One of the more interesting panels at last week's Health Datapalooza featured four speakers involved in the application of artificial intelligence to healthcare, including the creation of predictive models. In areas involving massive amounts of information in the diagnostic and genomic space, machine learning is already in use today, and the FDA is starting to approve applications of deep learning. For instance, a company called Arterys recently won FDA approval for its Cardio DL application, which uses deep learning to automate time-consuming analyses and tasks that are performed manually by clinicians today. Although they each come at it from a different angle based on their company's focus, there were several overarching themes the Datapalooza panelists tackled about the application of algorithms in healthcare, including the importance of transparency to getting clinician engagement. Getting buy-in from clinicians is a huge challenge, said Eric Just, a senior vice president for product development at Health Catalyst, which builds analytics and decision support tools for its health system customers.
Elon Musk's secretive "brain-machine interface" startup, Neuralink, stepped out of the shadows on Tuesday evening, revealing its progress in creating a wireless implantable device that can – theoretically – read your mind. At an event at the California Academy of Sciences in San Francisco, Musk touted the startup's achievements since he founded it in 2017 with the goal of staving off what he considers to be an "existential threat": artificial intelligence (AI) surpassing human intelligence. Two years later, Neuralink claims to have achieved major advances toward Musk's goal of having human and machine intelligence work in "symbiosis". Neurolink says it has designed very small "threads" – smaller than a human hair – that can be injected into the brain to detect the activity of neurons. It also says it has developed a robot to insert those threads in the brain, under the direction of a neurosurgeon.
The US Food and Drug Administration has announced that it is preparing to regulate AI systems that can update and improve themselves as they gorge on more training data. The announcement: The agency released a white paper proposing a regulatory framework to decide how medical products that use AI should seek approval before they can go on the market. It is the biggest step the FDA has taken to date toward formalizing oversight of products that use machine learning (ML). The challenge: Machine-learning systems are tricky to regulate because they can continuously update and improve their performance through new training data. In instances where the FDA has approved ML-based medical software before, it has required the algorithms to be "frozen" before commercial deployment and to go through a reapproval process when they are changed.
The experimental Smart Tissue Autonomous Robot (STAR) recently sewed a piglet's gut together using a computer program and camera-based guidance, overseen by a team of doctors and computer scientists from the Children's National Health System in Washington DC and Johns Hopkins University. The procedure took 50 minutes, as opposed to 8 minutes when performed by a surgeon, but (unfortunately for doctors) resulted in more evenly spaced sutures and less leakage from the gut. And with iterative improvements, it's likely that the time difference can be shrunk. Meanwhile, FDA-approved robotic surgery on humans is making strides as well, though it requires a surgeon to operate the mechanical arm. The potential treatment paradigm, highlighted by The Economist this month, raises questions about whether patients will trust robots with their lives, and who is liable if something goes wrong.
The 19th-century U.K. Locomotive Act, also known as the Red Flag Act, required motorized vehicles to be preceded by a person waving a red flag to signal the oncoming danger. Movies can be a good place to see what the future looks like. According to Robert Wallace, a retired director of the CIA's Office of Technical Service: "... When a new James Bond movie was released, we always got calls asking, 'Do you have one of those?' If I answered'no', the next question was, 'How long will it take you to make it?' Folks didn't care about the laws of physics or that Q was an actor in a fictional series--his character and inventiveness pushed our imagination ..."3 As an example, the CIA successfully copied the shoe-mounted spring-loaded and poison-tipped knife in From Russia With Love. It's interesting to speculate on what else Bond movies may have led to being invented. For this reason, I have been considering what movies predict about the future of artificial intelligence (AI).