I tried giving ChatGPT summaries of House episodes to test if the conclusions would match

Testing AI Accuracy: Can ChatGPT Correctly Identify TV Show Episodes?

Recently, I embarked on an experiment to evaluate the diagnostic capabilities of ChatGPT by providing it with episode summaries from the medical drama series House. My goal was to see whether the AI could accurately interpret the context and pinpoint the correct diagnosis based solely on the summaries.

To ensure the integrity of the test, I used a different AI tool to generate the episode summaries, reducing the risk that ChatGPT had prior knowledge or influenced the summaries itself. This setup was intended to make the assessment as fair and unbiased as possible.

After feeding ChatGPT the summaries, I asked it to identify the medical condition at the core of each episode. Remarkably, in this particular case, ChatGPT correctly identified the ailment as Leprosy (Hansen’s Disease). I found this result quite impressive, especially considering the complexity of the diagnosis and the AI’s ability to process and interpret the provided information accurately.

For transparency and to evaluate the reliability of its responses, I configured ChatGPT to include a confidence level with each answer. I then ignored the “Confidence: Medium-High” annotations at the end of each statement, focusing instead on the core conclusions. This approach was part of my effort to assess whether the AI’s answers could be trusted without overly relying on self-assessed certainty—a useful method to detect potential hallucinations or inaccuracies.

Overall, this experiment reinforced that advanced language models like ChatGPT can be quite adept at interpreting detailed summaries and arriving at accurate conclusions, even in specialized domains like medical diagnosis—at least within the scope of the information provided.

Keywords: ChatGPT, AI accuracy, House, medical diagnosis, episode summaries, digital diagnostics, AI testing