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AI medical misinformation is a growing public health threat

Jennifer Bechwati’s recent Channel 7 report on the rise of medical misinformation highlights a challenge clinicians are now confronting daily in their consulting rooms.

False health advice — increasingly delivered by AI-generated “experts” and fake doctors across social media — is spreading faster than evidence-based medicine can counter it. As the Australian Medical Association and the Royal Australian College of General Practitioners have warned, misinformation around vaccines, pregnancy, and treatment options is eroding trust in established medical guidance and placing growing pressure on frontline clinicians.

What is often missing from this conversation is an important distinction: not all AI is contributing to the problem. Some AI is being built deliberately to limit the spread of misinformation — not amplify it.

asksam™ was developed in direct response to this reality.

Unlike open, consumer AI tools that scrape the internet indiscriminately, asksam™ operates within a closed-source architecture. It does not rely on social media posts, influencer content, opinion blogs, or unverified websites. Instead, its medical knowledge is grounded in peer-reviewed medical literature, recognised clinical guidelines, approved product information, and trusted healthcare sources.

That distinction matters.

Today, many patients arrive at appointments armed with information designed for engagement rather than accuracy. Algorithms reward confidence, controversy, and speed — not nuance or clinical context. As a result, clinicians are spending increasing amounts of consultation time correcting misconceptions instead of focusing on care.

asksam™ is designed to work in the opposite direction.

Its role is to: • Filter out unreliable medical information rather than surface it • Align responses with established, evidence-based medical sources • Encourage appropriate clinical follow-up rather than self-diagnosis • Support clinicians — never replace them

In an environment where vaccine hesitancy has contributed to the re-emergence of conditions such as measles, the consequences of misinformation are no longer abstract. They are visible in delayed presentations, prolonged consultations, and heightened patient anxiety driven by conflicting information.

AI in healthcare should not add to the noise. It should help clinicians manage complexity, reduce cognitive burden, and guide conversations back to trusted medical evidence.

That is the role asksam™ is designed to play: more than a scribe — a medically grounded, accountable AI clinical assistant built to support clinicians and help counter misinformation at a time when the line between information and influence has never been more blurred.

asksam™ — your trusted AI-powered clinical assistant, designed to support clinicians and protect patients, with a human touch

Curious how it works?

asksam does all that and more

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Operates in a closed-source architecture

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Integrates notes into a holistic case file

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Provides patient specific outputs

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Provides medically derived suggestions admin

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Processes all types of medical documentation

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Acts as your medical encyclopedia

Accesses trusted medical literature

Clinicians can asksam anything and as the platform is trained on medical literature within a closed-source environment, the platform can act as an on-demand encyclopaedia drawing from reputable medical literature without the risk of hallucination from the open-source internet.

In the premium tier, asksam also offers a Health AI Education Program that helps clinicians build digital literacy and understand how to safely incorporate AI tools into clinical workflows.

Provides patient specific outputs

asksam tailors summaries, letters, and explanations to reflect the patient’s specific medical history, demographics, and clinical needs.

As asksam operates in a closed-source environment there is no need to de-identify patient data, meaning reports and insights are specific to the patient not at a population level.

Provides medically derived suggestions

asksam processes all documentation loaded by the clinician and uses its Clinical Knowledge Graph to investigate all known medical associations to provide suggestions based on medical literature for the clinician to consider in their clinical decision making.

These notifications are designed purely to support administrative workflow and reduce cognitive load. They do not assess patient risk, monitor clinical parameters, or generate independent medical recommendations. 

Processes all types of medical data

asksam processes clinical documentation across PDF and Word Documents, pathology results, imaging summaries, and medication histories within the patient’s context.

Instead, asksam helps present information more clearly and coherently to support documentation workflows. It does not analyse or interpret medical data for diagnostic, predictive, or monitoring purpose.

Operates in a closed-sourced architecture

asksam is built as a fully closed-source clinical AI system, ensuring every component is tightly controlled, verified, and secured. This architecture prevents external data access, training leakage, or exposure to open internet sources.

All patient information stays within the clinical environment, protected by strict privacy and compliance guardrails. The result is a trusted, healthcare-exclusive AI platform clinicians can rely on.

Integrates notes into a holistic case file

asksam captures each consultation and automatically organises it into a structured, longitudinal case file. Notes, letters, templates, and follow-up plans are connected to the patient’s history, giving clinicians a complete view of their care.

This allows consistent documentation across episodes avoiding fragmented notes and the need to manually add context.