post-trained explicitly for persuasion-to…

Large language models (LLMs) possess strong persuasive capabilities that outperform humans in head-to-head comparisons. Users report consulting LLMs to inform major life decisions in relationships, medical settings, and when seeking…

人机交互 · 计算机科学 2026-04-28 Nalin Poungpeth , Nicholas Clark , Tanu Mitra

Conversational AI has been proposed as a scalable way to correct public misconceptions and spread misinformation. Yet its effectiveness may depend on perceptions of its political neutrality. As LLMs enter partisan conflict, elites…

计算与语言 · 计算机科学 2026-02-23 Matthew DiGiuseppe , Joshua Robison

Conversational AI models are becoming increasingly popular and are about to replace traditional search engines for information retrieval and product discovery. This raises concerns about monetization strategies and the potential for subtle…

综合经济学 · 经济学 2024-09-19 Tobias Werner , Ivan Soraperra , Emilio Calvano , David C. Parkes , Iyad Rahwan

Are large language models (LLMs) biased in favor of communications produced by LLMs, leading to possible antihuman discrimination? Using a classical experimental design inspired by employment discrimination studies, we tested widely used…

计算与语言 · 计算机科学 2025-08-12 Walter Laurito , Benjamin Davis , Peli Grietzer , Tomáš Gavenčiak , Ada Böhm , Jan Kulveit

Large Language Models (LLMs) have emerged as formidable instruments capable of comprehending and producing human-like text. This paper explores the potential of LLMs, to shape user perspectives and subsequently influence their decisions on…

人工智能 · 计算机科学 2024-09-04 Ganesh Prasath Ramani , Shirish Karande , Santhosh V , Yash Bhatia

Warning: This research studies AI persuasion and bias amplification that could be misused; all experiments are for safety evaluation. Large Language Models (LLMs) now generate convincing, human-like text and are widely used in content…

计算与语言 · 计算机科学 2025-08-25 Saumya Roy

Large language models (LLMs) have the potential to aid and improve human decision-making in classification tasks, not only by providing fairly accurate predictions, but also in their ability to generate cogent narrative explanations of…

人机交互 · 计算机科学 2026-05-25 Laura R. Marusich , Mary Grace Kozuch Dhooghe , Jonathan Z. Bakdash , Murat Kantarcioglu

The rapid rise of Large Language Models (LLMs) has created new disruptive possibilities for persuasive communication, enabling fully-automated, personalized, and interactive content generation at an unprecedented scale. In this paper, we…

计算与语言 · 计算机科学 2026-04-22 Sander Noels , Alexander Rogiers , Maarten Buyl , Tijl De Bie

The advent of Large Language Models (LLMs) has revolutionized product recommenders, yet their susceptibility to adversarial manipulation poses critical challenges, particularly in real-world commercial applications. Our approach is the…

计算与语言 · 计算机科学 2025-10-23 Giorgos Filandrianos , Angeliki Dimitriou , Maria Lymperaiou , Konstantinos Thomas , Giorgos Stamou

Large Language Models (LLMs) are increasingly regarded as having the potential to generate persuasive content at scale. While previous studies have focused on the risks associated with LLM-generated misinformation, the role of LLMs in…

计算机与社会 · 计算机科学 2026-04-06 John Caffier , Olga Stavrova , Bennett Kleinberg

As large language models (LLMs) become increasingly persuasive, there is concern that people's opinions and decisions may be influenced across various contexts at scale. Prior mitigation (e.g., AI detectors and disclaimers) largely treats…

计算与语言 · 计算机科学 2026-04-06 Qihui Fan , Min Ge , Chenyan Jia , Weiyan Shi

Large language models (LLMs) are increasingly employed for decision-support across multiple domains. We investigate whether these models display a systematic preferential bias in favor of artificial intelligence (AI) itself. Across three…

计算与语言 · 计算机科学 2026-01-21 Benaya Trabelsi , Jonathan Shaki , Sarit Kraus

As large language models (LLMs) become increasingly capable of generating persuasive content, understanding their effectiveness across different advertising strategies becomes critical. This paper presents a two-part investigation examining…

计算机与社会 · 计算机科学 2025-12-04 Elyas Meguellati , Stefano Civelli , Lei Han , Abraham Bernstein , Shazia Sadiq , Gianluca Demartini

Large language models (LLMs) are increasingly being integrated into search engines to provide natural language responses tailored to user queries. Customers and end-users are also becoming more dependent on these models for quick and easy…

信息检索 · 计算机科学 2024-09-04 Aounon Kumar , Himabindu Lakkaraju

LLMs are increasingly being used in workflows involving generating content to be consumed by humans (e.g., marketing) and also in directly interacting with humans (e.g., through chatbots). The development of such systems that are capable of…

计算与语言 · 计算机科学 2024-10-08 Somesh Singh , Yaman K Singla , Harini SI , Balaji Krishnamurthy

Concerns persist regarding the capacity of Large Language Models (LLMs) to sway political views. Although prior research has claimed that LLMs are not more persuasive than standard political campaign practices, the recent rise of frontier…

计算与语言 · 计算机科学 2026-03-11 Zhongren Chen , Joshua Kalla , Quan Le

While natural-language explanations from large language models (LLMs) are widely adopted to improve transparency and trust, their impact on objective human-AI team performance remains poorly understood. We identify a Persuasion Paradox:…

人机交互 · 计算机科学 2026-04-07 Ruth Cohen , Lu Feng , Ayala Bloch , Sarit Kraus
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