This podcast episode focuses on how Google Search is affected by algorithmic bias and why users should be more careful about the risks that come with this system. We uncover the truth behind why certain autocomplete results are displayed, how the rankings of search results are determined, and what types of problematic images are shown when querying for specific information. We also discuss the rise of AI models and how they are used by Google Search to share biased information. Kevin Lin, a professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, features on this episode to answer questions students have about how search engines function and are affected by algorithmic bias, and share his thoughts about bias in Google Search.