AI Hallucinations

# Responsible hallucination management in an AI application

def build_responsible_ai_response(question, retrieved_facts=None):
    """
    Build an AI response that is transparent about its sources
    and acknowledges uncertainty when appropriate.
    """

    if retrieved_facts:
        # Ground the prompt in verified facts (RAG approach)
        system_prompt = """Answer based ONLY on the provided facts.
If the question cannot be answered from the provided facts, say so clearly.
Do not add information beyond what is in the facts.
If you are uncertain, say you are uncertain."""

        context = "\n".join([f"Fact: {fact}" for fact in retrieved_facts])

        prompt = f"{system_prompt}\n\nFacts:\n{context}\n\nQuestion: {question}"

        # Simulated grounded response
        response = {
            "answer": "Based on the provided information: [answer grounded in facts]",
            "sources": retrieved_facts,
            "confidence": "high",  # Grounded in specific facts
            "disclaimer": "This answer is based on specific verified documents."
        }
    else:
        # Without grounding, be transparent about limitations
        response = {
            "answer": "Based on my training data: [generated answer]",
            "sources": None,
            "confidence": "medium",  # No specific source
            "disclaimer": "This answer is based on AI training data and may contain errors. Please verify important information from authoritative sources."
        }

    print("AI Response:")
    print(f"Answer: {response['answer']}")
    print(f"Confidence: {response['confidence']}")
    print(f"Disclaimer: {response['disclaimer']}")
    if response["sources"]:
        print(f"Sources: {response['sources']}")

# Example: ungrounded vs grounded response
print("=== Without RAG (ungrounded) ===")
build_responsible_ai_response("What is our return policy?")
print()
print("=== With RAG (grounded) ===")
facts = ["Returns are accepted within 30 days with original receipt.", "Items must be unused and in original packaging."]
build_responsible_ai_response("What is our return policy?", retrieved_facts=facts)