In an era increasingly driven by artificial intelligence, ensuring ethical development and testing practices is more crucial than ever. In this thought-provoking session, Gaurav Khurana will explore the core principles of Responsible AI, including transparency, accountability, fairness, and privacy. These principles act as a foundation for building trust, mitigating algorithmic biases, and ensuring responsible data usage, ultimately fostering an AI ecosystem that prioritizes human welfare and respects privacy rights.

In this session, Gil Zilberfeld highlights a critical challenge in test automation—the creation of "Frankenstein tests." These tests combine programming languages, frameworks, and domain-specific languages into a mishmash that is difficult to read, interpret, and maintain. While this approach may seem functional initially, it often leads to complex, fragile tests that become a burden as projects evolve. Gil emphasizes the importance of addressing this issue to prevent the "monster" of unmanageable tests from overwhelming your testing strategy.