arXiv subjects

Kostas Karpouzis

Publications and source records attributed to Kostas Karpouzis.

14 recordsLinked to original sources

arXiv2026

A Critical Analysis of Trustworthy AI Tools, Mark Frameworks, and the Implementation Chasms

As artificial intelligence (AI) systems increasingly impact society, ensuring their ethical and trustworthy deployment has become a global priority. While a myriad of high-level ethical guidelines have emerged, criticism persists that these frameworks remain abstract and lack concrete mechanisms for implementation. This paper conducts a critical analysis of tools and trust mark frameworks intended to operationalize trustworthy AI (TAI), drawing on a comprehensive dataset from the OECD. Through empirical mapping and descriptive comparative analysis, we identify significant asymmetries in ethical focus, lifecycle coverage, stakeholder targeting, and tool typology. Our findings show a strong emphasis on fairness, transparency, and robustness, with comparatively little attention paid to explainability, digital security, and environmental sustainability. Moreover, most tools and certifications concentrate on post-development stages, with limited guidance for early design or data collection phases. Educational initiatives and policy engagement are notably underdeveloped, suggesting that current TAI efforts are dominated by technical and procedural measures within industry contexts. We argue that bridging the persistent chasm between AI principles and practice requires expanding ethical objectives, embedding ethics across the AI lifecycle, and fostering broader multi-stakeholder participation. This study provides both a diagnosis of existing implementation gaps and actionable recommendations for advancing more holistic, inclusive, and enforceable AI governance

cs.AI↗

arXiv2024

Artificial Intelligence in Education: Ethical Considerations and Insights from Ancient Greek Philosophy

This paper explores the ethical implications of integrating Artificial Intelligence (AI) in educational settings, from primary schools to universities, while drawing insights from ancient Greek philosophy to address emerging concerns. As AI technologies increasingly influence learning environments, they offer novel opportunities for personalized learning, efficient assessment, and data-driven decision-making. However, these advancements also raise critical ethical questions regarding data privacy, algorithmic bias, student autonomy, and the changing roles of educators. This research examines specific use cases of AI in education, analyzing both their potential benefits and drawbacks. By revisiting the philosophical principles of ancient Greek thinkers such as Socrates, Aristotle, and Plato, we discuss how their writings can guide the ethical implementation of AI in modern education. The paper argues that while AI presents significant challenges, a balanced approach informed by classical philosophical thought can lead to an ethically sound transformation of education. It emphasizes the evolving role of teachers as facilitators and the importance of fostering student initiative in AI-rich environments.

cs.CY↗

arXiv2024

What would Plato say? Concepts and notions from Greek philosophy applied to gamification mechanics for a meaningful and ethical gamification

Gamification, the integration of game mechanics in non-game settings, has become increasingly prevalent in various digital platforms; however, its ethical and societal impacts are often overlooked. This paper delves into how Platonic and Aristotelian philosophies can provide a critical framework for understanding and evaluating the ethical dimensions of gamification. Plato's allegory of the cave and theory of forms are used to analyse the perception of reality in gamified environments, questioning their authenticity and the value of virtual achievements, while Aristotle's virtue ethics, with its emphasis on moderation, virtue, and eudaimonia (true and full happiness), can help assess how gamification influences user behaviour and ethical decision-making. The paper critically examines various gamification elements, such as the hero's journey, altruistic actions, badge levels, and user autonomy, through these philosophical lenses, and addresses the ethical responsibilities of gamification designers, advocating for a balanced approach that prioritizes user well-being and ethical development over commercial interests. By bridging ancient philosophical insights with modern digital culture, this research contributes to a deeper understanding of the ethical implications of gamification, emphasizing the need for responsible and virtuous design in digital applications.

cs.HC↗

arXiv2024

Tailoring Education with GenAI: A New Horizon in Lesson Planning

The advent of Generative AI (GenAI) in education presents a transformative approach to traditional teaching methodologies, which often overlook the diverse needs of individual students. This study introduces a GenAI tool, based on advanced natural language processing, designed as a digital assistant for educators, enabling the creation of customized lesson plans. The tool utilizes an innovative feature termed 'interactive mega-prompt,' a comprehensive query system that allows educators to input detailed classroom specifics such as student demographics, learning objectives, and preferred teaching styles. This input is then processed by the GenAI to generate tailored lesson plans. To evaluate the tool's effectiveness, a comprehensive methodology incorporating both quantitative (i.e., % of time savings) and qualitative (i.e., user satisfaction) criteria was implemented, spanning various subjects and educational levels, with continuous feedback collected from educators through a structured evaluation form. Preliminary results show that educators find the GenAI-generated lesson plans effective, significantly reducing lesson planning time and enhancing the learning experience by accommodating diverse student needs. This AI-driven approach signifies a paradigm shift in education, suggesting its potential applicability in broader educational contexts, including special education needs (SEN), where individualized attention and specific learning aids are paramount

cs.CY↗

arXiv2023

Legal and ethical considerations regarding the use of ChatGPT in education

Artificial intelligence has evolved enormously over the last two decades, becoming mainstream in different scientific domains including education, where so far, it is mainly utilized to enhance administrative and intelligent tutoring systems services and academic support. ChatGPT, an artificial intelligence-based chatbot, developed by OpenAI and released in November 2022, has rapidly gained attention from the entire international community for its impressive performance in generating comprehensive, systematic, and informative human-like responses to user input through natural language processing. Inevitably, it has also rapidly posed several challenges, opportunities, and potential issues and concerns raised regarding its use across various scientific disciplines. This paper aims to discuss the legal and ethical implications arising from this new technology, identify potential use cases, and enrich our understanding of Generative AI, such as ChatGPT, and its capabilities in education.

cs.CY↗

arXiv2022

Identification of Common Trends in Political Speech in Social Media using Sentiment Analysis

Social Media have been extensively used for commercial and political communication, besides their initial scope of providing an easy-to-use outlet to produce and consume user-generated content. Besides being a popular medium, Social Media have definitely changed the way we express ourselves or where we look for emerging news and commentary, especially during troubled times. In this paper, we examine a corpus assembled from the Twitter accounts of politicians in the United States and annotated with respect to their audience and the sentiment they convey with each post. Our purpose is to examine whether there are stylistic differences among representatives of different political ideologies, directed to different audiences or with dissimilar agendas. Our findings verify existing knowledge from conventional written communication and can be used to evaluate the quality and depth of political expression and dialogue, especially during the period leading to an election.

cs.SI↗

arXiv2021

How player and opponent personalities influence cooperative gameplay

Research has shown that digital game players often feel engagement and rapport with a game hero or character when they can channel their own ambitions and goals through the hero's journey in the game world; in essence, they feel a sense of accomplishment and fulfilment whenever they put the game mechanics to use to help the hero reach a positive ending to the game quests. In the case of cooperative gameplay, rapport also has to do with their perception of their peers' skills, gameplay style and behaviour within the game. In this paper, we describe an experiment to identify whether matching players with different personalities, as characterized by the OCEAN or Big-5 personality model, can influence their player experience with a custom-made, cooperative game.

cs.MM↗

arXiv2021

Integrating psychotherapy practices and gamified elements in novel game mechanics for stress relief

We explore novel game mechanics and techniques in the domain of gamified and game-based mobile mental health applications. By combining modern game design elements with techniques applied by practitioners (e.g., therapists) and known mechanics used in relevant games, we developed an integrated mobile game. Playtesting with a group of individuals showed a positive response towards the study's claims and a promising direction for further research.

cs.HC↗

arXiv2021

How Camera Placement Affects Gameplay in Video Games

In video games, players' perception of the game world and related information depends on their or the game designer's choice of a virtual camera model. In this paper, we attempt to answer the research question of whether it is possible to identify which camera model is preferred by, fits and best serves each player depending on where they are in a game world and the kinds of challenges they face. To this end, a special type of video game, combining challenges from different game genres, was designed and developed with Unity; thirty players could choose from four camera models at their disposal, depending on where they were in the game world, and utilize the most suitable one to proceed. Each player's preference of camera model was collected using the data platform Unity Analytics and then analyzed. The analysis of the results showed that players managed to adapt to the logic and requirements of the game challenges by choosing different cameras for each of them, depending on the spatial requirements and the presence of enemies or platforms they should jump across from.

cs.MM↗

arXiv2021

AI in (and for) Games

This chapter outlines the relation between artificial intelligence (AI) / machine learning (ML) algorithms and digital games. This relation is two-fold: on one hand, AI/ML researchers can generate large, in-the-wild datasets of human affective activity, player behaviour (i.e. actions within the game world), commercial behaviour, interaction with graphical user interface elements or messaging with other players, while games can utilise intelligent algorithms to automate testing of game levels, generate content, develop intelligent and responsive non-player characters (NPCs) or predict and respond player behaviour across a wide variety of player cultures. In this work, we discuss some of the most common and widely accepted uses of AI/ML in games and how intelligent systems can benefit from those, elaborating on estimating player experience based on expressivity and performance, and on generating proper and interesting content for a language learning game.

cs.AI↗

arXiv2021

Developing for personalised learning: the long road from educational objectives to development and feedback

This paper describes the development needed to support the functional and teaching requirements of iRead, a 4-year EU-funded project which produced an award-winning serious game utilising lexical and syntactical game content. The main functional requirement was that the game should retain different profiles for each student, encapsulating both the respective language model (which language features should be taught/used in the game first, before moving on to more advanced ones) and the user model (mastery level for each feature, as reported by the student's performance in the game). In addition to this, researchers and stakeholders stated additional requirements related to learning objectives and strategies to make the game more interesting and successful; these were implemented as a set of selection rules which take into account not only the mastery level for each feature, but also respect the priorities set by teachers, helping avoid repetition of content and features, and maintaining a balance between new content and revision of already mastered features to give students the sense of progress, while also reinforcing learning.

cs.HC↗

arXiv2021

From pixels to notes: a computational implementation of synaesthesia for cultural artefacts

Synaesthesia is a condition that enables people to sense information in the form of several senses at once. This work describes a Python implementation of a simulation of synaesthesia between listening to music and viewing a painting. Based on Scriabin's definition, we developed a deterministic process to produce a melody after processing a painting, mimicking the production of notes from colours in the field of view of persons experiencing synaesthesia.

cs.HC↗

arXiv2020

A compact sequence encoding scheme for online human activity recognition in HRI applications

Human activity recognition and analysis has always been one of the most active areas of pattern recognition and machine intelligence, with applications in various fields, including but not limited to exertion games, surveillance, sports analytics and healthcare. Especially in Human-Robot Interaction, human activity understanding plays a crucial role as household robotic assistants are a trend of the near future. However, state-of-the-art infrastructures that can support complex machine intelligence tasks are not always available, and may not be for the average consumer, as robotic hardware is expensive. In this paper we propose a novel action sequence encoding scheme which efficiently transforms spatio-temporal action sequences into compact representations, using Mahalanobis distance-based shape features and the Radon transform. This representation can be used as input for a lightweight convolutional neural network. Experiments show that the proposed pipeline, when based on state-of-the-art human pose estimation techniques, can provide a robust end-to-end online action recognition scheme, deployable on hardware lacking extreme computing capabilities.

cs.CV↗

arXiv2020

Open and Cultural Data Games for Learning

Educators often seek ways to introduce gaming in the classroom in order to break the usual teaching routine, expand the usual course curriculum with additional knowledge, but mostly as a means to motivate students and increase their engagement with the course content. Even though the vast majority of students find gaming to be appealing and a welcome change to the usual teaching practice, many educators and parents doubt their educational value; in this paper, we discuss a card game designed to teach environmental matters to early elementary school students, using open data. We present a comparative study of how the game increased the students' interest for the subject, as well as their performance and engagement to the course, compared with conventional teaching and a Prezi presentation used to teach the same content to other student groups.

cs.CY↗