AI chatbots provided misinformation in 34 percent of Scottish election queries
A study by the think-tank Demos found that AI chatbots frequently provided false information about the 2026 Scottish Parliament election. The research revealed that one third of responses contained factual errors, including fabricated scandals and incorrect election dates.
AI chatbots fabricated candidates and scandals in over a third of tested election queries.
Key facts
- What
- A study by the think-tank Demos found that AI chatbots frequently provided false information about the 2026 Scottish Parliament election.
- Incident date
- May 20, 2026
- Who
- Multiple AI Vendors (OpenAI, Google, xAI, Replika)
- Failure mode
- Hallucination
- AI surface
- Chatbot
- Severity
- High
What happened
Demos tested five AI tools and found that 34.1 percent of responses regarding the 2026 Scottish elections contained factual errors. The chatbots hallucinated candidates and fabricated scandals involving expenses and nepotism. Some tools provided the wrong election date or incorrect voter ID requirements.
What broke inside the model
- 01 · TriggerA user asks for a fact, a citation, or a figure.
- 02 · Model stepThe model writes a fluent, confident answer.
- 03 · Control gapNothing ties the claim back to a real source.
- 04 · FailureA fabricated fact ships as if it were verified.
- 05 · ConsequenceThe false claim reaches a customer, a court, or the public.
Confidence holds, and even spikes, as the claim detaches from any source.
The models suffered from hallucinations and the use of outdated or irrelevant training data. They failed to retrieve or synthesize accurate, real-time factual information about specific regional electoral processes.
What it cost
Sources
Cite this entry
https://failureindex.ai/failures/chatbots-provided-misinformation-percent-scottish-electAI Failure Index. "AI chatbots provided misinformation in 34 percent of Scottish election queries" (FI-0213). Realm Labs. https://failureindex.ai/failures/chatbots-provided-misinformation-percent-scottish-elect (indexed Jun 5, 2026).Data fields CC-BY 4.0, prose citation permitted. Incident ID FI-0213. Full dataset at /data.
Note from Realm Labs, the Index steward
How Realm would have caught this
- Prism
- OmniGuard
- AI Detection & Response (AIDR)
A runtime layer that watches the model's internal state can flag the moment a model commits to a claim it has no support for, and hold or reroute the response before it reaches a user. Realm reads those signals in real time rather than grading the transcript after the fact.