In 2020, the year the Covid-19 pandemic struck, the Swedish Covid-19 response differed radically from the general policy of total lockdown and strict enforcement of Covid-measures and regulations recommended by the WHO. Instead, Sweden strove early on to achieve herd immunity, with no mandatory measures to limit numbers in shopping malls, buses, and other public events, nor mask requirements. Hence, during the height of the pandemic, Swedish Covid-19 policy was a highly debated issue in the international media, within academia and the World Health Organization. The aim of this study is to examine the international media discourse on the Swedish Covid-19 strategy in the international print media. The focus has been on newspapers from the Netherlands, the United Kingdom, and the United States. The research has been done by investigating how Sweden’s Covid-19 strategy is discursively constructed, through major themes and sub-themes that have emerged. Additionally, the differences in discourse between Dutch, English and American media have been explored. As well as the use of language, ideologies, and linguistic devices within the international discourse have been investigated. A total of 178 articles, published between the period of 1 January 2020 until 6 February 2022, have been collected and analyzed. This study uses Qualitative Content Analysis (QCA) as main method and has been inspired by Critical Discourse Analysis (CDA). A coding frame has inductively been created, by having used a sample of 20 newspaper articles in a pilot study. The software of NVivo has been used for the coding process. The major themes that emerged from my analyses of media discourses are: Anders Tegnell, Strategy, Trust and Image of Sweden and Swedes. My study found that media discourses on the Swedish Covid-19 policy are not positive. Rather these tend to be negative or at best neutral. Images of Sweden tend to vary in tandem with increase or decreases of Covid-19 infections and/or deaths. As the Swedish strategy became more or less aligned with the ‘norm’ of the WHO, the coverage of Sweden in media declined and lost its newsworthiness.

<p dir="ltr">Evidence for climate change-related impacts and risks is already widespread globally, affecting not only the ecosystems but also the economy and health of our communities. Data-driven predictive modeling approaches such as machine learning and deep learning have emerged to be powerful tools for interpreting large and complex non-linear datasets such as meteorological variables from weather stations or the distribution of infectious droplets produced in a cough. However, the strength of these data-driven models can be further optimized by complementing them with foundational knowledge of the physical processes they represent. By understanding the core physics, one can enhance the reliability and accuracy of predictive outcomes. The effectiveness of these combined approaches becomes particularly feasible and robust with the recent advancements in the High-Performance Computing field. With improved processing speed, algorithm design, and storage capabilities, modern computers allow for a deeper and more precise examination of the data. Such advancements equip us to address the diverse challenges presented by climate change more effectively.</p><p dir="ltr">In particular, this document advances research in mitigating and preventing the consequences of global warming by implementing data-driven predictive models based on statistical, machine learning, and deep learning methods via two phases. In the first phase, this dissertation proposes frameworks consisting of machine and deep learning algorithms to increase the resilience of small-scale renewable energy systems, which are essential for reducing greenhouse gas emissions in the ecosystems. The second phase focuses on using data from physics-based models, i.e., computational fluid dynamics (CFD), in data-driven predictive models for improving the design of air cleaning technologies, which are crucial to reducing the transmission of infectious diseases in indoor environments. </p><p dir="ltr">Specifically, this work is an article-based collection of published (or will be published) research articles. The articles are reformatted to fit the thesis's structure. The contents of the original articles are self-contained. </p>

Derek Parfit är kanske en av vår tids mest kända moralfilosofer. Parfit inleder sin första bok Reasons and Persons med att ställa frågan: vad har vi mest skäl att göra? Hans fråga berör vad som egentligen har betydelse, en fråga som han fortsätter att beröra i sin andra bok On What Matters. Filosofen Toby Ord argumenterar i sin bok The Precipice för att den utmaning som definierar vår tid, och bör ha en central prioritering, är utmaningen att skydda mänskligheten emot så kallade existentiella risker. En existentiell risk är en typ av risk som hotar att förstöra, eller förhindra, mänsklighetens långsiktiga potential. Ord menar att vi idag befinner oss vid en kritisk tidpunkt i mänsklighetens historia som kan vara helt avgörande för om det ens kommer existera en framtid för mänskligheten. Men om vi bör skydda mänskligheten emot existentiella risker, så kan en lämplig följdfråga vara i vilken ordning vi bör prioritera olika existentiella risker. Den svenske filosofen Nick Bostrom har liksom Ord länge förespråkat att existentiella risker bör tas på allvar. Han menar att preventiva åtgärder bör vidtas. I sin bok Superintelligens argumenterar Bostrom, både omfattande och väl, för att den existentiella risk som kan te sig som mest brådskande, och kanske allvarligast, är artificiell intelligens. Bostrom menar att vi har goda skäl att tro att utveckling av artificiell intelligens kan eskalera till den grad att mänsklighetens öde kan hamna bortom vår egen kontroll. Det han syftar på är att människan just nu är den dominerande agenten på jorden och därför innehar en stor kontroll, men att så inte alltid behöver vara fallet. Bostroms tes kunde te sig som okonventionell då den presenterades, men kan även te sig så idag vid en första anblick. Han har dock fått explicit medhåll av personer som Bill Gates, Stephen Hawking, Elon Musk, Yuval Noah Harari och Max Tegmark, som antingen håller med eller resonerar i liknande banor. Även jag själv finner Bostroms antaganden välgrundade. Slutsatsen som många drar är därför att vi bör betrakta artificiell intelligens som en existentiell risk som ska prioriteras högt. Jag kommer dock i denna text att argumentera för tesen att vi inte bör betrakta artificiell intelligens som en existentiell risk. Tesen följer från en invändning som jag kommer att kalla för AI-paradoxen. Det tycks enligt invändningen som att artificiell intelligens inte kan leda till en existentiell katastrof givet vissa premisser som flera i debatten om artificiell intelligens tycks acceptera. Texten i uppsatsen är strukturerad på följande sätt. I avsnitt 2 kommer jag att återge det övergripande argumentet som cirkulerar i debatten om artificiell intelligens som ett hot. I avsnittet kommer jag också förklara några viktiga termer och begrepp. I avsnitt 3 börjar jag med att titta på den första premissen i argumentet, samt resonera om dess rimlighet. I avsnitt 4 går jag sedan vidare till den andra premissen i argumentet och gör samma sak med den. Väl i avsnitt 5 så väljer jag att presentera min egen idé som jag kallar för AI-paradoxen, vilket är en invändning mot argumentet. I avsnitt 6 diskuterar jag sedan AI-paradoxens implikationer. Avslutningsvis, i avsnitt 7, så ger jag en övergripande sammanfattning och en slutsats, samt några sista reflektioner. / Derek Parfit is perhaps one of the most famous moral philosophers of our time. Parfit begins his first book Reasons and Persons by asking the question: what do we have most reason to do? His question touches upon what really matters, a question he continues to touch upon in his second book On What Matters. The philosopher Toby Ord argues in his book The Precipice that the challenge that defines our time, and should have a central priority, is the challenge of safeguarding humanity from so-called existential risks. An existential risk is a type of risk that threatens to destroy, or prevent, humanity’s longterm potential. Ord means that today we are at a critical time in the history of humanity that can be absolutely decisive for whether there will even exist a future for humanity. But if we are to safeguard humanity from existential risks, then an appropriate question may be in what order we should prioritize different existential risks. The Swedish philosopher Nick Bostrom, like Ord, has long advocated that existential risks should be taken seriously. He believes that preventive measures should be taken. In his book Superintelligence Bostrom argues, both extensively and well, that the existential risk that may seem most urgent, and perhaps most severe, is artificial intelligence. Bostrom believes that we have good reason to believe that the development of artificial intelligence can escalate to the point that the fate of humanity can end up beyond our own control. What he is referring to is that humans are currently the dominant agent on earth and therefore has great control, but that this does not always have to be the case. Bostrom's thesis may have seemed unconventional when it was presented, but it can also seem so today at first glance. However, he has been explicitly supported by people like Bill Gates, Stephen Hawking, Elon Musk, Yuval Noah Harari and Max Tegmark, who either agree or reason similarly. I myself also find Bostrom's assumptions well-founded. The conclusion that many draw is therefore that we should regard artificial intelligence as an existential risk that should be given a high priority. However, in this text I will argue for the thesis that we should not regard artificial intelligence as an existential risk. The thesis follows from an objection of my own, which I call the AI ​​paradox. According to the objection, it seems that artificial intelligence cannot lead to an existential catastrophe given certain premises that many in the debate about artificial intelligence as a threat seem to accept. The text in the essay is structured as follows. In section 2 I will present the main argument circulating in the debate about artificial intelligence as a threat. In the section I will also explain some important terms and concepts. In section 3 I begin by looking at the first premise in the argument, and also reason about its plausibility. In section 4 I proceed to the second premise in the argument and examine it similarly. Once in section 5 I choose to present my own idea, which I call the AI ​​paradox, which is an objection to the argument. In section 6 I discuss the implications of the AI ​​paradox. Finally, in section 7, I give an overall summary and a conclusion, as well as some last reflections.