This paper forms the foundation for an open-source library designed to implement an automated method for detecting fallacies in any type of speech, including speech-to-text features. The focus of this paper is on detecting false and manipulative discourse.

This paper is the base for an open-source library designed to implement the principles outlined in our research. The library, MADS, will allow data scientists and machine learning engineers to develop and implement data pipelines in a more efficient and collaborative way, including functionalities for the integration and management of multiple agents, where it optimizes the execution of complex tasks in data science.

Exploring the intersection of Artificial General Intelligence (AGI), autonomous drones and applied robotics, highlighting their transformative potential across sectors while addressing critical ethical concerns, particularly in warfare.