Carina Ines Hausladen

ETH Zurich | ETH Zürich · Department of Humanities, Social and Political Sciences

This paper investigates the voting behaviors of Large Language Models (LLMs), specifically GPT-4 and LLaMA-2, their biases, and how they align with human voting patterns. Our methodology involved using a dataset from a human voting experiment to establish a baseline for human preferences and conducting a corresponding experiment with LLM agents. We...

Social media manipulation poses a significant threat to cognitive autonomy and unbiased opinion formation. Prior literature explored the relationship between online activity and emotional state, cognitive resources, sunlight and weather. However, a limited understanding exists regarding the role of time of day in content spread and the impact of us...

We explore social perception of human faces in CLIP, a widely used open-source vision-language model. To this end, we compare the similarity in CLIP embeddings between different textual prompts and a set of face images. Our textual prompts are constructed from well-validated social psychology terms denoting social perception. The face images are sy...

Extensive literature probes labor market discrimination through correspondence studies in which researchers send pairs of resumes to employers, which are closely matched except for social signals such as gender or ethnicity. Upon perceiving these signals, individuals quickly activate associated stereotypes. The Stereotype Content Model (SCM; Fiske...

Collective action is essential for addressing the grand challenges of our time. However, for such action to be successful, decision-making processes must be perceived as legitimate. In this study, we investigate the legitimacy of different voting methods. Using a pre-registered human subject experiment, 120 participants cast their votes using four...

Participatory Budgeting (PB) has evolved into a key democratic instrument for resource allocation in cities. Enabled by digital platforms, cities now have the opportunity to let citizens directly propose and vote on urban projects, using different voting input and aggregation rules. However, the choices cities make in terms of the rules of their PB...

The current allocation of street space is based on expected vehicular peak-hour flows. Flexible and adaptive use of this space can respond to changing needs. To evaluate the acceptability of flexible street layouts, several urban environments were designed and implemented in virtual reality. Participants explored these designs in immersive virtual...

This paper investigates the voting behaviors of Large Language Models (LLMs), particularly OpenAI's GPT-4 and LLaMA-2, and their alignment with human voting patterns. Our approach included a human voting experiment to establish a baseline for human preferences and a parallel experiment with LLM agents. The study focused on both collective outcomes...

The current allocation of street space is based on expected vehicular peak-hour flows. Flexible and adaptive use of this space can respond to changing needs. To evaluate the acceptance of flexible street layouts, several urban environments were designed and implemented in virtual reality. Participants explored these designs in immersive virtual rea...

Social media manipulation poses a significant threat to cognitive autonomy and unbiased opinion formation. Prior literature explored the relationship between online activity, and emotional state, cognitive resources, sunlight, and weather. However, a limited understanding exists regarding the role of time of day in content spread and the impact of...

Digital democracy and new forms for direct digital participation in policy making gain unprecedented momentum. This is particularly the case for preferential voting methods and decision-support systems designed to promote fairer, more inclusive and legitimate collective decision-making processes in citizens assemblies, participatory budgeting and e...

Many experimental research designs offer participants the opportunity to chat with each other. While experimental research has traditionally treated text as process data, this paper proposes a novel approach to interpret and use chat data in a structured supervised classification task. Specifically, we provide a framework for supervised classificat...

This paper investigates the effects of temporal changes at the individual and the social level and their impact on cooperation in social networks. A theoretical framework is proposed to explain the probability of cooperation as a function of endogenously-driven periodical temporal variation and neural synchrony modeled as a diffusion process. Agent...

The technological revolution, particularly the availability of more data and more powerful computational tools, has led to the emergence of a new scientific area called Computational Diplomacy. Our work focuses on a popular subarea of it. In recent years, there has been a surge of interest in using digital technologies to promote more participatory...

We introduce a modified version of the die-in-the-cup paradigm to study (dis-)honest behavior under time pressure. Replacing the regular die with one with a distinct color on either side enables us to manipulate the amount of familiarity with the randomization device. This removes the limitations of the original paradigm and allows for a test of th...

In the context of urbanization and a growing population, cities and citizens are becoming more exposed and vulnerable to social and environmental changes, ranging from natural disasters like earthquakes and floods to uncertainties caused by issues related to climate change and complex social dynamics or even pandemics. There have been many debates...

The digital revolution has brought about many societal changes such as the creation of “smart cities”. The smart city concept has changed the urban ecosystem by embedding digital technologies in the city fabric to enhance the quality of life of its inhabitants. However, it has also led to some pressing issues and challenges related to data, privacy...

The digital revolution is reinventing business models, reshaping economic sectors, and changing entire societal institutions. Big Data and Artificial Intelligence, profiling and targeting, and several other technological developments are now fundamentally changing the ways economies work. This contribution discusses opportunities and threats of the...

In this thesis, I investigate decision-making in behavioral economics, experimental economics, and law and economics. The research questions I ask are: Can we nudge people towards being more honest? Can we use language to find out who lies? Which factors influence a judge’s decision, and how do people cooperate? Specifically, I investigate contribu...

This paper draws on machine learning methods for text classification to predict the ideological direction of decisions from the associated text. Using a 5% hand-coded sample of cases from U.S. Circuit Courts, we explore and evaluate a variety of machine classifiers to predict ”conservative decision” or ”liberal decision” in held-out data. Our best...