Single Player Roleplaying Game (SPRPG) is a popular genre among players as well as developers, with recent blockbuster titles such as Skyrim by Bethesda and Mass E↵ect 3 by Bioware. In recent years, an occurrence that have been gaining a lot of attention is the development of more advanced and vivid Artificial Intelligence (AI) within these SPRPG and a lot of progress has been made towards making the Non-player Character (NPC) more vivacious and life-like. It is, however, still a common occurrence that NPCs wait around for the player to interact with them; never having a plan or agenda of their own. Their purpose seem to be to wait for the player and provide him or her with information, bartering or a quest. This could result in a game environment that feels static and lifeless to some players and, thus, possibly become detrimental to the game experience. The main objective of this thesis was to implement a need-based system, resembling, to some degree, the one used in The Sims by Maxis, where NPCs get hungry, thirsty, sleepy and similar, and to test whether this system will enhance the game experience. If the NPCs of a SPRPG have needs of their own and therefore can not just wait around for the player to come to them, it may make the game experience more life-like and dynamic. A need-based system that allows the designer to define a set of needs for each NPC, was implemented using the Aurora Toolset for Neverwinter Nights by Bioware. The system was then tested by allowing a number of people play a custom module for Neverwinter Nights twice: once with the system in place and once without, then answering questionnaires regarding their experience. The results show, unanimously, that this prototype did enhance the game experience. Though this was a small module and only a prototype, it does indicates that the use of a need-based system might indeed enhance the dynamic and vivacity of a SPRPG. / Singleplayer-rollspel är en populär genre bland såväl spelare som utvecklare, med stora titlar såsom Skyrim av Bethesda och Mass Effect 3 av Bioware. På senare tid har utvcklandet av levande och avancerad AI erhållit mycket fokus inom denna typ av spel och stora framsteg har tagits vad gäller att skapa levnadslika och realistiska icke-spelarkaraktärer. Det är dock fortfarande en vanlig förekomst att ickespelarkaraktärer i denna typ av spel saknar en egen agenda eller plan och därför endast står och väntar på att spelaren ska interagera med dem. Denna uppsats har syftat till att implementera ett behovsbaserat system som till viss del liknar det som används i The Sims av Maxis, där icke-spelarkaraktärer blir hungriga, trötta och liknande, och att testa huruvida detta system förhöjer spelupplevelsen. Systemet har implementerats med hjälp av Aurora Toolset till Neverwinter Nights av Bioware och har testats av ett antal personer i en egenskapad modul till spelet. Resultatet har visat, entydigt, att implementationen av detta behovsbaserade system förhöjde spelupplevelsen. Även om systemet, i denna version, är en prototyp, ger det en indikation på att användandet av ett behovsbaserat system kan förhöja spelupplvelsen i ett singeplayer-rollspel.

This thesis aims to conduct a socio-political discourse analysis (SPDA) of digital articles discussing "The Portrait of Edmond Belamy," created by the Obvious team using AI. The sale of this portrait at Christie's auction for a record $432,500 excited the world. This was the first work sold at auction and created in collaboration with AI. The purpose is to explore AI and its integration into artistic practices and media discourse surrounding the event. The research question this dissertation seeks to explore is: "How AI-generated art, namely the portrait of Edmond de Belamy, is represented in digital media?". The sample consists of 12 articles from the UK and the USA outlets. It is analysed according to Van Dijk’s SPDA concepts as well as Actor-Network Theory (ANT) and Media Dissemination theory. Speaking about key findings, it can be mentioned that political-oriented magazines stress authenticity, while those on art and technology explore broader themes. Power dynamics among stakeholders shape perceptions of AI art, influencing its reception and evaluation. Market recognition at auctions underscores its value, reshaping perceptions of artistic worth. Ethical concerns raise questions on intellectual property, authorship, and code attribution, necessitating regulatory frameworks. Critical analysis provides diverse views on AI-generated artworks, challenging traditional notions of creativity and authenticity. The discourse reflects societal attitudes towards technology, creativity, and cultural production. Understanding AI art's implications aids informed dialogue and decision-making. Future research on practitioners' experiences offers insights into human-AI interactions in creativity, contributing to a nuanced understanding of this interplay.

<p dir="ltr">We present a framework for Trustworthy Artificial Intelligence (TAI) that dynamically assesses trust and scrutinizes past decision-making, aiming to identify both individual and community behavior. The modeling of behavior incorporates proposed concepts, namely trust pressure and trust sensitivity, laying the foundation for predicting future decision-making regarding community behavior, consensus level, and decision-making duration. Our framework involves the development and mathematical modeling of trust pressure and trust sensitivity, drawing on social validation theory within the context of environmental decision-making. To substantiate our approach, we conduct experiments encompassing (i) dynamic trust sensitivity to reveal the impact of learning actors between decision-making, (ii) multi-level trust measurements to capture disruptive ratings, and (iii) different distributions of trust sensitivity to emphasize the significance of individual progress as well as overall progress.</p><p dir="ltr">Additionally, we introduce TAI metrics, trustworthy acceptance, and trustworthy fairness, designed to evaluate the acceptance of decisions proposed by AI or humans and the fairness of such proposed decisions. The dynamic trust management within the framework allows these TAI metrics to discern support for decisions among individuals with varying levels of trust. We propose both the metrics and their measurement methodology as contributions to the standardization of trustworthy AI.</p><p dir="ltr">Furthermore, our trustability metric incorporates reliability, resilience, and trust to evaluate systems with multiple components. We illustrate experiments showcasing the effects of different trust declines on the overall trustability of the system. Notably, we depict the trade-off between trustability and cost, resulting in net utility, which facilitates decision-making in systems and cloud security. This represents a pivotal step toward an artificial control model involving multiple agents engaged in negotiation.</p><p dir="ltr">Lastly, the dynamic management of trust and trustworthy acceptance, particularly in varying criteria, serves as a foundation for causal AI by providing inference methods. We outline a mechanism and present an experiment on human-driven causal inference, where participant discussions act as interventions, enabling counterfactual evaluations once actor and community behavior are modeled.</p>