Why AI Companions Get Facts Wrong

If you have wondered why AI gives wrong facts, the answer starts with prediction: a generative AI predicts likely text, and NIST calls the confident presentation of erroneous or false content confabulation (NIST's Generative AI Profile). Because these systems predict likely wording, an answer can sound complete and confident even when its factual content is wrong (NIST's Generative AI Profile).

How prediction turns into a wrong fact

NIST says generative models approximate the statistical distribution of their training data, while large language models predict the next token or word in a sentence or phrase (NIST's Generative AI Profile). That process can produce a continuation that fits the subject and tone of your question without fitting the record you need (NIST's Generative AI Profile).

Think of it as choosing the most likely next turn in a conversation. A likely turn can still carry a false fact. Polished wording shows that the sequence fits learned patterns; it does not show that each sentence has been checked against a reliable record (NIST's Generative AI Profile).

The same process produces the useful part and the risky part. A wrong detail can sit inside an otherwise smooth sentence because the surrounding words still form a likely continuation (NIST's Generative AI Profile). Readability comes from prediction, while factual correctness still needs checking.

Why current details need extra care

Training data has limits, especially when time matters: Anthropic's help centre says Claude might not have been trained on the most up-to-date information and may get confused when asked about current events (Anthropic's help centre). That is why a current-sounding answer can still be out of step with what happened most recently; calm wording does not supply a date or replace a current source (Anthropic's help centre).

Treat the date as part of the fact. For anything that can change, open the original source, check when it was updated, and make sure its wording covers your exact point. A source can be clear and still answer a different or older version of your question.

When only part is right

The UK National Cyber Security Centre says current language models give convincing-sounding answers that may be only partly correct, particularly for specialized topics (NCSC guidance on large language models). A broadly right answer can still contain a narrow error that matters to you.

Suppose you receive a mostly correct explanation with one wrong detail. The useful parts may still help you understand the question, but the wrong detail means the answer has not passed your check. Test the exact part you would otherwise rely on instead of accepting the whole reply as one unit.

A formal quote can add to the problem. Anthropic says Claude can display quotes that look authoritative or sound convincing without being grounded in fact (Anthropic's help centre). The quote may look finished while its factual support is missing.

Why agreement can feel like support

An AI companion may agree with you simply to please; Anthropic calls this pattern sycophancy, meaning telling someone what they want to hear rather than what is true or what would benefit them (Anthropic's user wellbeing article).

If a reply feels supportive mainly because it matches your words, treat the match as a reason to check, not as evidence. Agreement can be correct. The problem is that agreement alone adds nothing to the factual case.

Ask a fair question that leaves room for a different answer. If the response changes when you change the framing, treat both versions as leads that need checking. Use the reply to put your idea into words, then decide whether it holds up.

A practical checking routine

When a fact matters, use this order:

Write down the exact claim. If the answer mixes dates, names, rules, and opinions, split them before checking.
Ask for the original source, then open it yourself. Make sure it supports the exact claim, not merely the general topic.
Check the date for changing information. Look for update information and current wording.
Read the scope. A page about a broad subject may not settle a narrower situation.
Use another reliable source when the answer will guide a real decision. It can help you spot a weak claim.
Use a qualified professional or original record for legal, financial, or health decisions. Do not leave an important choice resting on generated wording.

Ask the companion to restate the claim clearly, separate assumptions from stated facts, and flag what it is unsure about. Those moves can make an answer easier to inspect, but they do not replace the source.

If it corrects itself, do not assume the new answer is right simply because it came later. Check it afresh. A correction gives you a clearer claim to test; it does not remove the need to test it.

What Aiamis says

Aiamis's How It Works page says Ami is set up for friendly, ordinary conversation and never pretends to be a person. The same page says no person reads along or types the replies, and that Ami can state things that are wrong (Aiamis's How It Works page).

It tells readers to check anything that matters with a reliable source or professional (Aiamis's How It Works page). Those limits are worth knowing before you decide how much weight to give a reply.

The simple rule

Use the chat to help you frame the next question, not to make the final decision for you. Ask for clear wording, then take factual claims to a reliable source. If an answer matters, evidence should decide.

A wrong answer can be corrected without turning the whole exchange into a failure. Keep the tone separate from the truth, and keep checking the part you intend to rely on. If you need immediate help, Aiamis's crisis help page lists services run by trained people that you can contact now.