Concern 109 · Working draft · editorial review in progress
Cross-lingual hallucination
Cross-lingual hallucination concerns unsupported or incorrect AI answers when a task involves different languages or translation between them.
Understanding the concern
Unequal training resources can make some languages harder for a system to handle. Translation may also change a condition or local meaning while leaving the answer fluent enough to appear dependable.
The original entry claimed errors are always more severe in low-resource languages; that needs task-specific evidence. The safer claim is that performance can differ and should be tested by knowledgeable speakers, including checks of sources in the relevant language.
An example
A translated service explanation sounds natural but drops a condition that changes who qualifies.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
- Training
- The process of using examples to shape how an AI model behaves. Learning patterns from material does not establish that the material is true or fair.
- Hallucination
- An AI output that sounds plausible but is false or unsupported, such as an invented source.
Evidence and its limits
Documents resource inequality and confabulation as separate concerns; does not claim a universal cross-language error ranking.
Joshi and colleagues · ACL 2020 · Research study
The State and Fate of Linguistic Diversity and Inclusion in the NLP World ↗ (opens in a new tab)Documents language-resource and research-representation gaps. It does not measure every current language model.
NIST · AI 600-1 · 2024 · Official risk framework
Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile ↗ (opens in a new tab)Describes generative-AI risk categories and management actions; it does not measure the failure rate of every product.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
Has someone checked both the language and the underlying claim in the version users will read?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Humility
Humility means recognizing the limits of our knowledge and being willing to learn from others. Expertise can be valuable without answering every question.
State where evidence is weak, invite criticism, and listen to people with different experience. Leave room to revise a decision when new information appears.
Ask together: What might we be missing, and who could help us see it?
Prudence
Prudence means using careful judgment before and during action. It balances worthwhile opportunities with the need to avoid harm that could have been anticipated.
Start with a limited trial, set stopping points, and prefer choices that can be undone when uncertainty is high. Review what happens rather than assuming the original plan remains sound.
Ask together: What is a careful next step, and when should we stop or change course?
Truthfulness
Truthfulness means making claims that match the evidence and being clear about what we do not know. It includes correcting mistakes rather than protecting a polished story.
Check sources, label guesses, and distinguish a trial result from a proven benefit. If AI helped produce a claim, someone still needs to take responsibility for checking it.
Ask together: What can we honestly say, and what still needs checking?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
About the register and scoring →More ways to explore
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