In order to secure a sustainable future, it is crucial that consumers adopt more resource-efficient foods, such as soy butter, cultured beef and seaweed. One obvious marketing strategy is to position sustainable alternatives as the morally-superior choice. The main selling point of cultured beef, for instance, is its contribution to the collective good. But while such moral appeals could indeed boost demand, this proposal examines the notion that there are some important, previously unconsidered, social risks associated with moral appeals. Specifically, while compliance with moral appeals could satisfy consumers? internal need to be moral, it also calls the morality of fellow consumers into question. In response, fellow consumers may attempt to restore their threatened sense of morality by discrediting or rejecting moral outliers ? a phenomenon known as ?moral do-gooder derogation?. This social-psychological perspective on morality may have some important implications for the marketing of sustainable products, which I will examine in a series of lab and field studies. Project 1 takes the perspective of the observer. It documents defensive responses by consumers who witness others buying ?morally-superior? sustainable products. Importantly, I additionally propose that prospective buyers also anticipate such defensive responses. Project 2 therefore takes the perspective of the actor. It investigates the notion that consumers may avoid purchasing ?morally-superior? sustainable products in an attempt to avoid being perceived as a moral outlier. In doing so, this proposal introduces a new angle on the adoption of sustainable products: consumers want to be moral, but not be perceived as a moral outlier.

When we use language to refer to objects in our surroundings, our choice of what to say about them emerges from a close interplay between linguistic constraints and perceptual processes. In this project, we seek to model the interaction between language production and visual attention. Attention depends on salient features, but also on our knowledge of everyday scenes. How does the outcome of this interplay between salience and scene knowledge inform the formulation of a linguistic message in a specific language? We model the interaction between perception and language to develop human-centred, cognitively plausible AI models of referential communication.

The transition to renewables poses challenges due to weather fluctuations spanning days to years. To facilitate this transition power system modeling at high resolutions need to be integrated with extensive datasets of historical and future weather data, requiring solutions in big data analytics and advanced optimization algorithms. The Algorithmic Computing and Data-mining for Climate Integrated Energy System Models project (ACDC-ESM) introduced a faster single-unit commitment algorithm enabling decentralized solving. Three big data methods were developed to identify critical events affecting energy systems. Application to a future European power system revealed that specific weather regimes increased the likelihood of unserved energy.

The International Conference on Software Business aims to redefine the software industrys future through a scientific lens, focusing on ethics, equity, and sustainability. ICSOB 2024 invites interdisciplinary collaboration among researchers, practitioners, and policymakers to address ethical challenges, promote inclusivity, and ensure sustainable practices in the software sector. The conference brings together international experts in the fields of software business and software production, addressing topics such as AI in software production, ethics, sustainability, software engineering, and data science.

The project involves developing scientific foundations for a system that `looks over the surgeons shoulder during robot-assisted surgery and issues warnings when a dangerous move is likely to be made, such as touching or damaging anatomical structures not involved in the operation. This research will improve safety of robot-assisted surgical procedures.