Artificial intelligence has revolutionised how we access and generate information. From instant summaries to automated news articles, AI tools can produce content at lightning speed. As many a content provider will tell you: “Yippee! Makes my life easier!”

But……….

With this convenience comes a darker issue. How can you trust that the AI-generated content is actually based on fact?

A recent example highlights the risks of taking AI-generated content at face value. In late 2025, articles began circulating online claiming that the Australian government had introduced a driving curfew for people over the age of 60. The story spread rapidly across social media and even appeared on some news sites, sparking confusion and concern among older Australians.

The catch? It was misinformation.

Misinformation: Information that is false or inaccurate, but shared without intent to deceive.
It often spreads through misunderstanding, lack of verification, or assumptions.

Disinformation: False information that is deliberately created and shared to mislead or manipulate. It’s intentional and often part of a coordinated effort.

No such curfew exists at the federal or state level. In Queensland, for instance, drivers aged 75 and over are required to carry a medical certificate confirming their fitness to drive, but there are no blanket restrictions or curfews for those aged 60 or above. The misinformation likely stemmed from an AI-generated article that misinterpreted licensing guidelines or fabricated policy changes based on unrelated data.

How on Earth could AI make such a leap???

While one could think that the AI tool used to generate the content had shacked up in a basement tripping on some questionable brownies, here are a few likely contributing factors:

* Pattern extrapolation: AI models are trained to detect patterns and generate content that ‘fits’. If the model sees that older age groups are associated with driving restrictions (eg. medical certificates at 75), it might extrapolate that younger seniors might also have restrictions similar to age-related rules that exist in other countries.

* Semantic blending: AI often blends concepts from different sources. It might have combined:
– The 75+ medical certificate rule in Queensland
– International examples of senior driving restrictions
– Public discourse around aging and road safety
… and synthesised a fictional policy that sounded official.

* Prompt ambiguity or bias: If the original prompt was vague (eg. “What are the new driving rules for seniors in Australia?”), the AI might fill in gaps with assumptions. Worse, if the prompt was biased or leading (eg. “Write about Australia’s new curfew for older drivers”), the model could fabricate details to match the premise.

* Lack of real-time verification: AI models don’t inherently cross-check facts against live government databases unless explicitly designed to do so. Without external oversight they can confidently generate falsehoods that mimic regulatory language.

AI can be a powerful assistant, but it lacks judgment. Without human oversight, it can unintentionally reinforce stereotypes, misrepresent laws… all leading to panic – especially when the output is shared widely without verification. Once misinformation is published and it sparks outrage, it can be amplified quickly.

This incident underscores the importance of human-in-the-loop standard operating procedures (SOPs). When you’re publishing or creating content, AI should never operate in isolation… particularly, when accuracy matters. SOPs that include human review – especially for legal, medical, or policy-related outputs – help catch errors and contextual gaps before they reach the public. These checks are vital for ensuring that AI enhances rather than undermines what we as humans consume.

FAQ: Can You Trust AI-Generated Information Without Double-Checking?

What is AI-generated misinformation?
AI-generated misinformation refers to false or inaccurate content produced by artificial intelligence without intent to deceive. It often arises from misunderstood data, vague prompts, or pattern extrapolation, and can sound convincingly official.

What’s the difference between misinformation and disinformation?
Misinformation is incorrect but shared in good faith.
Disinformation is deliberately false and designed to mislead. In the case of the fabricated driving curfew for over-60s in Australia, it was misinformation, unless proven to be intentionally prompted.

Did the Australian government introduce a driving curfew for over 60s?
No. This claim was false. There is no curfew for drivers aged 60+ at the federal or state level. In Queensland, drivers aged 75 and over must carry a medical certificate confirming their fitness to drive – but that’s the only age-based requirement.

How could AI make such a leap from age 75 to 60?
AI models can:
* Extrapolate patterns (eg. assuming younger seniors might also face restrictions)
* Blend unrelated concepts (eg. mixing Queensland rules with international policies)
* Fill gaps with assumptions if prompts are vague or biased
* Lack real-time verification, leading to confident but incorrect claims

What are human-in-the-loop SOPs, and why do they matter?
Human-in-the-loop Standard Operating Procedures (SOPs) ensure that AI-generated content is reviewed by a human before publication, especially for legal, medical, or policy-related topics. These checks catch errors, prevent panic, and uphold public trust.

How can I verify AI-generated content?
* Cross-check with official government websites and reputable news outlets
* Look for credible citations and verify them
* Be skeptical of sweeping claims, especially about laws or health
* Treat AI like a fast assistant, not a final authority

So what can you do?

* Always cross-check AI-generated claims with trusted sources, such as official government websites, reputable news outlets, or subject matter experts.

* Look for citations and verify them. Remember, there have been cases where AI has even falsified citations. If an article doesn’t link to a credible source, treat it with skepticism.

* Be especially cautious with content that makes sweeping claims about laws, health, or public policy.

AI is a powerful tool, but it’s not infallible. As users, we must pair its speed with our own discernment. Have your Virtual Assistant double-check content before publishing. Highlight how important it is to behave like a journalist from ‘the good old days ‘ – checking with more than one credible source, questioning biases, and searching for loopholes.

And regarding the title of this article: “Can You Trust AI-Generated Information Without Double-Checking?”… you can probably guess the answer already – it is a resounding “Hell, no!”