DOWNLOAD CALL FOR PAPERS

Scientific research is the most significant engine of knowledge development. It stands as a powerful drive that shapes societies and civilizations. Research relies on collecting, analyzing, and interpreting data using scientific approaches aiming at testing hypotheses and confirming their reliability and relevance. Hence; mastering these processes is a daunting challenge to address, regarding both the scientific issues and the required specific techniques and tools.

Dramatic advances in artificial intelligence (AI) offer opportunities to improve researchers’ performance. AI models can trigger a profound revolution in scientific research processes, whose fundamental foundations have remained unchanged for centuries. Researchers seeking to use AI systems to overcome their cognitive ability limitations, should acquire new skills such as database preparation and algorithms among many others. It is, therefore, possible that a divide may emerge between researchers who are more familiar with AI and those who are not, with the former having privileges in terms of access to databases and analytical methods.

AI is a relevant topic of investigation for researchers. However, for AI to have a positive impact on research, it is crucial to render data and research results accessible for all; a fundamental concern of open science (OS) that promotes openness, transparency, and collaboration in research. Furthermore, it encourages a wide-spread of data sharing , ideas, and results, thereby enhancing scientific rigor, faster and more impactful discoveries (Goldstein, S., et al., 2016). Science openness is paramount in the field of AI, where algorithms are complex and black-boxed. By sharing their data and results, researchers should ensure AI systems are developed and used responsibly and ethically.

By allowing more access to data and resources, open science drives innovation and opens new avenues to solve almost every problem. Through OS principles, researchers can not only increase transparency and replicability of their works, but also stimulate innovation by allowing other researchers to harness and enrich their discoveries. Open science favors dynamic and inclusive research environments, where ideas flow freely, and creativity encouraged (Goldstein, S., et al., 2016; Lawson, C., et al., 2017; Borgman, C. L., 2015). Integrating artificial intelligence and open science offers exciting perspectives to scientific research. By combining AI analytical capabilities with open science transparency and collaboration principles, researchers can explore new avenues, and address challenges facing organizations around the world. From the development of more robust theories to innovation in research methodology, OS and AI will together be able to provide insightful answers to complex questions shaping the contemporary research landscape (Chellappan and Krishnan, 2018).

For AI and OS to unleash their full potential, several challenges need to be addressed. It is mandatory to use AI ethically and responsibly, ensuring that algorithms are fair, transparent, and privacy friendly. Similarly, promoting open science requires cultural and institutional changes that recognize and reward collaboration and sharing within research community. Furthermore, we need to ensure that open science and AI do not reinforce existing inequalities, but rather allow equitable access to knowledge.

This conference offers a solid ground to explore unprecedented opportunities and challenges to scientific research in the light of open science and artificial intelligence. Together, we can expand knowledge boundaries, enhance research practices, and contribute meaningfully to take research to the next level.