The New Scientific Revolution? Consequences of AI and Big Data in Biomedicine

The advent of new digital tools, methods, and infrastructures is generating an overwhelming amount of data that researchers are eager to harness and analyze. In the biosciences, there is growing anticipation that artificial intelligence (AI) will provide the means to manage and make sense of this data deluge.

Significant investments are being made in AI technologies, including machine learning and deep learning, within the biosciences. These advancements have the potential to challenge, or even overturn, established scientific truths about how the world works. AI and machine learning thus hold the promise of revolutionizing our approach to knowledge acquisition.

This project will focus on studying the implications of integrating AI into biomedicine, with particular attention to the following questions:

• Impact on Scientific Practice: What are the consequences of supplementing or replacing human judgment and traditional scientific methods with AI technologies?

• Challenges to Established Knowledge: How might AI-based analyses challenge or redefine established scientific truths?

• New Pathways to Knowledge: In what ways can AI and machine learning provide novel insights into the complexities of the biological world?

By addressing these questions, the researchers aim to provide a deeper understanding of the transformative potential of AI in biomedicine and its broader implications for the future of scientific inquiry.