As Artificial Intelligence (AI) and automation become more intertwined, understanding their impact on user control is essential. This study investigates dynamic user control in AI-driven automated systems, particularly in work environments. While adaptive automation (AA) has been extensively studied, there's a gap in research on adaptable and hybrid automation, where users control the level of automation (LOA). We bridge this gap with a design-oriented case study structured into three phases, evaluating one adaptable and one hybrid prototype. By understanding real-world perspectives of users and providers of an AI-driven automation system, we address the question: "How can we support users with dynamic control when designing for human-centred automation?”. Our findings are synthesized into insights that suggest a preference for a hybrid approach; one that balances user and AI-system collaboration, providing adaptive and personalized support, without overwhelming adaptability. Overall, our results conclude the importance of human involvement in the automation process, underscoring the need for "human touch” in the design of humancentred automation (HCAI).

The increasing prevalence and familiarity of Artificial Intelligence (AI) significantly impact various life aspects, particularly in the creative domain. Understanding perspectives and motivations towards AI, especially among artistic individuals, is crucial due to the substantial influence of this technology on their work. This paper investigates attitudes toward AI and the factors driving the use of generative AI in creative processes. The study aims to determine if attitudes toward AI impact the motivation to utilize generative AI. Data were collected using the General Attitudes Towards Artificial Intelligence Scale (GAAIS) and the Motivational Factors Toward Generative AI Usage Measurement Scale (Gen-AI Scale). Results indicate that all six positive motivational factors equally influence the intention to use generative AI in creative fields, though they have only a moderate positive impact. Additionally, while the entire group showed notable differences between GAAIS and Gen-AI Scale scores, the distinction between artists and non-artists was not significant.

The traditional linear economy, using a take-make-dispose model is resourceintense and comes with adverse environmental impacts. Circular economy (CE) is regenerative and restorative by design and intention and is recommended as the business model for efficient use of resources. Despite the push for businesses and organisations to switch from linear to CE, there are several barriers/challenges that need solving such as business models and the criticism of CE projects often being small scale. Technology can be an enabler toward scaling up CE; however, the prime challenge is to identify technologies that can allow predicting, tracking and proactive monitoring of product's residual value, that can potentially motivate businesses to pursue circularity decisions. In this thesis, an Internet of Things (IoT)-enabled decision support system (DSS) for CE business model is proposed. The aim is to effectively enable tracking, monitoring, and analysis of products in real time with focus on residual value. The business model is implemented using an ontological model. This model is complemented by a semantic DSS. The semantic ontological model, first of its kind, is evaluated for technical compliance, quality of modelling and domain coverage, for final reengineering and re-evaluations. The DSS and the ontological model is applied in a real-world use case and demonstrate viability and applicability of the approach to businesses and sustainability via Sustainable Development Goals (SDGs) lens. The results of the comparison of this novel model to the linear economy is promising with the novel model proving more profitable and resource efficient. / Petroleum Development Technology Fund (PTDF) Nigeria

The goal of General Game Playing (GGP) is to develop a system, that is able to automatically play previously unseen games well, solely by being given the rules of the game. In contrast to traditional game playing programs, a general game player cannot be given game specific knowledge. Instead, the program has to discover this knowledge and use it for effectively playing the game well without human intervention. In this thesis, we present a such a program and general methods that solve a variety of knowledge discovery problems in GGP. Our main contributions are methods for the automatic construction of heuristic evaluation functions, the automated discovery of game structures, a system for proving properties of games, and symmetry detection and exploitation for general games.

Commercial computer gaming is a large growing industry that already has its major contributions in the entertainment industry of the world. One of the most important among different types of computer games are Real Time Strategy (RTS) based games. RTS games are considered being the major research subject for Artificial Intelligence (AI). But still the performance of AI in these games is poor by human standards due to some fundamental AI problems those require more research to be better solved for the RTS games. There also exist some AI algorithms those can help us solve these AI problems. Anytime- Algorithms (AA) are algorithms those can optimize their memory and time resources and are considered best for the RTS games. We believe that by making AI algorithms anytime we can optimize their behavior to better solve the AI problems. Although many anytime algorithms are available to solve various kinds of AI problems, but according to our research no such study is been done to compare the performances of different anytime algorithms for an AI problem in RTS games. This study will take care of that by building our own research platform specifically design for comparing performances of our selected anytime algorithms for an AI problem. / Address: NaN Mob. +46 - 737 - 40 19 17

Commercial computer gaming is a large growing industry, that already has its major contributions in the entertainment industry of the world. One of the most important among different types of computer games are Real Time Strategy (RTS) based games. RTS games are considered being the major research subject for Artificial Intelligence (AI). But still the performance of AI in these games is poor by human standards because of some broad sets of problems. Some of these problems have been solved with the advent of an open real time research platform, named as ORTS. However there still exist some fundamental AI problems that require more research to be better solved for the RTS games. There also exist some AI algorithms that can help us solve these AI problems. Anytime- Algorithms (AA) are algorithms those can optimize their memory and time resources and are considered best for the RTS games. We believe that by making AI algorithms anytime we can optimize their behavior to better solve the AI problems for the RTS games. Although many anytime algorithms are available to solve various kinds of AI problems, but according to our research no such study is been done to compare the performances of different anytime algorithms for each AI problem in RTS games. This study will take care of that by building our own research platform specifically design for comparing performances of selected anytime algorithms for an AI problem

The present study is aiming to evaluate the Intelligent Personal Assistants usage motivations, addressing at the same time various privacy issues and concerns related to this emergent technology. To fulfil the purpose of the study I have applied two different research methods. Initially, a web survey conducted gathered 18 respondents answering 24 questions related to the presented topic. Subsequently, was organised a focus group by gathering seven respondents who shared their opinions on the subject of research. Two research questions were developed based on two hypotheses. First research question: “To what extent IPA users agree to personal data collection in order to gratify their sought needs?”; exploring the participants’ opinions when it comes to the degree of acceptance of personal information disclosure to gratify their needs. Moreover, second research question: “What are the motivating criteria that determine the usage of IPA?”. This question develops opinions and experiences on the usage of Intelligent Personal Assistants, as well as the way people perceive this new technology. The finding of this studies reveals that users of new media are concerned and aware of their personal data collection. However, as a result, they feel trapped in the network society by the peer pressure towards the usage of favourite mediums. Therefore, the denial of technology would bring unfavourable consequences from a social perspective. Further researches can be conducted on this topic, addressing in depth the Artificial Intelligence and its societal implications, possible utilities of the Intelligent Personal Assistants as a companion for children, elders and people with disabilities, Artificial Intelligence used in public administration. Consequently, many different aspects can be explored having the topic of this thesis as a starting point.

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Digital transformation is evolving, and it is driving at the helm of the digital evolution. The amount of information accessible to us has revolutionized the way we gather information. Mobile technology and the immediate and ubiquitous access to information has changed how we engage with services including healthcare. Digital technology and digital transformation have afforded people the ability to self-manage in different ways than face-to-face and paper-based methods through different technologies. This study focuses on exploring the use of the most commonly used digital health technologies in the healthcare sector and how it affects physicians’ daily routine practice. The study presents findings from a qualitative methodology involving semi-structured, personal interviews with physicians from Sweden and a physician from Spain. The interviews capture what physicians feel towards digital transformation, digital health technologies and how it affects their work. In a field where a lack of information regarding how physicians work is affected by digital health technologies, this study reveals a general aspect of how reality looks for physicians. A new way of conducting medicine and the changed role of the physician is presented along with the societal implications for physicians and the healthcare sector. The findings demonstrate that physicians’ role, work and the digital transformation in healthcare on a societal level are important in shaping the future for the healthcare industry and the role of the physician in this future. / Den digitala transformationen växer och den drivs vid rodret för den digitala utvecklingen. Mängden information som är tillgänglig för oss har revolutionerat hur vi samlar in information. Mobila tekniker och den omedelbara och allmänt förekommande tillgången till information har förändrat hur vi tillhandahåller oss tjänster inklusive inom vården. Digital teknik och digital transformation har gett människor möjlighet att kontrollera sig själv och sin egen hälsa på olika sätt än ansikte mot ansikte och pappersbaserade metoder genom olika tekniker. Denna studie fokuserar på att utforska användningen av de vanligaste digitala hälsoteknologierna inom hälso- och sjukvårdssektorn och hur det påverkar läkarnas dagliga rutin. Studien presenterar resultat från en kvalitativ metod som involverar semistrukturerade, personliga intervjuer med läkare från Sverige och en läkare från Spanien. Intervjuerna fångar vad läkare tycker om digital transformation, digital hälsoteknik och hur det påverkar deras arbete. I ett fält där brist på information om hur läkare arbetar påverkas av digital hälsoteknik avslöjar denna studie en allmän aspekt av hur verkligheten ser ut för läkare. Ett nytt sätt att bedriva medicin och läkarens förändrade roll presenteras tillsammans med de samhälleliga konsekvenserna för läkare och vårdsektorn. Resultaten visar att läkarnas roll, arbete och den digitala transformationen inom hälso- och sjukvården på samhällsnivå är viktiga för att utforma framtiden för vårdindustrin och läkarens roll i framtiden.

The goal of General Game Playing (GGP) is to develop a system, that is able to automatically play previously unseen games well, solely by being given the rules of the game. In contrast to traditional game playing programs, a general game player cannot be given game specific knowledge. Instead, the program has to discover this knowledge and use it for effectively playing the game well without human intervention. In this thesis, we present a such a program and general methods that solve a variety of knowledge discovery problems in GGP. Our main contributions are methods for the automatic construction of heuristic evaluation functions, the automated discovery of game structures, a system for proving properties of games, and symmetry detection and exploitation for general games.:1. Introduction 2. Preliminaries 3. Components of Fluxplayer 4. Game Tree Search 5. Generating State Evaluation Functions 6. Distance Estimates for Fluents and States 7. Proving Properties of Games 8. Symmetry Detection 9. Related Work 10. Discussion