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. And he’ll discuss what they might mean for IT leaders, physicians and patients.
To preview the event, West recently answered some questions from Healthcare IT News.
Q. Your book is titled Turning Point. Could you say a few words about what makes this moment in artificial intelligence policy unique?
A. AI is the transformative technology of our time. It is being deployed in many different areas and is altering how people communicate, work and learn. It offers a number of benefits but also poses considerable risks.
Q. What are some potential or pending regulations around healthcare AI that providers and tech developers should be paying attention to/preparing for in the near future?
A. There are lots of new applications coming online, from fitness trackers and remote monitoring devices to AI algorithms and data analytics. There likely won’t be much regulation of consumer devices, but there will be oversight of any applications with the potential for human harm. Devices that have inaccurate readings of blood pressure or glucose levels could be risky as could clinical decision support systems employed by health providers.
Q. What are some of the big challenges facing policymakers as they try to grapple with these fast-evolving technologies? Are federal agencies up to the task?
A. The biggest problem for policymakers is hiring staff with technical expertise. Government oversight always lags technology innovation, and it is hard for the public sector to be competitive in hiring people with technical skills because of the large salaries such people can earn in the private sector. How does the private sector fit in here? Should there be some consensus on certain areas of self-regulation?
Q. What are some use cases in healthcare where AI has the most potential?
A. There are algorithms that can read X-rays and CT-scans with high accuracy, so that will have big consequences for radiologists. There are many consumer devices that record vital signs, test for various medical conditions and compile data on medical conditions. The future is likely to be information rich.
Q. What are some areas that are perhaps concerning to you, where tighter regulation is needed?
A. AI applications definitely require greater oversight to make sure the algorithms conform to human values and protect personal privacy. There is a risk of unfair or biased decisions resulting from incomplete or unrepresentative data.
Q. According to your book description, “Near-term policy decisions could determine whether the technology leads to utopia or dystopia.” What are some of the biggest choices facing the healthcare industry, in particular?
A. The big choice concerns the balance between promoting health innovation on the one hand versus protecting personal privacy on the other hand. Digital applications generate a large amount of data and there are interesting questions about who owns that information and how the data can be used.
West will discuss more during his session on regulatory developments at the virtual HIMSS Machine Learning & AI for Healthcare event. It is scheduled to air Wednesday, December 15, from 11:05-11:30 p.m. ET.