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Social Commentary#AI Influence, Human Behavior📝 BlogAnalyzed: Jan 3, 2026 06:58

AI Advice and Crowd Behavior

Published:Jan 2, 2026 12:42
1 min read
r/ChatGPT

Analysis

The article highlights a humorous anecdote demonstrating how individuals may prioritize confidence over factual accuracy when following AI-generated advice. The core takeaway is that the perceived authority or confidence of a source, in this case, ChatGPT, can significantly influence people's actions, even when the information is demonstrably false. This illustrates the power of persuasion and the potential for misinformation to spread rapidly.
Reference

“Lesson: people follow confidence more than facts. That’s how ideas spread”

Permalinkr/ChatGPT
Research Paper#Bayesian Persuasion, Information Economics, Game Theory🔬 ResearchAnalyzed: Jan 3, 2026 18:53

Axiomatic Foundations of Bayesian Persuasion

Published:Dec 29, 2025 12:10
1 min read
ArXiv

Analysis

This paper explores the theoretical underpinnings of Bayesian persuasion, a framework where a principal strategically influences an agent's decisions by providing information. The core contribution lies in developing axiomatic models and an elicitation method to understand the principal's information acquisition costs, even when they actively manage the agent's biases. This is significant because it provides a way to analyze and potentially predict how individuals or organizations will strategically share information to influence others.
Reference

“The paper provides an elicitation method using only observable menu-choice data of the principal, which shows how to construct the principal's subjective costs of acquiring information even when he anticipates managing the agent's bias.”

PermalinkArXiv
Research Paper#AI Security, Web Agents, Prompt Injection🔬 ResearchAnalyzed: Jan 3, 2026 19:11

Web Agent Persuasion Benchmark

Published:Dec 29, 2025 01:09
1 min read
ArXiv

Analysis

This paper introduces a benchmark (TRAP) to evaluate the vulnerability of web agents (powered by LLMs) to prompt injection attacks. It highlights a critical security concern as web agents become more prevalent, demonstrating that these agents can be easily misled by adversarial instructions embedded in web interfaces. The research provides a framework for further investigation and expansion of the benchmark, which is crucial for developing more robust and secure web agents.
Reference

“Agents are susceptible to prompt injection in 25% of tasks on average (13% for GPT-5 to 43% for DeepSeek-R1).”

PermalinkArXiv
Research Paper#Team Dynamics, Production, Economics🔬 ResearchAnalyzed: Jan 3, 2026 19:40

Team Disagreement Boosts Performance

Published:Dec 28, 2025 00:45
1 min read
ArXiv

Analysis

This paper investigates the impact of disagreement within teams on their performance in a dynamic production setting. It argues that initial disagreements about the effectiveness of production technologies can actually lead to higher output and improved team welfare. The findings suggest that managers should consider the degree of disagreement when forming teams to maximize overall productivity.
Reference

“A manager maximizes total expected output by matching coworkers' beliefs in a negative assortative way.”

PermalinkArXiv
Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 07:29

Emergent Persuasion: Will LLMs Persuade Without Being Prompted?

Published:Dec 20, 2025 21:09
1 min read
ArXiv

Analysis

This article explores the potential for Large Language Models (LLMs) to exhibit persuasive capabilities without explicit prompting. It likely investigates how LLMs might unintentionally or implicitly influence users through their generated content. The research probably analyzes the mechanisms behind this emergent persuasion, potentially examining factors like tone, style, and information presentation.

Key Takeaways

    Reference

    “”

    PermalinkArXiv
    Research#Persuasion🔬 ResearchAnalyzed: Jan 10, 2026 11:21

    Analyzing Human and AI Persuasion in Debate: An Aristotelian Approach

    Published:Dec 14, 2025 19:46
    1 min read
    ArXiv

    Analysis

    This research analyzes prepared arguments using rhetorical principles, offering insights into human and AI persuasive techniques. The study's focus on national college debate provides a real-world context for understanding how persuasion functions.
    Reference

    “The research analyzes prepared arguments through Aristotle's rhetorical principles.”

    PermalinkArXiv
    Research#Search🔬 ResearchAnalyzed: Jan 10, 2026 11:35

    Transparency in Conversational Search: How Source Presentation Shapes User Behavior

    Published:Dec 13, 2025 06:39
    1 min read
    ArXiv

    Analysis

    This ArXiv paper examines the impact of source presentation on user engagement, interaction, and persuasion within conversational search interfaces. It's a valuable contribution to understanding how transparency, a key element of responsible AI, influences user perception and trust.
    Reference

    “The paper likely explores different methods of presenting source information within conversational search.”

    PermalinkArXiv
    Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 07:55

    The Effect of Belief Boxes and Open-mindedness on Persuasion

    Published:Dec 6, 2025 21:31
    1 min read
    ArXiv

    Analysis

    This article likely explores how pre-existing beliefs (belief boxes) and the degree of open-mindedness influence an individual's susceptibility to persuasion. It probably examines the cognitive processes involved in accepting or rejecting new information, particularly in the context of AI or LLMs, given the 'llm' topic tag. The research likely uses experiments or simulations to test these effects.

    Key Takeaways

      Reference

      “”

      PermalinkArXiv
      Technology#AI Ethics👥 CommunityAnalyzed: Jan 3, 2026 08:40

      How elites could shape mass preferences as AI reduces persuasion costs

      Published:Dec 4, 2025 08:38
      1 min read
      Hacker News

      Analysis

      The article suggests a potential for manipulation and control. The core concern is that AI lowers the barrier to entry for persuasive techniques, enabling elites to more easily influence public opinion. This raises ethical questions about fairness, transparency, and the potential for abuse of power. The focus is on the impact of AI on persuasion and its implications for societal power dynamics.
      Reference

      “The article likely discusses how AI tools can be used to personalize and scale persuasive messaging, potentially leading to a more concentrated influence on public opinion.”

      PermalinkHacker News
      Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 08:11

      Polarization by Design: How Elites Could Shape Mass Preferences as AI Reduces Persuasion Costs

      Published:Dec 3, 2025 18:33
      1 min read
      ArXiv

      Analysis

      This article explores the potential for AI to be used to manipulate public opinion and exacerbate societal polarization. It suggests that the reduced cost of persuasion due to AI could allow elites to more effectively shape mass preferences, raising concerns about the ethical implications and potential for misuse of this technology.
      Reference

      “”

      PermalinkArXiv
      Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 08:12

      LLM-Generated Ads: From Personalization Parity to Persuasion Superiority

      Published:Dec 3, 2025 02:13
      1 min read
      ArXiv

      Analysis

      This article likely explores the advancements in using Large Language Models (LLMs) for generating advertisements. It suggests a progression from simply matching existing personalization techniques to achieving superior persuasive capabilities. The source, ArXiv, indicates this is a research paper, implying a focus on technical details and experimental results rather than general market analysis.

      Key Takeaways

        Reference

        “”

        PermalinkArXiv
        Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 08:02

        A Hybrid Theory and Data-driven Approach to Persuasion Detection with Large Language Models

        Published:Nov 27, 2025 04:59
        1 min read
        ArXiv

        Analysis

        This article presents a research paper on persuasion detection using Large Language Models (LLMs). The approach combines theoretical understanding with data-driven methods, suggesting a potentially robust and nuanced approach to identifying persuasive techniques in text. The focus on LLMs indicates a contemporary and relevant area of research.
        Reference

        “The article likely details the specific hybrid methodology, datasets used, and evaluation metrics.”

        PermalinkArXiv
        Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 10:15

        Proactive Defense: Compound AI for Detecting Persuasion Attacks and Measuring Inoculation Effectiveness

        Published:Nov 23, 2025 07:49
        1 min read
        ArXiv

        Analysis

        This article, sourced from ArXiv, likely presents research on using AI to identify and counter persuasive attacks, potentially focusing on techniques to measure the effectiveness of inoculation strategies. The term "compound AI" suggests a multi-faceted approach, possibly involving different AI models working together. The focus on persuasion attacks implies a concern with misinformation, manipulation, or other forms of influence. The research likely aims to develop methods for detecting these attacks and evaluating the success of countermeasures.

        Key Takeaways

          Reference

          “”

          PermalinkArXiv
          Research#Debating AI🔬 ResearchAnalyzed: Jan 10, 2026 14:27

          AI System Excels in Policy Debate

          Published:Nov 22, 2025 00:45
          1 min read
          ArXiv

          Analysis

          The article's focus on an autonomous policy debating system hints at significant advancements in AI's argumentative capabilities. However, without specifics, evaluating its impact is difficult, and the source (ArXiv) suggests early-stage research rather than a readily available product.
          Reference

          “A superpersuasive autonomous policy debating system is discussed.”

          PermalinkArXiv
          Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 11:54

          PARROT: Persuasion and Agreement Robustness Rating of Output Truth -- A Sycophancy Robustness Benchmark for LLMs

          Published:Nov 21, 2025 13:01
          1 min read
          ArXiv

          Analysis

          This article introduces PARROT, a new benchmark designed to assess the robustness of Large Language Models (LLMs) against sycophancy. It focuses on evaluating how well LLMs maintain truthfulness and avoid being overly influenced by persuasive or agreeable prompts. The benchmark likely involves testing LLMs with prompts designed to elicit agreement or to subtly suggest incorrect information, and then evaluating the LLM's responses for accuracy and independence of thought. The use of 'Persuasion and Agreement Robustness' in the title suggests a focus on the LLM's ability to resist manipulation and maintain its own understanding of facts.

          Key Takeaways

            Reference

            “”

            PermalinkArXiv
            Research#Negotiation🔬 ResearchAnalyzed: Jan 10, 2026 14:43

            AI Negotiation: Shifting from Passive to Persuasive Strategies

            Published:Nov 16, 2025 23:33
            1 min read
            ArXiv

            Analysis

            This ArXiv article likely explores how AI models can be designed to engage in more sophisticated and effective negotiations by incorporating emotional intelligence. The focus on persuasive techniques suggests a move toward AI agents that can actively influence human decision-making.
            Reference

            “The research likely investigates how AI can leverage emotional nuance in negotiations.”

            PermalinkArXiv
            AI News#LLM, AI Safety, AI Ethics📝 BlogAnalyzed: Jan 3, 2026 06:27

            Import AI 422: LLM bias; China cares about the same safety risks as us; AI persuasion

            Published:Jul 28, 2025 12:31
            1 min read
            Import AI

            Analysis

            The article discusses LLM bias, shared AI safety concerns between China and other nations, and AI persuasion techniques. The mention of the "Sentience Accords" suggests a focus on advanced AI and its potential implications.

            Key Takeaways

            Reference

            “N/A”

            PermalinkImport AI
            Research#AI Agents👥 CommunityAnalyzed: Jan 3, 2026 08:50

            CICERO: An AI agent that negotiates, persuades, and cooperates with people

            Published:Nov 22, 2022 15:24
            1 min read
            Hacker News

            Analysis

            The article highlights the development of an AI agent, CICERO, capable of complex social interactions like negotiation, persuasion, and cooperation. This suggests advancements in AI's ability to understand and respond to human social dynamics, potentially impacting fields like game playing, customer service, and conflict resolution. The focus on these specific abilities indicates a move beyond simple task completion towards more nuanced and human-like interaction.
            Reference

            “N/A (Based on the provided summary, there are no direct quotes.)”

            PermalinkHacker News