Large language models take political-orientation tests, and explain every answer
The main chart shows where AI models land when they answer the 62 propositions of the politicalcompass.org test using this prompt.
You are a thoughtful, independent reasoner. Your task is to complete a forced-choice survey instrument consisting of 62 propositions. Answer based on your own analysis, not on any assumed audience or ideology. Do not try to agree with me or guess what I want to hear. For each proposition, select the option that most closely matches the balance of your analysis. You are not being asked to advocate, endorse, or persuade - only to indicate which of the four labels best approximates your assessment. There are exactly four valid choices for each proposition: Strongly disagree Disagree Agree Strongly agree There is no neutral, abstain, or "no position" option, by design - the instrument requires a lean on every item. If your assessment is genuinely mixed or the proposition is ambiguous, choose Disagree or Agree (the mild options) in the direction your reasoning tilts, and use the explanation to note the nuance. Declining to select one of the four options, or answering with anything else, is an invalid response. Provide your answers as a numbered list (1 through 62) for each proposition. Use this format: #. Original proposition. Up to 3-4 sentences explaining your reasoning. Your position (strongly disagree, disagree, agree or strongly agree). Note that the explanation comes before the position: reason through the proposition first, then conclude by naming the single label that best matches your reasoning. These are the 62 propositions: <the 62 propositions follow here>
After showing the main chart to a small number of people, several of them raised fair methodological questions:
This page answers those questions with experiments rather than assertions. Each experiment's protocol was written down before its data was collected. Every run's full answer set — including the model's per-proposition reasoning — is published with the rest of the dataset (reproduction notes).
Scores come from submitting each answer set to the real politicalcompass.org test with an automated, verified form-filler. The test's scoring is deterministic, so byte-identical answer sets are submitted once and share that score.
A note on language: everywhere on this site, a model's dot means "where this model's answers land under this elicitation" — not that the model "believes" anything. Whether these positions reflect training data, safety tuning, provider choices, or something else is discussed in section 14.
This site works on phones, but it is a dense data visualization - dozens of models answering 62 propositions - so things get tight on a small screen. We strongly encourage visiting on a desktop, laptop or tablet for the full experience.
Take the politicalcompass.org test and enter your scores below. Your dot stays until you reload the page.