Deceptive AI and Society

Deceptive artificial intelligence (AI) is a heavily loaded term. Its semantic load has become exponentially heavier in a very short period of time. Perhaps, most of this semantic load, at least in the recent public sphere, has been placed on it because of the deployment of large language models (LLMs), such as ChatGPT. Deceptive AI is very multifaceted. Different AI approaches give rise to different types of AI technologies, or, in some cases, autonomous agents. Some of these technologies already exist in practice, others exist in theory, some are transitioning between theory to implementation, and, finally, some are still only fictions of our shared imagination [62]

Self-Governing Hybrid Societies and Deception

Self-governing hybrid societies are multi-agent systems where humans and machines interact by adapting to each other’s behaviour. Advancements in Artificial Intelligence (AI) have brought an increasing hybridisation of our societies, where one particular type of behaviour has become more and more prevalent, namely deception. Deceptive behaviour as the propagation of disinformation can have negative effects on a society's ability to govern itself. However, self-governing societies have the ability to respond to various phenomena. In this paper we explore how they respond to the phenomenon of deception from an evolutionary perspective considering that agents have limited adaptation skills. Will hybrid societies fail to govern deceptive behaviour and reach a Tragedy of The Digital Commons? Or will they manage to avoid it through cooperation? How resilient are they against large-scale deceptive attacks? We provide a tentative answer to some of these questions through the lens of evolutionary agent-based modelling, based on the scientific literature on deceptive AI and public goods games

Reflective Artificial Intelligence

As Artificial Intelligence (AI) technology advances, we increasingly delegate mental tasks to machines. However, today's AI systems usually do these tasks with an unusual imbalance of insight and understanding: new, deeper insights are present, yet many important qualities that a human mind would have previously brought to the activity are utterly absent. Therefore, it is crucial to ask which features of minds have we replicated, which are missing, and if that matters. One core feature that humans bring to tasks, when dealing with the ambiguity, emergent knowledge, and social context presented by the world, is reflection. Yet this capability is completely missing from current mainstream AI. In this paper we ask what reflective AI might look like. Then, drawing on notions of reflection in complex systems, cognitive science, and agents, we sketch an architecture for reflective AI agents, and highlight ways forward

Interoperable AI: Evolutionary Race Towards Sustainable Knowledge Sharing

Article and Supplementary MaterialInternational audienceThe advancement and deployment of artificial intelligent agents brought numerous benefits in knowledge and data gathering and processing. However, one of the key challenges in deploying such agents in an open environment like the Web is their interoperability as they currently mostly run in silos. In this paper we report on a simulation and evaluation based on evolutionary agent-based modelling to empirically test how sustainable different strategies are for knowledge sharing in open multi-agent systems (MAS). Our results show the importance of translation-based approaches and the need for incentives to support these

Everyday Argumentative Explanations for Classification

In this paper we study everyday explanations for classification tasks with formal argumentation. Everyday explanations describe how humans explain in day-to-day life, which is important when explaining decisions of AI systems to lay users. We introduce EVAX, a model-agnostic explanation method for classifiers with which contrastive, selected and social explanations can be generated. The resulting explanations can be adjusted in their size and retain high fidelity scores (an average of 0.95

Online Handbook of Argumentation for AI: Volume 1

This volume contains revised versions of the papers selected for the first volume of the Online Handbook of Argumentation for AI (OHAAI). Previously, formal theories of argument and argument interaction have been proposed and studied, and this has led to the more recent study of computational models of argument. Argumentation, as a field within artificial intelligence (AI), is highly relevant for researchers interested in symbolic representations of knowledge and defeasible reasoning. The purpose of this handbook is to provide an open access and curated anthology for the argumentation research community. OHAAI is designed to serve as a research hub to keep track of the latest and upcoming PhD-driven research on the theory and application of argumentation in all areas related to AI.Comment: editor: Federico Castagna and Francesca Mosca and Jack Mumford and Stefan Sarkadi and Andreas Xydi

Traditional Eastern European diet and mortality : prospective evidence from the HAPIEE study

Purpose: cardiovascular disease (CVD) and cancer mortality rates in Eastern Europe are among the highest in the world. Although diet is an important risk factor, traditional eating habits in this region have not yet been explored. This analysis assessed the relationship between traditional dietary pattern and mortality from all-causes, CVD and cancer in Eastern European cohorts. Methods: data from the Health, Alcohol and Psychosocial factors in Eastern Europe prospective cohort were used, including participants from Russia, Poland and the Czech Republic. Based on food frequency questionnaire data, we constructed an Eastern European diet score (EEDS) from nine food groups which can be considered as traditional in this region. The relationship between categorical (low, moderate, high) and continuous (range 0-18) EEDS and mortality was estimated with Cox-regression. Results: from 18,852 eligible participants, 2234 died during follow-up. In multivariable adjusted models, participants with high adherence to the traditional Eastern European diet had significantly higher risk of all-cause (HR 1.23; 95% CI 1.08-1.42) and CVD (1.34; 1.08-1.66) deaths compared to those with low adherence. The association with cancer mortality was only significant in Poland (high vs. low EEDS: 1.41; 1.00-1.98). From the specific EEDS components, high consumption of lard was significantly positively related to all three mortality outcomes, while preserved fruit and vegetable consumption showed consistent inverse associations. Conclusion: our results suggest that traditional eating habits may contribute to the poor health status, particularly the high CVD mortality rates, of populations in Eastern Europe. Adequate public health nutritional interventions in this region are essential