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Följande uppsats analyserar det straffrättsliga ansvaret vid olyckor orsakade av självkörande fordon. Dessa självkörande fordon styrs av avancerade artifi-ciella algoritmer som fattar autonoma beslut, vilket utmanar straffrättens grundläggande krav och principer. Bland annat blir maximet ”nulla poena sine culpa” (inget straff utan skuld) lidande när beslutsprocessen i gärningsögon-blicket saknar tThe following thesis analyzes criminal liability in accidents caused by self-driving vehicles. These autonomous vehicles are governed by advanced artifi-cial algorithms that make autonomous decisions, which challenges the funda-mental requirements and principles of criminal law. Among other things, the maxim "nulla poena sine culpa" (no punishment without guilt) suffers when the decision

This thesis project challenges the current municipality plans for Trollhättan 4, 6 and 7 in Malmö and suggests an alternative vision for the place. Instead of working with high-density offices, residential buildings and retail, the project aims to work with a program such as spa and a bath with a distinct public character.

This essay portrays the VINN-program, a motivational program for female prisoners in Sweden with the purpose to increase their ability to make choices with the aim of creating a better life-quality for them. The underlying ideological intent of the VINN- program is examined through discourse-analysis. The focus in the analysis is on how normalization and disciplination are used to shape a certain

A traineeship abroad provides experience that gives your degree a unique profile. If you are a student at Lund University and you wish to do a traineeship in Europe, you might be eligible to apply for an Erasmus+ traineeship grant. Shortcuts to page content:About the grantFinding a traineeshipHow to applyIf you are awarded a traineeship grantAfter your traineeship Next application period: The appl

https://www.lunduniversity.lu.se/current-students/international-opportunities/grants-and-scholarships-studies-and-traineeships-abroad/erasmus-grants/erasmus-traineeship-grant - 2026-06-15

Swedish National Center for applied AI Funded by Vinnova, AI Sweden aims to accelerate the adoption of AI across all Swedish sectors. To fulfill their mission, the centre runs multiple programs ranging from helping professionals build their AI skills to funding projects on new uses for Artificial Intelligence in Sweden. Due to the high potential associated with widespread adoption of Artificial In

https://www.ai.lu.se/about/partner/ai-sweden - 2026-06-15

Due to the increasingly concerning threat of climate change, organizations, including industrial companies, are pressured by various stakeholders to consider their impact on the environment, economy and society. The Industry 4.0 (I4.0) revolution enables companies to use new technologies such as Artificial Intelligence (AI) to address the challenge of making a positive impact on sustainability. Ho

Restyling Factual TV is about understanding genres in relation to each other and in relation to popular audiences. It takes as a starting point the idea that factual television is being restyled, that various kinds of news, current affairs, documentary and popular factual genres are part of a turbulent time in broadcasting. The boundaries between fact and fiction have been pushed to the limits in

Large language models (LLMs) like GPT-4 have the potential to dramatically change the landscape of influence operations. They can generate persuasive, tailored content at scale, making campaigns using falsified content, such as disinformation and fake accounts, easier to produce. Advances in self-hosted open-source models have meant that adversaries can evade content moderation and security checks

This thesis explored the application of pre-trained transformer models in detecting suicidal ideation in social media posts. We leveraged social media data from platforms like Reddit and Twitter and applied a robust hyperparameter random search strategy to fine-tune and evaluate existing transformer models. Despite noise in the fine-tuning data, the models demonstrated high performance in identify