How Will Cloud Computing AI Proliferate in Healthcare?

| October 28, 2020

We’ve been saying this for a while, but we believe that the vast majority of computing is going to be done in the cloud.

Very few companies in the fullness of time, whether it’s five years from now, 10 years from now, or 15 years from now, will own their own data centers, and those that do will have much smaller footprints. All that is moving to the cloud.

We’re at the very beginning of this big shift. We can expect a lot of geographical expansion as well as huge investments and continued substantial capabilities in machine learning and AI, connected devices and IoT. And voice will be an increasingly larger percentage of the total applications out there.

When we first started being able to use applications on the phone, tapping a few times felt pretty handy. Then you used an application on something like Alexa, a voice-driven application, and it actually seems awfully inconvenient to have to tap three or four times.

We’re going to see an explosion of voice applications over time as well, and AI in Healthcare will become mainstream with voice-assisted technology and chatbots automating many of the tedious and simple activities, such as booking appointments.

What are the ethical implications for the cloud computing AI space?

In the longer term, we’ll see more and more clinicians come to rely on the capabilities of AI. For example, in diagnosis, Babylon Health’s technology is already providing useful information to clinicians. This will improve over time as the algorithms underpinning Babylon Health’s services are refined as a result of access to richer data sets from applied treatments and resultant patient outcomes.

AI and clinicians will continue to have complementary roles. Humans will remain the most appropriate providers of care, because the human context of that care is an essential element to recovery, and has a powerful bearing upon it.  AI technology has the potential to free up a great deal of clinician time to focus more on the patient rather than the mechanics of their care, but AI is still artificial, reliant upon algorithms built on prior health data for patients will similar conditions in the past but is inherently better equipped to take advantage of those prior data better than humans can.

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