How does Google want to apply artificial intelligence in healthcare?
Recently, DeepMind's leaders announced its healthcare team will be combined into Google to help them become the "AI-powered assistant for nurses and doctors everywhere."
Observers say the move is part of a broader effort within Google to boost collaboration and communication among health projects.
In a statement, DeepMind leaders said the company has "made major advances in health care in AI research," including advances related to "detecting eye disease more quickly and accurately than experts; planning cancer radiotherapy treatment in seconds rather than hours; and working to detect patient deterioration from electronic records."
One of its most prominent projects is Streams, an app developed with the United Kingdom's National Health Service that clinicians can use to detect health issues, such as kidney failure. The app enables nurses and physicians to view patients' vital signs, test results and medical histories in one place.
In a statement, DeepMind leaders said its healthcare team will move to Google in an effort to expand Streams' reach. The leaders said they want Streams to become "an AI-powered assistant for nurses and doctors everywhere."
What are the prospects for Google’s AI initiatives in healthcare?
Artificial intelligence and machine learning have demonstrated their promise on a broad range of healthcare decision-making tasks, ranging from better readmissions predictions, financial forecasting and acute clinical diagnoses.
Alphabet's DeepMind group has pushed frontiers in AI at a dizzying pace, tackling everything from chess to automatically diagnosing eye disease. Therefore, its recent announcement that some of the more practically focused teams within DeepMind Health will move to Google and focus on commercializing AI capabilities has provoked strong reactions within the UK and the US.
In the UK, many NHS patients are deeply skeptical of data sharing outside of their local health trusts, partly dating back to the NHS's failed Care.data national exchange, which they terminated in 2016. Smaller scandals, including DeepMind's collaboration with Royal Free NHS Trust, a London-area system, have made headlines and further entrenched a belief that all sharing with commercial interests is dangerous—regardless of the details.
By contrast, US health systems routinely share data with analytics firms and other vendors within a framework permitted under HIPAA. Vendors are required to sign business associate agreements (BAAs) with the healthcare organization, which limit the scope and permitted uses of data. HIPAA places sharp restrictions on selling data, but does allow commercialization of insights and predictive models distilled from it.
But besides the patient data privacy issues with the NHS, there is another business angle to this story. Google likely wants greater control of DeepMind because it needs to make a more immediate impact in the highly competitive AI market, where they're facing constant competition from the other big tech vendors such as Microsoft, Apple and Amazon.
There are a range of AI capabilities, from narrowly focused "task AI," to "general AI" or more flexible intelligence that closely resembles human intelligence. During the last few years, the healthcare industry has seen a growth in examples of task-oriented decisions driven by AI, particularly for administrative processes. On the other hand, clinical decisions driven by a more general AI is still a concept mostly out of reach.
DeepMind essentially falls into the latter category—a research company that has a long-term view to create general AI. It has a team loaded with talent that works on a variety of projects with great potential, however years into its acquisition, it has not focused much on commercializing its products on a large scale.
If they can do this commercialization successfully, and translate DeepMind's advances into scalable decision support for patients and providers, there is tremendous potential. Even narrowly focused assistive technologies can be tremendously helpful and free up overwhelmed decision makers to focus on other areas of care.
In the same way Google Maps now offers super-human navigation skills to anyone with a smartphone, we're optimistic that the judicious use of AI will help providers deliver better, more consistent, and more efficient care than a purely human system can.