5 papers
AI Debaters are More Persuasive when Arguing in Alignment with Their Own Beliefs
MarÃa Victoria Carro, Denise Alejandra Mester, Facundo Nieto +9
The core premise of AI debate as a scalable oversight technique is that it is harder to lie convincingly than to refute a lie, enabling the judge to identify the correct position.…
Do Large Language Models Show Biases in Causal Learning? Insights from Contingency Judgment
MarÃa Victoria Carro, Denise Alejandra Mester, Francisca Gauna Selasco +4
Causal learning is the cognitive process of developing the capability of making causal inferences based on available information, often guided by normative principles. This process…
A Conceptual Framework for AI Capability Evaluations
MarÃa Victoria Carro, Denise Alejandra Mester, Francisca Gauna Selasco +7
As AI systems advance and integrate into society, well-designed and transparent evaluations are becoming essential tools in AI governance, informing decisions by providing evidence…
Do Large Language Models Show Biases in Causal Learning?
Maria Victoria Carro, Francisca Gauna Selasco, Denise Alejandra Mester +4
Causal learning is the cognitive process of developing the capability of making causal inferences based on available information, often guided by normative principles. This process…
Are UFOs Driving Innovation? The Illusion of Causality in Large Language Models
MarÃa Victoria Carro, Francisca Gauna Selasco, Denise Alejandra Mester +1
Illusions of causality occur when people develop the belief that there is a causal connection between two variables with no supporting evidence. This cognitive bias has been propos…