Open Science at the generative AI turn: An exploratory analysis of challenges and opportunities

Area of Science:

• Information Science
• Computer Science
• Scientific Policy

Background:

• Technology is integral to Open Science (OS) practices, influencing transparency, accessibility, and participation.
• Generative Artificial Intelligence (GenAI) is increasingly adopted in research for tasks like text refinement, coding, literature review, and data analysis.

Purpose of the Study:

• To explore the multifaceted impacts, both positive and negative, of Generative Artificial Intelligence (GenAI) on Open Science (OS) objectives.
• To systematically analyze the intersection of GenAI and OS using the UNESCO Recommendation on Open Science taxonomy.

Main Methods:

• Systematic exploration of GenAI's intersection with OS principles.
• Analysis based on the taxonomy within the UNESCO Recommendation on Open Science.

Main Results:

• GenAI can potentially enhance OS by improving knowledge access, efficient infrastructure use, societal engagement, and inter-knowledge system dialogue.
• GenAI's limitations pose risks to research integrity, equity, reproducibility, and reliability, potentially harming social actors.

Conclusions:

• GenAI offers significant potential to advance Open Science objectives.
• Critical assessment, validation, and checks are crucial for integrating GenAI responsibly into research to uphold OS values.