Google is producing some of the best AI models, but it has already set its sights on using AI to impact fields far removed from it.
Jeff Dean, Google’s Chief Scientist and one of the architects of the company’s AI infrastructure, has articulated an ambitious vision for healthcare that goes far beyond incremental improvements. Speaking about artificial intelligence’s potential in medicine, Dean outlined what he calls a “moonshot goal”—a vision that would fundamentally transform how medical knowledge is accumulated and applied across the entire healthcare ecosystem.
“I think I am quite passionate about the application of AI to health in various ways,” Dean explained, “and I think the moonshot, if you like, would be how can we as society use every past decision that’s been made in health to inform every future decision.”
It’s a deceptively simple statement that masks enormous complexity. Dean’s vision isn’t just about building better diagnostic tools or more efficient hospital systems. Instead, he’s proposing a fundamental reimagining of medical knowledge itself—transforming it from isolated decisions made in individual clinics and hospitals into a vast, interconnected learning system that continuously improves with every patient interaction.
“That’s a super hard goal because there’s all kinds of impediments to doing that,” Dean acknowledged. “There’s very real privacy concerns. There’s complicated regulatory requirements that differ for every jurisdiction. But I think if we kind of aspirationally try to say what could we do so that we can learn from every past decision that’s been made in a way that helps us have every clinician and every person themselves be informed and make better decisions in the future—that would be an awesome, amazing goal.”
Dean’s candid recognition of the challenges is as significant as the vision itself. Privacy concerns in healthcare aren’t theoretical—they’re deeply personal and protected by regulations like HIPAA in the United States and GDPR in Europe. The fragmented nature of healthcare data, locked away in incompatible systems and jurisdictions, presents technical hurdles that even the most advanced AI cannot easily overcome. Yet Dean’s framing suggests these aren’t reasons to abandon the goal, but rather problems to be solved through careful, ethical innovation.
Google’s work in healthcare AI has already begun laying the groundwork for this vision. The company’s AlphaFold breakthrough, which solved the protein folding problem that had stumped scientists for decades, demonstrated AI’s potential to accelerate biological understanding at a fundamental level. The success was so profound that Google spun out Isomorphic Labs, a drug discovery company, to translate these capabilities into actual therapeutics. Meanwhile, Google Research has published work on AI systems that can detect diabetic retinopathy from eye scans, predict patient deterioration in hospitals, and assist radiologists in identifying breast cancer—all examples of using past medical data to inform future clinical decisions.
What Dean is proposing, however, is a leap beyond these individual applications. He’s envisioning a future where the collective intelligence embedded in billions of medical decisions—from diagnoses and treatment choices to surgical techniques and medication adjustments—becomes accessible to every clinician and patient at the point of care. It’s a vision where a doctor treating a rare condition in rural India could instantly benefit from patterns learned across similar cases worldwide, or where a patient with multiple chronic conditions could receive personalized guidance informed by the outcomes of thousands of people with similar health profiles. Google DeepMind CEO Demis Hassabis has already said that AI has a shot at solving all disease in 10-15 years. The technical, ethical, and regulatory challenges are immense, but for a company that has built its empire on organizing the world’s information, the ambition to organize and democratize medical knowledge seems like a natural, if extraordinarily complex, next frontier.