Sofia Almpani

Hate speech narratives represent a significant societal challenge, amplified by digital platforms, algorithmic recommendation systems, and sophisticated online communication. Existing approaches to counter such narratives focus on content detection, moderation, and compliance, often treating hostile expressions as isolated artefacts rather than broader socio-technical processes. The motivation behind this vision paper is based on the premise that hate speech narratives are produced and sustained through interactions among stakeholders, institutions, technologies, and social structures. Countering hate speech is not only a linguistic or computational challenge but also a socio-technical, ethical, legal, and organisational one, since the meaning and impact of hostile expressions depend on context, speaker intentions, platform dynamics, and wider social consequences. This paper argues that countering hate speech in the broader spectrum of hostile narratives requires a holistic Requirements Engineering (RE) perspective capable of integrating technological, linguistic, ethical, legal, and societal concerns. Building on goal-oriented requirements engineering, socio-technical systems analysis, argumentation, archetypes modelling, and systems thinking, the paper outlines a requirements-driven modelling framework to monitor, analyse, mitigate, and counter hostile narratives. The framework is grounded in the definition of hate speech characteristics developed through twin lenses: the delineation of expressions and the analysis of structural and behavioural characteristics of hate speech. By positioning the countering of hate speech narratives as an RE challenge, the aim is to stimulate new research directions that bridge technical innovation with societal values and democratic governance.

The growing impact of artificial intelligence on everyday life has fueled the emergence of Human–Centered Artificial Intelligence (HCAI), an approach aimed at developing intelligent systems that not only emulate and extend human capabilities but also foster meaningful collaboration, societal integration, and ethical responsibility. In this work, we present a comprehensive survey of the role of argumentation in HCAI, examining its theoretical foundations, methodologies, and applications, as well as its potential to enhance communication, informed decision-making, and responsible human–AI interaction across diverse domains. Building on this analysis, we introduce the Argumentation-based Proof-Event Calculus (APEC), a formal and aligned framework designed to support trustworthy collaboration between humans and AI agents in goal-oriented decision processes. The proposed APEC framework advances HCAI by explicitly incorporating temporal dynamics, evaluating both individual and collective agent contributions in multi-agent systems, and supporting the iterative refinement and evolution of decisions toward well-justified outcomes.

Creativity, informal reasoning and dynamic exchange of ideas form the pulsating heart of mathematical creation. In this approach, the concept of a mathematical object surpasses conventional boundaries of formal presentation, as they also encompass the intention to prove, significant creative stages within the proving, and the overall experience of prover's journey, which may involve arguments, debates, discovery insights, aesthetic visualizations, and narrative elements. In this paper we present two conceptual frameworks, namely Argumentation-based Proof-Events Calculus (APEC) and Mathematical RUPAs, in order to provide distinct yet interconnected perspectives on informal thinking, knowledge creation, and proving in mathematics. Following the two perspectives, we explore the nature of mathematical objects, the diverse roles of provers, and the influence of social and pluralistic factors in proving practices. Through this analysis, we aim to create a synthesis, named RUPAPEC, that elucidates how the creative and sociocultural dimensions presented in these two approaches can come together into a harmonious whole by mutually reinforcing each other. This theoretical synthesis embodies an ontological exploration delineating the essence and existence of mathematical objects as dynamic entities shaped by creative cognitive processes and interactive dialogues.

This paper explores the relationship between informal reasoning, creativity in mathematics, and problem solving. It underscores the importance of environments that promote interaction, hypothesis generation, examination, refutation, derivation of new solutions, drawing conclusions, and reasoning with others, as key factors in enhancing mathematical creativity. Drawing on argumentation logic, the paper proposes a novel approach to uncover specific characteristics in the development of formalized proving using “proof-events.” Argumentation logic can offer reasoning mechanisms that facilitate these environments. This paper proposes how argumentation can be implemented to discover certain characteristics in the development of formalized proving with “proof-events”. The concept of a proof-event was introduced by Goguen who described mathematical proof as a multi-agent social event involving not only “classical” formal proofs, but also other informal proving actions such as deficient or alleged proofs. Argumentation is an integral component of the discovery process for a mathematical proof since a proof necessitates a dialogue between provers and interpreters to clarify and resolve gaps or assumptions. By formalizing proof-events through argumentation, this paper demonstrates how informal reasoning and conflicts arising during the proving process can be effectively simulated. The paper presents an extended version of the proof-events calculus, rooted in argumentation theories, and highlights the intricate relationships among proof, human reasoning, cognitive processes, creativity, and mathematical arguments.

Proof requires a dialogue between agents to clarify obscure inference steps, fill gaps, or reveal implicit assumptions in a purported proof. Hence, argumentation is an integral component of the discovery process for mathematical proofs. This work presents how argumentation theories can be applied to describe specific informal features in the development of proof-events. The concept of proof-event was coined by Goguen who described mathematical proof as a public social event that takes place in space and time. This new meta-methodological concept is designed to cover not only “traditional” formal proofs but all kinds of proofs and inference steps, including incomplete or purported proofs. Our approach attempts to make proof-events more comprehensive to express the complete trajectory of a mathematical proof-event until the ultimate validation of the proving outcome. Thus, we advance an extended version of proof-event calculus which is built on argumentation theories designed to capture the internal and external structure of collaborative mathematical practice and highlight the relationship between proof, human reasoning, and cognitive processes. In addition, another area in which argumentation can make a significant contribution is dealing with the defeasible knowledge of the Web which is a product of its open and ubiquitous nature. This approach seems to be sufficient for the presentation of Web-based proving processes as manifested in the case of the Mini-Polymath 4 project.

As automation in robotics and artificial intelligence is increasing, we will need to automate a growing amount of ethical decision making. However, ethical decision-making raises novel challenges for designers, engineers, ethicists, and policymakers, who will have to explore new ways to realize this task. For example, engineers building wearable robots should take into consideration privacy aspects and their different context-based scenarios when programming the decision-making procedures. This in turn requires ethical input in order to respect norms concerning privacy and informed consent. The presented work focuses on the development and formalization of models that aim at ensuring a correct ethical behavior of artificial intelligent agents, in a provable way, extending and implementing a logic-based proving calculus. This leads to a formal theoretical framework of moral competence that could be implemented in artificial intelligent systems in order to best formalize certain parameters of ethical decision-making to ensure safety and justified trust.

In this paper, we introduce the subject of the special issue Trends in Argumentation Logic . Here we mainly describe two approaches to argumentation logic with explicating monotonic and non-monotonic, or defeasible, reasoning and explain the role of artificial intelligence in applying argumentation logic. Then we give a short overview of the papers contributed to the special issue.

As automation in artificial intelligence is increasing, we will need to automate a growing amount of ethical decision making. However, ethical decision- making raises novel challenges for engineers, ethicists and policymakers, who will have to explore new ways to realize this task. The presented work focuses on the development and formalization of models that aim at ensuring a correct ethical behaviour of artificial intelligent agents, in a provable way, extending and implementing a logic-based proving calculus that is based on argumentation reasoning with support and attack arguments. This leads to a formal theoretical framework of ethical competence that could be implemented in artificial intelligent systems in order to best formalize certain parameters of ethical decision-making to ensure safety and justified trust.

This work implements argumentation as the basis for modeling the relevant EU legislation concerning medical devices classification. Stakeholders can consult a web application for determining the risk-based class of a medical device based on the relevant legislation. The described approach is generally applicable to any other analogous cases of decision-making based on legislative regulations. One of the main advantages of using argumentation is the explainability and the high modularity of software permitting the extension and/or modification of the code when new relevant regulations become available.