Can a large language model accurately solve a university-level microeconomics exercise on health insurance? We tested Manus AI on a multi-part problem involving demand curves, list prices, out-of-pocket prices, and the calculation of social loss under various insurance schemes – including full insurance, coinsurance, and copayment plans. Not only did the
In our earlier posts, we explored how useful existing Custom GPTs are for academic tasks and explained how to create your own GPT from scratch. This follow-up post puts those insights into practice by introducing QuantiCheck—a Custom GPT we developed specifically to assess the methodological rigour and reproducibility of
In our previous blog post, we examined how useful publicly available Custom GPTs are for academic tasks. While many showed promise, especially for brainstorming or outlining, they often fell short in areas where accuracy, source verification, and methodological transparency are crucial. In short: if your work demands high standards of
In this post, we present a straightforward yet revealing task: classifying 25 philosophical and scientific arguments as either deductive or inductive. We tested Mistral Le Chat on this argument classification task to evaluate its ability to distinguish between these fundamental forms of reasoning. Le Chat demonstrated a solid grasp of
Thematic content analysis is a key method in political text interpretation, but it typically requires human judgement to define categories and trace meaning. In this study, we explored whether Grok 3, a state-of-the-art large language model, can carry out this task autonomously—without predefined themes or external guidance. Using Martin
Can a language model accurately classify argumentative claims without any prior examples or fine-tuning? We put DeepSeek-V3 to the test on a real-world stance classification task involving 200 claims from a structured dataset. The model was asked to determine, for each claim, whether it supported (PRO) or opposed (CON) a
Argument mapping is a useful method for visualising the logical structure of reasoning, particularly in complex or multi-step arguments. In this post, we examine how Claude 3.7 Sonnet performs when prompted to identify the structure of arguments and represent them visually. The model was given five tasks, each involving
Can a generative AI model perform critical discourse analysis at a level comparable to a trained scholar? This case study puts OpenAI’s o3 model to the test by asking it to analyse Tony Blair’s 1996 “stakeholder economy” speech—a foundational text in New Labour rhetoric. The model'
Can large language models return accurate results when asked to find real academic texts written by specific philosophers on a specific topic? In this case, the topic was Marxist theory — and the instruction was to list peer-reviewed publications in which Gilles Deleuze or Michel Foucault offer a critique of it.
Can a generative AI model systematically identify and structure philosophical arguments from classic political texts? In this post, we put OpenAI’s o3 model to the test by applying it to a foundational work in early modern political thought: John Locke’s Second Treatise of Government. Focusing on Chapter II
What if philosophy students could go beyond reading about Kant and Hume — and instead step into their minds? What if, instead of summarising the Critique of Pure Reason, they became Hume and challenged Kant directly on causality, synthetic a priori knowledge, or the limits of metaphysics? This blog introduces a
Can a language model reason like a philosopher—not just mimic their tone, but follow and evaluate arguments with analytic precision? To explore this, we designed a two-step prompt experiment using Robert Nozick’s famous “Experience Machine” thought experiment. First, we instructed OpenAI’s o3 model to adopt the persona
