The Second International Workshop on AI Principles in Science Communication (Ai4SC)

In an era when the boundaries of science and technology are increasingly overlapping, the emergence of generative AI and large language models (LLMs) has marked a pivotal shift in scientific communication. These avant-garde technologies offer opportunities to enhance the dissemination of complex scientific knowledge, making it more accessible and understandable to the scientific and research communities.

Furthermore, the recent integration of generative AI and research tools puts science communication ahead of significant challenges, notably in maintaining and fostering innovation and research across research communities. This paradigm shift and the novel scientific communication approach have necessitated the evolution of the current software ecosystems and repositories into a new dimension. This presents a potential gap and signifies a concerted effort across the community to develop strategies that address and bridge this gap.

It is critical that the data and computational science community investigate how Generative AI, Knowledge Graphs, and NLP can redefine scientific knowledge structuring, sharing, and understanding. Beyond communication, these technologies are becoming essential for developing, managing, and making scientific software and repositories usable—key enablers of modern research.

Building on the success of our previous workshop, this event will bring together scientists, technologists, AI researchers, ethicists, and software developers to explore this evolving intersection of AI and scientific communication. Together, we will examine how AI-driven techniques can enhance scientific discourse, improve software and repository accessibility, and address the broader implications of automation in research workflows.

Overview (Workshop Theme and Key Topics)

This workshop explores the fundamental scientific communication methodology using AI technology, software ecosystems, and methods of software usability, discovery, and automation, AI-enabled software and repository for enriching scientific communications, constructing tools like automated knowledge processing, knowledge graph constructions, and documentation generation in the context of science communication.

Through a series of presentations and discussions, participants will gain a comprehensive understanding of how AI, particularly generative AI, can transform science communication, making complex information more accessible and engaging for a broader audience.

Furthermore, beyond communication, the workshop will highlight the broader impact of AI on scientific software ecosystems and repositories, as well as integration with critical technologies such as databases, workflow management, knowledge graphs, ontologies, and security frameworks.

Discussions will explore AI-driven techniques for software analysis, repository management, discovery, and reusability. Additionally, the workshop will highlight the interconnectedness of generative AI with other critical technologies, including databases, workflow management, knowledge graphs, ontologies, and security mechanisms.