Hallucinating Risks: Why AI Translation Needs Validation and Domain Expertise for Medical and Scientific Content

Why Accuracy, Validation, and Domain Expertise Still Matter – Even in an AI-Driven World

Artificial intelligence is transforming how global organizations create, process, and translate content at scale. The technology has already reached all areas of life-science translation, from clinical trial protocols and investigator brochures to IFUs, safety reporting and pharmacovigilance, regulatory submissions, and multilingual patient engagement materials. With every advance comes a new risk and one of the most serious risks in life-science translation with AI is hallucination.

AI hallucinations happen when an LLM confidently generates text that is incorrect, fabricated, inaccurate, misleading, and often wrong, yet does not exist in the source input. It doesn’t “guess,” it synthesizes. The result sounds right, looks right, and is presented as if it is right, even if it is clinically, scientifically, culturally, or linguistically wrong. Hallucinations might be entertaining or harmless for fiction or casual uses, but hallucinations in life sciences and healthcare could lead to catastrophic consequences.

Patient safety, clinical accuracy, regulatory compliance, and scientific integrity should never rely on an estimated or predicted meaning, probability-based language models, or non-traceable, machine-generated output.

What Is AI Hallucination?

AI hallucination is content that an AI system outputs that:

• Does not align with the source text
• Is factually false, logically incorrect, or scientifically inaccurate
• Adds detail or information that was not in the original source
• Appears to be plausible, authoritative, and properly formatted
• Cannot be traced, validated, or QA’ed without human review

Hallucinations are not a bug, they are a feature. In large language models, hallucinations are built into the statistical design. Instead of a factual and verified truth, the model predicts the statistically most-likely output based on its prior data training. This works fine for a chatbot, creative writing, or casual communication. In the life sciences, it fails on the most critical details:

AI hallucinations could:

• Coin new medical terms
• Misinterpret clinical meaning
• Missphrase or re-order essential details
• Infer and insert unknown details rather than leave ambiguity
• Choose a common-meaning over a more precise or scientifically correct one
• Translate via analogy, not validated equivalence

In medical or scientific translation, there is no such thing as “close enough” as accuracy is a life-critical requirement.

Why Hallucinations Happen: A Systemic Design Flaw

AI translation models do not know medical accuracy, they only recognize and generate text patterns. When given ambiguous language or unknown details, they predict the statistically-likely output. Hallucinations are caused by three interrelated reasons:

1. AI Does Not Know, It Predicts

AI translation is not the same as comprehension, reasoning, or subject-matter interpretation. It is probability-based projection.

2. Scientific and Medical Language Is Extremely Specialized

Technical language can mean different things in different domains, molecular biology vs. infectious disease, cardiology vs. oncology, regulatory writing vs. clinical patient-facing communications. Without special focus on the medical field and specialization, AI has to fall back to general-purpose meaning, which is often incorrect.

3. AI Has No Accountability for Accuracy

AI models are not a human, team, company, or brand. There is no risk, liability, accountability, or ethical responsibility for a model. It has no stake in being correct. The humans, the regulators, and the patients are the ones who pay the price, not the AI model.

Real-World Consequences: What Hallucinations Can Cause

Regulatory Non-Compliance

Regulators require output that is traceable, replicable, and validated. Machine hallucinations do not meet those standards, which puts at risk:

• FDA regulatory filings
• EMA and Notified Body submissions
• Safety reporting and pharmacovigilance
• Clinical trial materials
• Labeling and IFUs
• Quality management documentation

Clinical Misinterpretation

Hallucinated verb tenses, dosage readings, or contraindications could lead to:

• Patient misuse
• Investigator misunderstanding
• Protocol misexecution
• Misclassified adverse events
• Trial stakeholder miscommunication

Patient Harm

Patients may:

• Misread and take an incorrect dosage
• Misunderstand contraindications
• Fail to recognize adverse reactions
• Misinterpret risks or warnings
• Misread follow-up instructions

Institutional Liability

Organizations may incur:

• Data integrity investigations
• Market access delays
• Retractions or restudies
• Legal exposure
• Financial loss
• Reputational damage

In short, AI hallucinations are not a productivity risk. They are a patient-safety risk.

Why General-Purpose AI Models Are Especially Prone to Hallucinations

Consumer-grade or public AI engines are not designed for life-science accuracy, which is highly-regulated, scientific, and medical. They are designed for:

• Speed
• Probability-based language synthesis
• Natural language fluency
• Conversational relevance
• Broad general user needs

They are not designed for:

• Controlled scientific terminology
• Device-specific language
• Anatomy, physiology, and biochemistry nuance
• Therapeutic indications and contraindications
• Risk-mitigation regulatory language
• Population-specific cultural interpretation

AI hallucination accuracy may be statistically “good enough” for most of the time, but life sciences demands 100% accuracy, all of the time.

Areas in Translation Where Hallucinations Are Most Likely to Occur

Hallucinations tend to appear in:

• Clinical trial protocols: Invented or re-phrased medical procedural language
• Investigator brochures: Incorrect use of technical terminology
• Patient-facing patient education materials: Over-simplified or re-interpreted language
• IFUs & device labeling: False procedural or safety instructions
• Pharmacovigilance: Misclassified word use
• Manufacturing SOPs: Ambiguous word or phrasing-order
• Regulatory submissions: Incorrect terminology standardization

Hidden in legitimate language, hallucinations are hard to find until they’ve been incorporated into output and may cause harm.

Human-in-the-Loop Is Required: Not Optional

Simply put, the solution is not AI. The solution is Responsible AI. Life-science organizations need to adopt an AI-optimized translation process that includes:

• Secure & controlled AI implementation
• Specialized medical/scientific linguists
• Validation & quality assurance workflows
• Traceable audit trails
• Terminology control and linguistic harmonization
• Compliance-aligned data governance

AI without humans is a tool. AI + Expertise = Trustworthy Translation Output.

Responsible AI Translation: A Step-by-Step Overview

A compliant and reliable translation process should include:

• ISO certified quality management
• Subject-matter expert linguists (not generalist translators)
• Controlled and secure AI systems, not consumer-facing ones
• Human validation and peer review
• Medical-grade terminology harmonization
• Cultural adaptation for population-specific language
• Documentation and version traceability

The difference is not small or incremental, it is transformational.

Language Scientific Approach to AI in Translation

Language Scientific pioneered an AI-optimized, human-validated translation methodology, using medically and scientifically trained linguists through our ASKnetwork™. It includes:

• Secure, controlled, encrypted infrastructure
• NDA-protected translation workflows
• Human-verified scientific and clinical accuracy
• ISO-certified quality management systems
• Documented linguistic traceability
• Subject-matter-specific translator assignments
• No pipeline exposure to public AI engines

This gives our clients the power of the speed, efficiency, and scale of AI without having to sacrifice:

• Scientific or medical meaning
• Regulatory integrity
• Patient safety
• Data privacy
• Institutional and regulatory trust

Final Thoughts: An AI-Optimized, Human-Verified Path Forward

AI has changed what is possible. It has not changed what is acceptable. Clinical research, scientific communication, medical device safety, and patient outcomes should never rely on estimated or predicted meaning, fabricated content, or an approximation based on statistical confidence. Accuracy is a human responsibility and the only safe course is to have AI-optimized translation that is properly secured, responsibly controlled, and human-verified by trained scientific experts.

Words are more than language in life sciences. They are instructions for life-saving or risk-mitigation actions.

If you’re exploring AI translation, or if your current vendor is using AI and you are not sure how, where, or under what safeguards, now is the time to assess your risk posture and elevate your controls.

Language Scientific delivers AI-optimized translation built specifically for high-stakes medical, clinical, pharmaceutical, biotech, and medical device environments, combining secure AI with human subject-matter expertise, ISO-certified validation, and full linguistic accountability.

See how our AI-optimized translation approach works and why leading life-science companies trust us:
Visit our AI Translation page.