Recent technological breakthroughs in natural language processing and artificial intelligence (AI) and the subsequent release of OpenAIs generative AI system, ChatGPT, have warranted much attention from researchers and the general public alike. Some with praise, foreseeing a brighter future for all, and some predicting the end of humanity. As AI agents become increasingly complex and gain the ability to deal with tradeoffs and become more autonomous, the problem of embedding human values into these AI agents becomes more pressing. Embedding human values is a crucial part of the development of aligned AI systems that act in accordance with human intents and desires. The black-box nature of large language models (LLMs) offers little insight into the mechanics of the AI agents' decision-making processes. For this reason, it is of great interest to explore what values an LLM might hold. This explorative study lets the most popular LLM chatbot today, ChatGPT answer a set of questions focusing on human values. The questions were adopted from the World Value Survey (WVS) and relate to current global values around different subjects, such as same-sex marriage, corruption and raising children. The results were compared to the latest data set (from 2022) from the WVS to show how close or far the values of ChatGPT are to the respondents' values across countries. The findings contribute to the broader understanding of the challenges and implications of developing AI systems that align with human values. Which is crucial in ensuring the systems trustworthiness and beneficial impact on society. The findings of this explorative study support that ChatGPT's values are influenced by the values prevalent in developed democracies, with a leaning towards progressive/liberal views. Results could also imply that ChatGPT may propose a neutral attitude towards questioning established systems and institutions, and emphasizing individual rights. / Nya tekniska genombrott inom naturlig språkbehandling och artificiell intelligens (AI) samt OpenAIs generativa AI-system, ChatGPT, har genererat mycket uppmärksamhet från både forskare inom fältet och från allmänheten. Vissa spår en ljusare framtid, medan andra siar om slutet för mänskligheten. Allteftersom “AI-agenter” blir mer komplexa utvecklar förmågan att göra avvägningar, och blir mer autonoma, blir problemet med att integrera mänskliga värden i dessa AI-agenter mer angeläget. Att integrera mänskliga värderingar är en avgörande del i utvecklingen av AI-system som agerar i enlighet med mänskliga avsikter och vilja. Vi saknar insyn i mekaniken för beslutsprocesser hos stora språkmodeller (eng: large language models, LLMs) och av denna anledning är det av stort intresse att utforska vilka värderingar en språkmodell uttrycker. Denna utforskande studie låter den, för närvarande, mest populära LLM-chatboten, ChatGPT, svara på en uppsättning av frågor som fokuserar på mänskliga värderingar. Frågorna har hämtats från World Value Survey (WVS) och relaterar till aktuella globala värderingar kring olika ämnen, såsom samkönade äktenskap, korruption och barnuppfostran. Resultaten jämfördes med den senaste datan (från 2022) från WVS för att visa hur nära eller långt värdena för ChatGPT ligger respondenterna från olika länders. Resultaten från denna studie bidrar till en bredare förståelse för utmaningarna och konsekvenserna av att utveckla AI-system som är i linje med mänskliga värderinga. Detta är en viktig aspekt för att kunna säkerställa systemens pålitlighet och positiva inverkan på samhället. Resultaten av denna explorativa studie stödjer att ChatGPT:s värderingar influeras av de värderingar som råder i utvecklade demokratier, med en tendens mot progressiva/liberala åsikter. Resultaten kan också antyda att ChatGPT kan ställa sig neutralt till ifrågasättandet av etablerade system och institutioner, samt betonar individuella rättigheter.

ChatGPT has made large language models more accessible and made it possible to code using natural language prompts. This study conducted an experiment comparing prompt engineering techniques called task specification and investigated their impacton code generation in terms of correctness and variety. The hypotheses of this study focused on whether the baseline method had a statistically significant difference in code correctness compared to the other methods. Code is evaluated using a software requirement specification that measures functional and syntactical correctness. Additionally, code variance is measured to identify patterns in code generation. The results show that there is a statistically significant difference in some code correctness criteria between the baseline and the other task specification methods, and the code variance measurements indicate a variety in the generated solutions. Future work could include using another large language model; different programming tasks andprogramming languages; and other prompt engineering techniques.

The launch of the chatbot ChatGPT in November of 2022 has sparked a fierce debate on how AI tools will affect future education. Currently, there have been multiple articles about how universities and educators do not yet have an action plan on how to respond to the consequences of the launch of the chatbot. The technology behind ChatGPT is generative AI and is anticipated to be the next big digital disruption. Generative AI and its effects on higher education is still unexplored territory. In this thesis we aim to answer the following research question: how can generative AI be managed as a digital disruption in higher education? We conducted a qualitative case study at a university in Sweden, where the participants were educators from different departments. The three main themes discussed in this thesis are: disruptive effects of generative AI; three elements of managing digital disruption; emerging challenges and opportunities. We contribute to existing research by providing a model on how the digital disruption caused by generative AI manifests in higher education and provide suggestions on how to manage it. Further, we suggest that future research add students’ perspective to the model, since this was not covered in this thesis.

Background: As the demand for cybersecurity professionals continues to rise, it is crucial to identify the key skills necessary to thrive in this field. This research project sheds light on the cybersecurity skills landscape by analyzing the recommendations provided by the European Cybersecurity Skills Framework (ECSF), examining the most required skills in the Swedish job market, and investigating the common skills identified through the findings. The project utilizes the large language model, ChatGPT, to classify common cybersecurity skills and evaluate its accuracy compared to human classification. Objective: The primary objective of this research is to examine the alignment between the European Cybersecurity Skills Framework (ECSF) and the specific skill demands of the Swedish cybersecurity job market. This study aims to identify common skills and evaluate the effectiveness of a Language Model (ChatGPT) in categorizing jobs based on ECSF profiles. Additionally, it seeks to provide valuable insights for educational institutions and policymakers aiming to enhance workforce development in the cybersecurity sector. Methods: The research begins with a review of the European Cybersecurity Skills Framework (ECSF) to understand its recommendations and methodology for defining cybersecurity skills as well as delineating the cybersecurity profiles along with their corresponding key cybersecurity skills as outlined by ECSF. Subsequently, a Python-based web crawler, implemented to gather data on cybersecurity job announcements from the Swedish Employment Agency's website. This data is analyzed to identify the most frequently required cybersecurity skills sought by employers in Sweden. The Language Model (ChatGPT) is utilized to classify these positions according to ECSF profiles. Concurrently, two human agents manually categorize jobs to serve as a benchmark for evaluating the accuracy of the Language Model. This allows for a comprehensive assessment of its performance. Results: The study thoroughly reviews and cites the recommended skills outlined by the ECSF, offering a comprehensive European perspective on key cybersecurity skills (Tables 4 and 5). Additionally, it identifies the most in-demand skills in the Swedish job market, as illustrated in Figure 6. The research reveals the matching between ECSF-prescribed skills in different profiles and those sought after in the Swedish cybersecurity market. The skills of the profiles 'Cybersecurity Implementer' and 'Cybersecurity Architect' emerge as particularly critical, representing over 58% of the market demand. This research further highlights shared skills across various profiles (Table 7). Conclusion: This study highlights the matching between the European Cybersecurity Skills Framework (ECSF) recommendations and the evolving demands of the Swedish cybersecurity job market. Through a review of ECSF-prescribed skills and a thorough examination of the Swedish job landscape, this research identifies crucial areas of alignment. Significantly, the skills associated with 'Cybersecurity Implementer' and 'Cybersecurity Architect' profiles emerge as central, collectively constituting over 58% of market demand. This emphasizes the urgent need for educational programs to adapt and harmonize with industry requisites. Moreover, the study advances our understanding of the Language Model's effectiveness in job categorization. The findings hold significant implications for workforce development strategies and educational policies within the cybersecurity domain, underscoring the pivotal role of informed skills development in meeting the evolving needs of the cybersecurity workforce.

This thesis investigates the applications and implications of Generative Pretrained Transformer (GPT) technology in international entrepreneurship. The research questions focus on how GPT can serve as a strategic tool, communication tool, and knowledge leverage tool, and how these applications influence decision-making, enhance performance, The findings from the analysis chapters highlights that GPT significantly contributes to strategic planning, market analysis, and operational management, thereby enhancing decision-making and performance. GPT technology, acting as a potent communication tool, nurtures more robust client relationships and eases cross-cultural interactions, courtesy of its superior language processing capabilities. The thesis discusses how these capabilities of GPT can lead to reduced miscommunications and enhanced client satisfaction. This, in turn, contributes to cost savings by retaining existing customers and attracting new ones, thereby enhancing profits. Moreover, The main theoretical implications that this  thesis has resulted in will showcase the time efficiency brought by automated, high-quality communication that reduces man-hours spent on routine interactions, freeing resources for strategic tasks for international entrepreneurship.  Furthermore, this study enriches the literature on generative AI exemplified by models like GPT in the world of international business, particularly within the context of international entrepreneurship. It offers essential insights that can guide international entrepreneurs in understanding the potential advantages of integrating GPT technology into their business operations.

Denna studie presenterar en undersökning om användningen av ChatGPT inom programvaruutveckling. Med den snabba tillväxten av artificiell intelligens (AI) och dess inverkan på teknikområdet, har verktyg som ChatGPT blivit alltmer relevanta inom mjukvaruutveckling. Studiens huvudsyfte är att undersöka hur ChatGPT kan fungera som ett verktyg i programvaruutvecklingsprocessen och om det kan bidra till att underlätta utvecklingsprocessen för en utvecklare.Genom en kombination av enkätundersökningar och experiment har studien visat att ChatGPT har potential att vara ett värdefullt verktyg inom programvaruutveckling. Detta genom att erbjuda automatisk kodkomplettering och andra hjälpmedel som kan förbättra utvecklarnas effektivitet. Resultaten från denna studie indikerar att integrationen av AI-verktyg som ChatGPT i mjukvaruutvecklingsprocessen kan leda till förbättrade arbetsflöden och ökad produktivitet. Dock bör ytterligare forskning genomföras för att fullt ut förstå fler potentiella fördelar och utmaningar. För att ytterligare förstå ChatGPT:s roll inom programvaruutveckling rekommenderas det att utföra mer omfattande fältstudier där verktyget används i verkliga utvecklingsprojekt. / This study presents an investigation into the use of ChatGPT in the software development field. With the rapid growth of artificial intelligence (AI) and its impact on the technology field, tools like ChatGPT have become increasingly relevant in software development. The main aim of the study is to investigate how ChatGPT can work as a tool in the software development process and if it can help facilitate the development process for a developer.Through a combination of questionnaire survey and experiments, the study has shown that ChatGPT has the potential to be a tool of great value in software development. This by offering automatic code completion and other aids that can improve developers' efficiency. The results of this study indicate that the integration of AI tools such as ChatGPT into the software development process can lead to improved workflows and increased productivity. However, further research should be conducted to better understand potential benefits and challenges. To further understand ChatGPT's role in software development, it is recommended to conduct more extensive field studies where the tool is used in real world development projects.

ChatGPT is a newly launched Artificial Intelligence (AI) powered model with several functions, providing the user with human-like responses. Recently, ChatGPT have gain a lot of recognition and popularity. The aim of this research is to examine the perceptions of ChatGPT from a Swedish professional service workers (PSW) perspective. More precisely, the study explores how the usage of ChatGPT in regard to supporting various work tasks is perceived. Additionally, the aim is to examine what factors could influence the perceptions regarding the model, and how the information provided is viewed by PSWs. The research uses a qualitative approach, and the data is collected through semi-structured interviews. Moreover, the study uses a thematic analysis for the analysis of data gathered. Additionally, the study uses Unified Theory of Acceptance and Use of Technology (UTAUT) to explore the factors influencing PSWs perception of ChatGPT. The findings show that PSWs believed that ChatGPT could be used to support some of their work tasks. The model was seen as easy to use and had its benefits, such as perceived increased productivity and efficiency. However, the findings also indicate that there are several challenges that could influence the overall usage of ChatGPT. Overall, both performance expectancy and effort expectancy showed to be important factors of the evaluation of ChatGPT usage in this study. Moreover, the findings indicate that the functions and information provided by ChatGPT could influence the perceptions. For example, lack of references, lack of human touch, and security issues were found to influence the interviewed PSWs. Additionally, the study concludes that there are several perceived areas of improvements regarding ChatGPT. This research contributes with knowledge about ChatGPT from a PSWs perspective and how it could be used for work related tasks.

In this study, we tested the performance of ChatGPT-4 on the concept inventory Brief Electricity and Magnetism Assessment (BEMA) to understand its potential as an educational tool in physics, especially in tasks requiring visual interpretation. Our results indicate that ChatGPT-4 performs similarly to undergraduate students in introductory electromagnetism courses, with an average score close to that of the students. However, ChatGPT-4 displayed significant differences compared to students, particularly in tasks involving complex visual elements such as electrical circuits and magnetic field diagrams. While ChatGPT-4 was proficient in proposing correct physical reasoning, it struggled with accurately interpreting visual information. These findings suggest that while ChatGPT-4 can be a useful supplementary tool for students, it should not be relied upon as a primary tutor for subjects heavily dependent on visual interpretation. Instead, it could be more effective as a peer, where its outputs are critically evaluated by students. Further research should focus on improving ChatGPT’s visual processing capabilities and exploring its role in diverse educational contexts.

The use of artificial intelligence (AI), especially ChatGPT, has increased exponentially in the past years, and it can be seen how AI-based tools are being used in several fields, including education. The literature on AI on education (AIEd), how it has been used, its potential uses, opportunities and challenges were reviewed as well as the literature on sentiment analysis on social media to evaluate the best approach. Since education might face notorious changes due to this technology, assessing how people feel about this potential change in the paradigm is essential. Sentiment analysis on YouTube comments of videos related to ChatGPT, the most popular AI tool for education across learners and educators, was performed. It was found that 62.1% of thes ample had a positive feeling regarding this technology for educational purposes, whereas 19.4% had a negative sentiment and 18.5% were neutral. To contribute to the literature on sentiment analysis of YouTube comments, the two most used and best-performing algorithms were used for this task: Naive Bayes and Support Vector Machine. The results show that the first algorithm had a 61.30% accuracy, whereas SVM had a 71.79%.

Identifying the most used design patterns and communication methods for a microservices architecture holds paramount importance in ensuring system stability within the IT industry. With a plethora of approaches available, encompassing various design patterns and communication techniques, the selection of technologies often hinges upon the expertise and knowledge of software designers. However, designing microservices solely through human efforts poses significant challenges for companies. Moreover, the monitoring aspect presents its own set of complexities in the realm of microservices. This research aims to elucidate the prevalent design patterns and communication methods utilized in modern IT microservices environments. It also seeks to demonstrate the integration of Artificial Intelligence tools such as ChatGPT into the architecture design process, particularly in enhancing monitoring capabilities within microservices. Subsequently, a prototype is proposed to offer design guidance, as recommended by the ChatGPT and Llama 2 customized models in accordance with the specified requirements. Additionally, the study primarily seeks to identify prevalent design patterns and communication methods employed within the IT industry through the utilization of surveys and interviews conducted with both technical and non-technical personnel.