How Reliable Is AI, Really?

AI Fact Checking Tips And Techniques

How To Use AI Responsibly

Frequently Asked Questions (FAQs)

All too often, artificial intelligence turns out to be a questionable source of truth.

Unfortunately, hallucinations happen quite frequently, and extend to any and all types of searches. The 2026 Stanford HAI AI Index found hallucination rates across 26 top models ranging from 22% to 94%, depending on the benchmark and use case.

“When a false statement is presented as something another person believes, models handle it well,” the researchers found. “When the same false statement is presented as something a user believes, performance collapses.” We press on with AI, but there’s a clear need for AI fact-checking techniques.

The depth of such a re-examination depends on the nature of the inquiry. More casual, low-impact AI queries, such as confirming recipe ingredients, movie plots or shoe-store locations, likely will not require rigorous AI fact checking. High-impact AI queries, such as reviewing academic research, medical diagnoses and financial data, call for a very comprehensive verification. In such instances, AI users need to take a more critical eye and look deeper into the information they are extracting from AI.

How Reliable Is AI, Really?

Simple projects, such as summarizing a document, explaining a concept or drafting a first pass at something, can help jump-start inquiries. However, it should not be fully accepted as a final source of information, especially for high-impact queries.

At first glance, AI seems to function as a search engine on steroids, rapidly locating and summarizing information on any topic. But it is quite different from conventional search engines. Pragati Awasthi, an assistant teaching professor at Drexel University, explains that AI models generate text by predicting statistically probable word sequences based on patterns learned during training. “It means an AI can produce a response that sounds authoritative, reads fluently and is completely wrong all at once,” said Awasthi.

The accuracy rate for AI answers generated is an open question, subject to many variables. “Even humans often struggle to determine whether a decision was correct. This is precisely why we have legal systems to gather evidence and arrive at a consensus about truth and responsibility,” said Jan Liphardt, an associate professor at Stanford University and CEO of OpenMind.

At least 45% of all AI answers in a study conducted by BBC and the European Broadcasting Union had at least one significant issue. The research, based on input from 22 media organizations, also found 31% had sourcing problems — missing, misleading or incorrect attributions. Another 20% of AI answers contained major accuracy issues, including hallucinated details and outdated information.

One estimate for error rates on a general-purpose AI on complex professional queries possibly falls into the 20% to 40% range, estimated Dr. Fara Kamangar, founder of DermGPT, the dermatology industry’s first AI tool. Even at the low end of this estimate, 20%, is something to be concerned about, according to Aleshia Hayes, a clinical associate professor at Southern Methodist University, based on her own experience with her queries and........

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