What are the upcoming policies that will shape AI – and are policymakers up to the task?

As vice president and director of governance studies at the Brookings Institution, and a senior fellow at its Center for Technology Innovation, Darrell M. West spends a lot of time thinking about the intersection of policy and emerging tech. In his recent book, Turning Point: Policymaking in the Era of Artificial Intelligence, co-authored with Brookings President John R. Allen, West looks at AI use cases – "from self-driving cars to e-commerce algorithms that seem to know what you want to buy before you do" – and assesses where they're headed and how they will be shaped by policy decisions made today. The key challenge – not least in healthcare, where patient safety is paramount – is to devise regulatory guardrails that maximize the benefits of AI and machine learning and minimize their potentially dangerous downsides. In the book, West and Allen offer a series of recommendations – bolstering governmental oversight, creating new specialized advisory boards at federal agencies, third-party auditing to sniff out algorithmic bias and more. At the upcoming HIMSS Machine Learning & AI for Healthcare event, West will offer a presentation titled "The Latest Regulatory Developments Impacting Machine Learning and AI in Healthcare," where he'll explore potential new policy shifts around clinical uses of artificial intelligence: algorithmic bias, remote patient monitoring, patient safety, fitness trackers and more.