Generative AI like ChatGPT has been diagnosed to fundamentally impact different realms of life. This includes science communication, where GenAI tools are becoming important sources of science-related content for many people. This raises the question of whether people trust GenAI as a source in this field, a question that has not been answered sufficiently yet. Adapting a model developed by Roberts et al. [2013] and utilizing survey data from the German Science Barometer 2023, we find that Germans are rather sceptical about and do not strongly trust GenAI in science communication. Structural equation modelling shows that respondents' trust in GenAI as a source in science communication is driven strongly by their general trust in science, which is largely driven by their knowledge about science and the perception that science improves quality of life.

Evaluations are becoming more important in science communication. But both science communication practitioners and researchers are not sufficiently utilizing the potential of evaluations yet. In this essay, we first define four requirements for rigorous evaluations of science communication activities and projects. To substantiate our argument, we take stock of the scientific literature, uncover deficiencies in current evaluation practices and identify potential causes. We conclude with laying out how different actors in the field — including science communication practitioners, professional associations, scientific institutions and funding bodies as well as researchers — can contribute to advancing evaluation practices in science communication as well as research on it.

ChatGPT provides original, human-like responses to user prompts based on supervised and reinforcement machine learning techniques. It has become the poster child of generative AI, which is widely diagnosed to disrupt many realms of life — including science communication. This essay reflects on this development. It discusses opportunities for the practice of science communication, such as generative AI’s translational and multimodal capacities and its capacity to provide dialogical science communication at scale, but also challenges in terms of accuracy, ‘wrongness at scale’ or job market implications. It also ponders implications for research on science communication, which has largely neglected (generative) AI so far. It argues that scholars should analyze public communication “about” AI as well as communication “with” AI, given its ‘increased agency’. Furthermore, scholars should analyze the impact of AI on science communication itself and the larger science communication ecosystem.

The public communication of higher education institutions (HEIs) has gained importance both in practice and research and can serve different goals. Many scholars argue that HEI communication departments mainly aim to promote their organization and are less concerned with broader societal goals and normative principles of communication. Since these assumptions have not yet been explored empirically, we surveyed 203 communication practitioners from all 42 Swiss HEIs on their role conceptions and the quality criteria used in their communication departments. Our results show no general dominance of organizational over societal goals and revealed few differences between different types of HEIs.

Since the early 1990s, there has been a considerable increase in the number of scientific studies on science communication, and this increase has been accompanied by a diversification of the research field. This study focuses on one aspect of this development: it analyses how citation network structures within the field have developed over time, and whether science communication research shows signs of becoming a research field or a discipline in its own right. Employing a co-citation analysis of scholarly publications published between 1996 and 2015, it assesses to what extent a coherent communication network exists within science communication research. The results show a field with a diverse internal structure and clear internal changes over time which suggest an increasing emancipation of the field.

Trust in science is, to a considerable extent, the outcome of communication. News and online media in particular are important mediators of trust in science. So far, however, conceptual works on mediated trust in science are lacking. Taking a cue from Weingart & Guenther, this commentary proposes a concept of mediated trust in science and for its measurement, and shows where it could be used in the science of science communication.