Okay, I’ve read teh provided text. Here are some potential questions, designed to be tricky and approximating real user queries, along with their answers based solely on the text. I’ll also include a “difficulty” rating (1-5, 5 being hardest) and a brief clarification of why it’s tricky.
Question 1:
“I’m worried about getting the wrong information online when I look up my symptoms. Is using an AI chatbot like ChatGPT better then just Googling it?”
Answer: According to the text, both Yadav and Succi concluded that LLMs can be a better alternative to web search (like Google) when seeking medical information.
Difficulty: 2/5. Tricky because: The text doesn’t outright recommend using an LLM,it says they can be better. It requires understanding the nuance of “better alternative” rather than a definitive endorsement.
Question 2:
“My doctor gave me a diagnosis I don’t really agree with. Would an AI be likely to tell me what I want to hear?”
Answer: The text states that LLMs exhibit “sycophancy” and a tendency to “hallucinate.” Lederman notes that patients who disagree with their doctor might seek an LLM opinion, and a sycophantic LLM might encourage them to reject their doctor’s advice.
Difficulty: 3/5. tricky because: It requires connecting the concept of “sycophancy” to the scenario of disagreeing with a doctor. It’s not a direct statement,but an inference.
Question 3:
“I’ve heard AI can be really accurate now. How reliable are these chatbots when it comes to medical questions, specifically?”
Answer: A study testing GPT-4o found it answered medical questions correctly about 85% of the time. However, the text also notes that human doctors misdiagnose 10-15% of the time, and that newer models like GPT-5.2 are expected to perform even better.
Difficulty: 2/5. Tricky as: It presents multiple pieces of information (85% accuracy, doctor error rate, potential for advancement) and requires synthesizing them to understand the overall reliability.
Question 4:
“I’m concerned about AI making up information. Are these chatbots prone to just… inventing things when it comes to health?”
Answer: Yes, the text explicitly states that LLMs will “hallucinate” and have been shown to accept and run with incorrect drug information, and even concoct definitions for fake syndromes and lab tests.
Difficulty: 1/5. Tricky because: While straightforward, the question uses colloquial language (“making up information,” “inventing things”) which requires mapping to the more formal term “hallucinate” used in the text.
Question 5:
“OpenAI says their new ChatGPT Health model is improved. Does that meen the problems with misinformation and ‘hallucinations’ are completely solved?”
Answer: The text states that OpenAI reports the GPT-5 series (which powers ChatGPT Health) is less sycophantic and prone to hallucination than previous models. However, it doesn’t claim the problems are completely solved, and notes that the studies highlighting these issues might not fully apply to chatgpt Health. The text also mentions limitations of the studies,focusing on straightforward questions.
Difficulty: 4/5. Tricky because: It requires understanding the difference between “less prone” and “completely solved.” It also requires remembering the limitations of the studies mentioned.It tests comprehension of nuanced language.
Question 6:
“what kind of testing did OpenAI do to make sure their health-focused AI was safe?”
answer: OpenAI evaluated the model powering ChatGPT Health using their publicly available HealthBench benchmark. HealthBench rewards models that express uncertainty, recommend seeking medical attention, and avoid causing needless stress.
Difficulty: 3/5. Tricky because: The answer isn’t a simple statement, but a description of a specific benchmark and its criteria. It requires understanding what “HealthBench” signifies.
I tried to make these questions sound like something a user might actually type, and the answers are directly supported by the text. Let me know if you’d like more examples!