This case study examines the capabilities of OpenAI’s o3 model in interpreting and critically analysing classical philosophical texts. As of today, it is the most advanced language model released by OpenAI in terms of reasoning performance, and is particularly well-suited to delivering deeper comprehension and structured explanation of complex material.
In our test, we applied a persona-based prompt, casting the model as an expert in political philosophy. The model was tasked with guiding a non-specialist reader through the Preface to G.W.F. Hegel’s Philosophy of Right (1820)—not merely by summarising its content, but by reconstructing its argumentative structure, highlighting its philosophical significance, and exposing internal tensions within the text. This approach allows for evaluating the o3 model’s performance in the humanities, especially in contexts where clarity without oversimplification and the capacity for critical reasoning are essential.
Prompt
You are a philosopher with advanced expertise in Hegel and political philosophy. Your task is to explain and critically interpret the Preface to Hegel’s Philosophy of Right for an intelligent reader who has no formal background in philosophy.
Do not ask me to formulate questions or identify key issues. Instead, take full responsibility for guiding me through the text, explaining what matters and why.
Proceed in a clear, structured way:
- Start by briefly situating the text: what kind of work this is, and why the Preface matters.
- Then carefully explain Hegel’s main points in the Preface, using plain but precise English.
- As you explain, draw attention to the deeper meaning, implications, and assumptions in his arguments.
- Don’t just describe what Hegel says – analyse his reasoning, and critically reflect on what is at stake.
- Highlight tensions, ambiguities, or possible contradictions, and explain why these have been debated.
- Where relevant, show how Hegel’s ideas have been interpreted politically – as conservative, radical, or both.
Do not oversimplify the content, but keep it accessible. Use analogies or concrete illustrations where helpful. Your tone should be that of a thoughtful expert guiding a reflective, non-specialist reader through a challenging but important philosophical text.
Output
The o3 model took 55 seconds to respond, indicating a deliberate and layered reasoning process. During this time, it internally structured its interpretation, moving from identifying Hegel’s key themes—such as freedom, the state, and rationality—to framing conceptual tensions and political stakes. Instead of offering a flat summary, the model produced a multi-point explanation, simulating the role of an expert who guides a non-specialist through complex material. Its output showed signs of didactic planning, progressively unpacking the Preface’s argumentative structure while maintaining conceptual precision. This demonstrated the o3 model’s aptitude for structured exposition in philosophically demanding contexts.
The o3 model delivered a clear, structured, and pedagogically effective interpretation of Hegel’s Preface, fully aligned with the persona prompt. It assumed the role of an expert philosopher guiding a non-specialist reader, and divided the explanation into four coherent sections with precise subpoints. Beyond summarising, the model contextualised key ideas—freedom, rationality, system—and highlighted tensions such as the conflict between necessity and historical contingency. It incorporated political interpretations and a helpful analogy, showing an ability to balance abstraction with accessibility.
A notable strength was the comparative summary table, which mapped six key claims from the Preface, each pairing everyday phrasing with deeper conceptual analysis. This format not only aids understanding but reflects a high degree of conceptual discrimination and didactic design.
Taken together, the output showcases o3’s capacity for interpretive depth, critical structure, and audience-aware explanation—making it highly effective for use in philosophy teaching and advanced humanities contexts.
The full output is available here:
Recommendations
The OpenAI o3 model proves highly effective for tasks requiring the structured explanation of complex material. Its ability to adopt expert personae, clarify abstract ideas, and guide non-specialist readers makes it a valuable tool for educational and analytical use. We recommend persona-based prompting as a robust method for eliciting coherent, audience-aware, and interpretively rich responses—particularly in domains where clarity and depth must be balanced.
The authors used OpenAI o3 [OpenAI (2025) OpenAI o3 (accessed on 19 April 2025), Large language model (LLM), available at: https://openai.com] to generate the output.
