SCIENTIFIC COLLECTIVE and ARTIFICIAL INTELLIGENCE
Welcome to the First Round !
Submit here you contribution, including name, academic email address and Institution.
In this round we expect that most contributions will consist of approximately one page of text. Other formats are acceptable if you provide a reason for it.
Please provide as an attached supplementary file full details of any AI interactions, including models used, prompts and responses.
Here are the guidelines:
A Federated, AI-Curated Clinical Knowledge Archive for Diagnosis and Research
Contributed on Sept 7, 2026 by Stefano Bae
PhD student, La Sapienza University, Rome, Italy
Goal
From Instruments to Reusable Data: an AI Layer for Experimental Data
Capture and Reuse
Contributed on Sept 3, 2026 by Francesco D'Amico
PhD student, La Sapienza University, Rome, Italy
SEE ATTACHMENTS
AI-assisted science needs a collective verification network
Contributed on Sept 2, 2026 by Luca Maria Del Bono
PhD student, La Sapienza University, Rome, Italy
Artificial intelligence (AI) is already changing radically the way scientific research is carried out. Programming, numerical calculations, literature searches, data analysis, or the exploration of alternative hypotheses are increasingly being delegated to AI systems. This allows scientist to focus on more higher level and creative-based tasks. Additionally, this change has the potential to make science much more interdisciplinary. At variance with system-specific research that has been carried out in the last decades, a researcher can now use AI to explore questions that require knowledge or technical tools outside their main field of expertise. A physicist, for example, might use AI to construct a model involving biological mechanisms that they would previously have lacked the expertise or time to investigate.
However, the same development creates a…