Artificial intelligence in healthcare: Is it ready for deployment?
So why isn’t healthcare, a multi-million industry, adopting artificial intelligence yet? Let’s find out.
Artificial intelligence. The tech industry is just so enthusiastic for it and with good reason. As if the ability to process immense amounts of data wasn’t already good enough, the ability of AI to use this data and to learn from it in order to make subsequent interactions is nothing short of amazing.
This change in behavior based on experience is what makes most if not all, organisms function properly. And to have that ability to learn not only makes it capable of problem-solving, this literally means that as the technology learns more, the more effective it’s going to be. So why haven’t we integrated this technology into our healthcare systems yet?
After all, tech companies like Google have already subtly integrated AI into our phones. The prime example of this isn’t Google Assistant or Siri, but rather in how Google Photos is able to identify faces in the Photos app. Don’t you think it’s equally impressive as it is scary that the app is able to relate one face in one photo to another face in a different photo?
So why isn’t healthcare, a multi-million industry, adopting artificial intelligence yet? Even the feature of being able to identify what’s in a picture is going to be incredibly useful in diagnosis.
This is nothing new to the healthcare industry
In fact, healthcare organizations like the National Health Services (NHS) were rather slow in adopting paperless digitization when it was being pushed forth a few years ago, while most companies have already adopted the new tech.
The answer to this snail’s pace is simple. Unlike the tech industry where consumer products are introduced at a rapid rate (just observe how we have so much new tech every year), healthcare companies push back on the adoption of new technology for several years because new tech needs to be absolutely foolproof. There can be no mistakes in the healthcare industry, especially since these are people’s lives that are at stake.
And should anything go wrong, these companies can’t simply say that their tech was faulty. A lot of these companies rely heavily on the trust of their patrons. To be known to have faulty technology can hurt a healthcare company’s reputation very much, whether it’s in diagnosis or even in customer service. If you have faulty AI, you’re much better off using conventional customer service methods like Ameridial.
So, why the delay?
The main reason for this is that before any new technology is adopted by the healthcare industry, these pieces of technology need to be extensively tested to ensure that the chance of failure is at least close to nil. These are the lives of people after all. And any fiasco related to any upcoming technology, as good as it may be, can easily damage the trust that clients have toward a company.
Because of this, healthcare companies want to be as sure as they can be before they can deploy new technology. But despite this, you should find comfort in the fact that when new technology is deployed in the healthcare industry, you can definitely trust it.
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