Large Language Models (LLMs) are already as persuasive as humans. However, we know very little about how they do it. This paper investigates the persuasion strategies of LLMs, comparing them with human-generated arguments. Using a dataset of 1,251 participants in … Continued
Recent generative AI systems have demonstrated more advanced persuasive capabilities and are increasingly permeating areas of life where they can influence decision-making. Generative AI presents a new risk profile of persuasion due the opportunity for reciprocal exchange and prolonged interactions. … Continued
Value capture occurs when an agent’s values are rich and subtle; they enter a social environment that presents simplified — typically quantified — versions of those values; and those simplified articulations come to dominate their practical reasoning. Examples include becoming … Continued
Consider the following two (hypothetical) generic causal claims: “Living in a neighborhood with many families with children increases purchases of bicycles” and “living in an affluent neighborhood with many families with children increases purchases of bicycles.” These claims not only … Continued
Abstract Growing concern surrounds the impact of social media platforms on public discourse1,2,3,4 and their influence on social dynamics5,6,7,8,9, especially in the context of toxicity10,11,12. Here, to better understand these phenomena, we use a comparative approach to isolate human behavioural … Continued
Abstract The dramatic expansion of internet communication tools has led to the increased use of temporary online groups to solve problems, provide services, or produce new knowledge. However, many of these groups need help to collaborate effectively. The rapid development … Continued
This paper explores the transformative potential of computer-assisted textual analysis in enhancing instructional quality through in-depth insights from educational artifacts. We integrate Richard Elmore’s Instructional Core Framework to examine how artificial intelligence (AI) and machine learning (ML) methods, particularly natural … Continued
Human choices are context-dependent, and options evaluation is biased by the quality and quantity of available alternatives. In the attraction effect, apparently irrelevant dominated decoys have proven effective in shifting preferences in numerous laboratory experiments, yet its relevance in real-life … Continued
Abstract This study investigates the efficacy of an AI-based ethical advisor using the GPT-4 model. Drawing from a pool of ethical dilemmas published in the New York Times column “The Ethicist”, we compared the ethical advice given by the human … Continued
As artificial intelligence (AI) advances, human-AI collaboration has become increasingly prevalent across both professional and everyday settings. In such collaboration, AI can express its confidence level about its performance, serving as a crucial indicator for humans to evaluate AI’s suggestions. … Continued