Can Generative AI Help Combat Medical Misinformation?

 Can Generative AI Help Combat Medical Misinformation?

What happens nearly six million times a minute? That’s one estimate of how many Google searches were conducted every 60 seconds in 2022. In that same one-minute-time frame,, we also generated nearly 350,000 tweets, sent 230 million emails, and uploaded 500 hours of YouTube video. 

That’s a lot of data. If you multiply these figures across all of the types of content on the internet, it brings to mind the image of a plant furiously sprouting new tendrils that stretch and curl without any indication of slowing down. The internet is that plant, and when it comes to accurate content, it’s becoming increasingly difficult to separate truth from falsehood among the foliage. 

AI Generation’s Accuracy Crisis 

Medical misinformation itself isn’t new; snake oil salesmen have been around for millennia. But these days, Google is our first stop when we want to know something. The fact that it’s not easy to tell what’s true and what’s not is a big problem—and our health is on the line. COVID crystallized this issue.

At the same time, healthcare organizations must keep up with ever-growing demands for medical and patient content. Generative AI seems like the natural answer to these pressures, but the new technology keeps making it into the headlines for its lack of accuracy. And healthcare content producers have to ensure that their content is reliable above all else.

Given this landscape, can AI play a helpful role in combating medical misinformation?

To answer this question, we need to understand how the technology works. Then we have to look at how those operations come into play in the specific realm of healthcare writing. Let’s dive in.

The Four Pillars of AI and User Interaction - How it Works

AI is built upon four pillars that describe the way users interact with the technology. These pillars are:

  • data capture, 
  • classification, 
  • delegation, 
  • and social. 

In the case of generative AI, the most relevant aspects are data capture and delegation, and it’s these that we will focus on for the purposes of this article. 

Data capture

While generative AI didn’t become a kitchen table topic until recently, we’ve been integrating AI into our daily lives for some time now. We’re all intimately acquainted with the data capture aspect of AI. When you give your Amazon Alexa device a command, it captures the data in your request and uses it to perform the task. Ever notice the automatic response options at the bottom of a Gmail screen? Gmail captures the data in your email and uses that information to offer you those suggestions.


Delegation is just what it sounds like - handing off tasks from one party to another. It refers to our action of giving certain tasks to the AI. When we ask Alexa to tell us the weather forecast, or click on Gmail’s suggestion to respond “Thanks so much!” to that email, we have delegated to Amazon or Google things that we could have done ourselves.

How data capture and delegation work in generating healthcare content

Companies across industries are already using AI to draft a range of content types, and healthcare organizations are no different. The technology can be used to create blog posts, caregiver guides, post-appointment notes, preventative care flyers and more. No matter what type of medical content you need to create, the process is the same when you use generative AI:

  • Data capture: First, the AI tool captures the parameters from your prompt (subject, subtopics, voice, tone, etc.).Then it uses that data to do research by searching for more data on the internet.
  • Delegation: Through this process you assign the creation of the draft to the AI tool.

How to put AI to use in preventing medical misinformation

The key to avoiding medical misinformation—or preventing it altogether—lies in both the data capture and delegation phases. First, you need to make sure that the data that is being captured is high-quality and fact-based. This can seem like a tall task. After all, generative AI pulls its information from the internet, which is already riddled with inaccuracies. If a human can be fooled, how can we make sure that our generative AI isn't fooled?

The degree of delegation matters because content managers and creators are going to have to strike the right balance between the amount of work that they delegate to the technology and how much they continue to own. Too much human intervention will slow the process down and dilute or eliminate the benefits of AI. But people also can’t rely entirely on AI at this stage of the game.


The chart above is a depiction of the way that the degree of human involvement and AI involvement in a task affect the accuracy of the end result. The red dot is the point at which a person and the AI have equal shares of the work. There isn’t much difference in accuracy close to the dividing line, no matter what side you’re on.

But even before the advent of ChatGPT, popular opinion on AI has swayed back and forth, between a desire to use AI to relieve us of part of our workloads, and a reluctance to trust it. When ChatGPT first emerged, there was a rush to embrace it. But as more instances of inaccuracy have become public knowledge, the pendulum has swung back to the side of mistrust.

All that said, it’s important to remember that AI is a tool. If you can control that tool, you can reap its benefits. And a good starting point is ensuring that it is pulling from reputable sources. Learn more at if you want to start using AI content support to write faster without medical misinformation. 

This is where Grafi AI can help.

How Grafi AI can help combat medical misinformation

Grafi AI takes the uncertainty out of the data capture phase of content generation. On its own, the platform uses only data from credible medical sources. You can also introduce your own handpicked, vetted sources to add more trusted data. In this case, you’re assisting the AI in the data capture phase while still delegating easily automated tasks—and speeding up the entire process as a result. At the same time, you can create first drafts of useful, trustworthy articles, guides and more while resting easy that they are all grounded in solid fact. 

The entire process takes just a few minutes, in contrast to the hours or days that used to be spent in painstaking research and writing. Then the writer can take over to customize the content to the brand. Grafi AI is the only generative AI platform specifically for healthcare writers. It relieves them of the hardest part of the task and gives them an accurate, high-quality first draft that they can spend their time refining and polishing. 

With Grafi, you have more control over the data capture and the delegation process. With Grafi, you are in control of the AI.

Key Takeaways

  • Generative AI can help content managers and creators combat medical misinformation. The key is to make sure that the data the AI captures to create the draft is factual. 
  • You need to remove the uncertainty out of the data capture phase of content generation by using only credible medical sources. 
  • Users should also be able to add handpicked, vetted sources that will help further customize their content. 
  • Grafi AI is the only generative AI platform specifically for healthcare content writers. It relieves them of the hardest part of the task and gives them an accurate, high-quality first draft in minutes. Then they can spend the time they saved refining and polishing it to their standards. Sign up, and generate your first content for free.

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