Legitimacy is about meeting society's expectations and as we live in a society that is constantly changing, the perception of what is legitimate or not is also changing. The main purpose of an auditor in today's society is to review financial reports and guarantee their quality. In recent years, technological developments have changed the profession of auditors and previous research shows that digitalization has made it easier for the auditors as certain parts of the audit process have been automated. The purpose of the study was to examine how AI in audit firms will affect the legitimacy of auditors. The focus has been on the audit companies' working process and how the process is going to change with the help of AI, and finally how the auditors believe this will affect the legitimacy of the audit companies. Qualitative interviews have been used on auditors, to be able to get into the depth and obtain personal thoughts from the respondents. The results of the study show that the introduction of AI will have a positive impact on the audit process since it is assumed that standardized and time-consuming tasks will be automated. Furthermore, this means that auditors will be able to perform more accurate analyzes and get more time over to the customers, which means that the audit companies are assumed to be able to increase their legitimacy. Therefore, the conclusion is that AI will help audit companies with their legitimacy in the future.

Forskare och teknologer talar om artificiell intelligens som en revolution lika omvälvande som industrialismen och investerare har skyhöga förväntningar. Detta medan det hos allmänheten finns både okunskap om och rädsla inför AI, även om AI redan i dag tillämpas inom områden som sjukvård och industri. Många tillämpningar innebär att människans livsmiljö behöver anpassas för att AI ska fungera. När ny teknologi växer fram saknar vi ofta uttryck att tala om den och AI är dessutom till stor del osynlig för blotta ögat. Allmänheten blir därför i stor utsträckning beroende av mediernas skildringar. Det ger medierna makt eftersom de får kontroll över de budskap som sprids om AI, vilket gör att de kan påverka våra tankar, känslor och handlingar. Syftet med studien har varit att utforska hur AI har konstruerats i medierna i en tid när varken AI eller diskurserna om AI har hittat sin slutgiltiga form, det vill säga låsts in. Vad säger vi egentligen om AI i form av diskurser, ramar och metaforer? Empirin består av 90 nyhetsartiklar om AI publicerade av TT Nyhetsbyrån från 1980-talet till mars 2020. TT Nyhetsbyrån har en unik plats som nyhetsförmedlare då de når ut till hela Sveriges befolkning och åtnjuter stort förtroende hos allmänheten. Studiens teoretiska ramverk består av tre teorier i samspel: diskursanalys, framingteori och metaforteori. Diskursanalys ser språket som en social handling, vilket innebär att diskurser om AI kan leda oss i en viss riktning. Framingteori studerar hur olika sätt att rama in ett ämne som AI styr hur vi uppfattar och tolkar det. Metaforer ses i studien som centrala tankestrukturer som påverkar hur vi uppfattar, känner och handlar kring AI. Metodval är kvalitativ analys utifrån den undersökningsmodell som konstruerades med det teoretiska ramverket som grund. Resultaten visar att inramningen av TT Nyhetsbyråns artiklar är övervägande positiv, där AI i majoriteten av artiklarna presenteras som ett verktyg med stora möjligheter, som bör utvecklas och tillämpas. Metaforer som förekommer tillskriver maskinen mänskliga egenskaper och motiv och framställer AI-tillämpningar som smarta, läskunniga, nyfikna med flera mänskliga förmågor. Det impliceras i flera artiklar att maskinen skulle ha ett intresse av att konkurrera med människan. En central slutsats är att det förekommer ett spänningsfält med två motsatta huvuddiskurser i empirin. Den ena beskriver AI som ett neutralt verktyg, den andra som en konkurrent till människan. Båda leder till bilden av AI som ett verktyg med stor potential. AI-intressenterna gynnas av spänningsfältet medan läsare missgynnas: de lämnas att själva dra slutsatser om AI:s egentliga fördelar och nackdelar. Andra slutsatser är att de metaforer som förekommer tillskriver AI mänskliga egenskaper och motiv, vilket skapar stora förväntningar. Metaforerna döljer att AI kan förekomma i andra former än som en människoliknande robot, former som inskränker människans livsutrymme. Inramningen har varierat något över tid och tecken finns på att diskurser har låsts in. I empirin finns en klar övervikt för vita män ur elitklassen, vilket gör att TT Nyhetsbyrån kan sägas reproducera existerande maktstrukturer. / According to scientists and technologists, Artificial Intelligence is as revolutionary as the Industrialisation, and investors have soaring expectations. At the same time there is ignorance and fear of AI among the public, even though AI is already being applied in areas such as healthcare and industry. Many applications mean that human life must be adapted to make AI work. As new technologies emerge, we often lack expressions to talk about them, and AI is also largely invisible to the naked eye. The public, therefore, is largely dependent on depictions in media. Newspapers and radio channels decide what messages are spread about AI, messages which influence our thoughts, feelings and actions. The aim of this study was to explore how AI has been constructed in the media at a time when neither AI nor the discourses of AI have found their final form. What do we really say about AI? This study investigates 90 news articles about AI published by TT Nyhetsbyrån from the 1980s to March 2020. TT Nyhetsbyrån has the ability to reach the entire population of Sweden and enjoy great public confidence. The study’s theoretical framework consists of three theories in interaction: discourse analysis, framing theory and metaphor theory. Discourse analysis sees language as a social act, which means that discourses about AI can influence our behaviour. Framing theory studies how different ways of framing a topic such as AI can determine how we perceive and interpret it. In this study, metaphors are defined as central thought structures that influence how we perceive, feel and act. A qualitative analysis was applied in the study, based on a model that was constructed using the theoretical framework. TT Nyhetsbyrån’s articles are found to be predominantly positive, where AI in the majority of articles is framed as a tool with great opportunities, that should be developed and applied. Metaphors ascribe human attributes and motives to the machine, such as smart, literate and curious. It is implied in several articles that the machine has an interest in competing with man. In TT Nyhetsbyrån’s articles two opposite main discourses are visible, creating a tension between the two. One describes AI as a neutral tool, the other as a competitor to humans. Both lead to the image of AI as a tool with great potential. AI stakeholders are favoured by this tension between discourses, while the public is disfavoured: the readers of TT Nyhetsbyrån’s articles are left to draw conclusions about the true advantages and disadvantages of AI. The metaphors in the articles attribute human traits and motives to AI, which creates high expectations. The metaphors hide that AI can exist in forms other than a human-like robot, forms that restrict human life. The framing has varied somewhat over time and there are signs that discourses have been locked in. Since a majority of the interviewees in the articles are white men of the elite class, TT Nyhetsbyrån can also be said to reproduce existing power structures.

Background  AI adoption is increasing, and the highest increase of AI is seen in service functions, followed by product applications. Moreover, the patent filing is rapidly increasing showing high interest in the technology. Product-based firms developing AI technology may need to develop their business model as a result of the introduction of AI. Research aim This thesis aims to explore how product-oriented companies innovate the business model based on AI development. More specifically, how these technological opportunities can, create value, deliver value, and capture value as a result.    Method This thesis follows a qualitative strategy, mainly being explorative. The thesis follows a single case study approach of Axis Communications. Data collection was mainly conducted with semi-structured interviews. Findings The value creation of AI development is described based on functions and the value-added. The value delivery explores key capabilities of the data pipeline, algorithm development and partners. The value capture described the sales model and compares AI-related solutions with competitors. Conclusions The study concludes that AI-based solutions can be an attributing factor for a product-based company to innovate the business model towards a more service and partner-oriented business model. Keywords: Artificial intelligence, Internet of things, Digital servitization, Business model innovation, Business ecosystem

We present a theoretical study that investigates the applicability of a graph theoretical approach to realize various quantum experiments. Crucially, we may represent quantum optical experiments involving tabletop optical elements in terms of highly interpretable, coloured, weighted multi-graphs. We introduce the formalism behind this approach; then through the digital discovery framework PyTheus, we uncover over 100 different quantum experiments which realizes complex, novel quantum states. Towards enhancing our interpretation of the AI-based framework's solutions, we also leverage eXplainable-AI (XAI) techniques from computer vision to investigate what a trained neural network learns about quantum experiments. Crucially, we find that we are able to conceptualize the learned strategies which the neural network applies to optimize for a target quantum property, and discover how the network conceives of its solution. We conclude by presenting an experimental proposal which yields realizable solutions that, for the first time, solves high-dimensional variants of a quantum retrodiction puzzle known as the Mean King's Problem. We, therefore, present a case study which investigates the potential for new scientific discoveries through a joint collaboration between human and artificial intelligence.

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We live in a world that is constantly evolving and changing due to technological advances. With tools that utilize generative artificial intelligence, creation has never been more accessible to everyone, regardless of previous experience. Combined with a new variety of user platforms and streaming services, a whole new landscape content exchange is shaping. But how does this affect the industry and, above all, people who make a living from creating moving images? This study focuses on figuring out different creators' general attitude regarding implementing tools based on GenAI and how this would change their creative process. We also explore the consequences that widespread use can lead to. From the creator’s perspective, threats and opportunities are identified because of technological development, as well as how ethical aspects are affected. By utilizing a qualitative approach, the study conducts in-depth interviews with industry professionals to capture their perceptions and experiences with GenAI. The findings reveal a cautious optimism among participants, acknowledging GenAI’s potential to streamline production processes while also recognizing the necessity for careful management regarding regulations. Finally, the research contributes to a better understanding of how GenAI is reshaping video production and suggests pathways for its responsible integration into the industry.

This thesis investigates the impact of generative AI technologies on deliberative democracy in Latin America, focusing on the cases of Peru and Brazil. Through qualitative interviews with experts from both countries, this research uses several techniques to process the data collected and intends to draw conclusions from it. The study found that unregulated generative AI is a source of concern for Peruvian and Brazilian participants. Another key finding was that these two countries are not keen on collaborating with other countries in the region to establish a regulatory framework on generative AI. Through the analysis of the five principles of deliberative democracy: citizen participation, inclusivity, accessibility, accountability, and quality of deliberation, this project was able to draw conclusions on which of these dimensions could be impacted by generative AI. The results of the study show that in the case of  Peru, generative AI technologies impact citizen participation and accountability the most.  In the case of Brazil generative AI technologies impact citizen participation, inclusivity, and transparency the most. The most important finding, however, is the commonality shared by Peru and Brazil which signifies that in both countries citizen participation will be impacted by generative AI. The question of how citizen participation will be impacted requires a deeper analysis of the responses of the interviewees as they have both positive and negative perspectives on the issue.

Main reason of this study is to set forth the internal paradox of the basic approach of the artificial intelligence in the medical field to by discussing on the theoretical and application levels and to suggest solutions in theory and practice against that. In order to rule out the internal paradox in the medical decision support systematic, a new medical model is suggested and based on this, concepts such as disease, health, etiology, diagnosis and treatment are questioned. Meanwhile, with the current scientific data, a simple application sample based on how a decision making system which was set up by fuzzy logic and which is based on the perception of human as a complex adaptive system has been explained. Finally, results of the research about accuracy and validity of this application, current improvements based on the current model and the location on the artificial intelligence theory is discussed.

Ce mémoire eut pour ambition première d’aborder les enjeux éthiques de la robotique sexuelle selon une perspective critique féministe. Nous avons défendu la thèse selon laquelle les robotes sexuelles telles que développées à ce jour constituaient le continuum de la domination masculine en contexte sexuel. Il s’agissait alors dans un premier temps de distinguer les fondements sur lesquels la robotique sexuelle prenait forme, à savoir une structure de pouvoir inégalitaire, l’utilisation de normes dominantes et des schémas relationnels oppressifs. Dans un deuxième temps, il s’agissait de mettre en lumière les implications symboliques, c’est-à-dire au niveau de la représentation du groupe des femmes et matérielles, autrement dit en ce qui concerne le renforcement des inégalités de statuts, nous amenant alors à déterminer les caractéristiques propres à la robotique sexuelle, en d’autres termes, la réitération de paradigmes de domination sous une forme novatrice, soit celle d’un.e robot.e intelligent.e. / The primary aim of this paper was to address the ethical issues of sexual robotics from a feminist critical perspective. We argued that sexual robotes as developed to date constituted the continuum of male domination in a sexual context. The first step was to distinguish the foundations on which sexual robotics was taking shape, namely an unequal power structure, the use of dominant norms and oppressive relational patterns. The second step was to highlight the symbolic implications, that is to say the representation of women’s group and material effects, in other words, the reinforcement of inequalities of status. This led us to determine the characteristics of sexual robotics, otherwise stated, the repetition of domination paradigms in an innovative form, that of an intelligent robot.

University/College selection is a daunting task for young adults and their parents alike. This research presents True-Ed Select, a machine learning framework that simplifies the college selection process. The framework uses a four-layered approach including the user survey, machine learning, consolidation, and recommendation. The first layer collects both the objective and subjective attributes from users that best characterize their ideal college experience. The second layer employs machine learning techniques to analyze the objective and subjective attributes. The third layer combines the results from the machine learning techniques. The fourth layer inputs the consolidated result and presents a user-friendly list of top educational institutions that best match the user’s interests. We use our framework to analyze over 3500 United States post-secondary institutions and show search space reduction to top 20 institutions. This drastically reduced search space facilitates effective and assured college selection for end users. Our survey results with 10 participants highlight an average satisfaction rating of 4.11, showing the efficacy of the framework.