The challenges of verifying AI for healthcare

There is a lot of excitement in healthcare about the use of artificial intelligence (AI) to improve clinical decision-making. Pioneered by the likes of IBM Watson for Healthcare and DeepMinds Healthcare, AI promises to help specialists diagnose patients more accurately. Two years ago, McKinsey co-produced a report with the European Union's EIT Health to explore the potential for AI in healthcare. Among the key opportunities the report's authors found were in healthcare operations: diagnostics, clinical decision support, triage and diagnosis, care delivery, chronic care management and self-care. "First, solutions are likely to address the low-hanging fruit of routine, repetitive and largely administrative tasks, which absorb significant time of doctors and nurses, optimising healthcare operations and increasing adoption," they wrote.