Related papers: Artificial Intelligence for Conflict Management
Our poster presents ConflictLens, a three-stage simulation system powered by large language models (LLMs) and grounded in psychological theory, designed to help users reflect on and practice conflict resolution in romantic relationships.…
Background: What counts as violence is neither self-evident nor universally agreed upon. While physical aggression is prototypical, contemporary societies increasingly debate whether exclusion, humiliation, online harassment or symbolic…
In this paper, in an attempt to improve power grid resilience, a machine learning model is proposed to predictively estimate the component states in response to extreme events. The proposed model is based on a multi-dimensional Support…
Cognitive control, the ability to coordinate competing information sources in pursuit of goals, is fundamental to intelligent behavior. We systematically investigate whether Vision Language Models (VLMs) exhibit cognitive control and how…
Social hierarchy in animal groups carries a crucial adaptive function by reducing conflict and injury while protecting valuable group resources. Social hierarchy is dynamic and can be altered by social conflict, agonistic interactions, and…
Neural networks (NNs) can achieved high performance in various fields such as computer vision, and natural language processing. However, deploying NNs in resource-constrained safety-critical systems has challenges due to uncertainty in the…
Language is both a cause and a consequence of the social processes that lead to conflict or peace. Hate speech can mobilize violence and destruction. What are the characteristics of peace speech that reflect and support the social processes…
This draft article outlines a prediction challenge where the target is to forecast the number of fatalities in armed conflicts, in the form of the UCDP `best' estimates, aggregated to the VIEWS units of analysis. It presents the format of…
This paper presents Networks of Influence Diagrams (NID), a compact, natural and highly expressive language for reasoning about agents beliefs and decision-making processes. NIDs are graphical structures in which agents mental models are…
The concepts of conditional mutual information (CMI) and normalized conditional mutual information (NCMI) are introduced to measure the concentration and separation performance of a classification deep neural network (DNN) in the output…
Understanding how different stakeholders perceive risks in AI systems is essential for their responsible deployment. This paper presents a framework for stakeholder-grounded risk assessment by using LLMs, acting as judges to predict and…
Knowledge-based or Artificial Intelligence techniques are used increasingly as alternatives to more classical techniques to model ENVIRONMENTAL SYSTEMS. Use of Artificial Intelligence (AI) in environmental modelling has increased with…
The efficient integration of multisensory observations is a key property of the brain that yields the robust interaction with the environment. However, artificial multisensory perception remains an open issue especially in situations of…
Conflict transformation and management are complex decision processes with extremely high stakes at hand and could greatly benefit from formal approaches to decision support. For this purpose we develop a general framework about how to use…
Artificial Intelligence (AI) and its relation with societies is increasingly becoming an interesting object of study from the perspective of sociology and other disciplines. Theories such as the Economy of Conventions (EC) are usually…
The so-called Mild Cognitive Impairment (MCI) or cognitive loss appears in a previous stage before Alzheimer's Disease (AD), but it does not seem sufficiently severe to interfere in independent abilities of daily life, so it usually does…
Foreign information operations on social media platforms pose significant risks to democratic societies. With the rise of Artificial Intelligence (AI), this threat is likely to intensify, potentially overwhelming human defenders. To achieve…
This paper investigates the emerging challenges posed by the integration of Artificial Intelligence (AI) in the military domain, particularly within the context of United Nations Security Council Resolution 1540 (UNSCR 1540), which seeks to…
In this paper, we present an approach to neural network mean-field-type control and its stochastic stability analysis by means of adversarial inputs (aka adversarial attacks). This is a class of data-driven mean-field-type control where the…
Adversarial Machine Learning (AML) is emerging as a major field aimed at protecting machine learning (ML) systems against security threats: in certain scenarios there may be adversaries that actively manipulate input data to fool learning…