Databases and Data Processing in the Life Sciences: Why Should We Care in the AI Era?

Lecture slides for the Introduction to Data Analysis course unit (Biology), November 2026. The talk examines why biological databases and data processing still matter in the AI era: the scale of public sequence data, the gap between information and wisdom, and the limits of both data and human judgment. It uses examples of bias, irreproducible or retracted studies, and unpublished negative results to argue that AI-generated information becomes reliable knowledge only through critical thinking, context, and human oversight.