Dawn Bloxwich and Tom Lue outline how DeepMind embeds responsibility into AI development from day one — using red-teaming, factuality initiatives, and real-world feedback to address immediate risks like hallucinations and misinformation. They stress proactive evaluation of long-term frontier risks, including loss of control and societal harms, while publishing transparent yet competitive-safe assessments. Globally, DeepMind advocates for application-focused regulation and technical collaboration across borders — though geopolitical divides, especially with China, complicate harmonization. Differing national approaches are evident: the EU’s AI Act is now undergoing pragmatic recalibration, Singapore leads with agility, and the US faces fragmentation and political volatility. Ultimately, the team argues that robust safeguards don’t hinder innovation — they enable trustworthy, scalable progress in science, climate forecasting, robotics, and beyond.