# Can machines perform a qualitative data analysis? Reading the debate with Alan Turing

arXiv: https://arxiv.org/abs/2512.04121 · HTML: https://mlsanity.com/paper/2512.04121/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 12 of its 46 references that are in the map.
- First posted on arXiv 2 Dec 2025.

## Builds on (most cited first, 12 of 12)

- [Successive Prompting for Decomposing Complex Questions](https://mlsanity.com/paper/2212.04092/) (2022)
- [Supporting Qualitative Analysis with Large Language Models: Combining Codebook with GPT-3 for Deductive Coding](https://mlsanity.com/paper/2304.10548/) (2023)
- [LLM-Assisted Content Analysis: Using Large Language Models to Support Deductive Coding](https://mlsanity.com/paper/2306.14924/) (2023)
- [Using Large Language Models for Qualitative Analysis can Introduce Serious Bias](https://mlsanity.com/paper/2309.17147/) (2023)
- [Large Language Models in Qualitative Research: Uses, Tensions, and Intentions](https://mlsanity.com/paper/2410.07362/) (2024)
- [Applications and Implications of Large Language Models in Qualitative Analysis: A New Frontier for Empirical Software Engineering](https://mlsanity.com/paper/2412.06564/) (2024)
- [Reflections on Inductive Thematic Saturation as a potential metric for measuring the validity of an inductive Thematic Analysis with LLMs](https://mlsanity.com/paper/2401.03239/) (2024)
- [Codebook Reduction and Saturation: Novel observations on Inductive Thematic Saturation for Large Language Models and initial coding in Thematic Analysis](https://mlsanity.com/paper/2503.04859/) (2025)
- [Qualitative Research in an Era of AI: A Pragmatic Approach to Data Analysis, Workflow, and Computation](https://mlsanity.com/paper/2509.12503/) (2025)
- [Generative Artificial Intelligence in Qualitative Research Methods: Between Hype and Risks?](https://mlsanity.com/paper/2511.08461/) (2025)
- [Prompt Engineering for Large Language Model-assisted Inductive Thematic Analysis](https://mlsanity.com/paper/2503.22978/) (2025)
- [TALLMesh: a simple application for performing Thematic Analysis with Large Language Models](https://mlsanity.com/paper/2504.13892/) (2025)

## Abstract (arXiv)

This paper reflects on the literature that rejects the use of Large Language Models (LLMs) in qualitative data analysis. It illustrates through empirical evidence as well as critical reflections why the current critical debate is focusing on the wrong problems. The paper proposes that the focus of researching the use of the LLMs for qualitative analysis is not the method per se, but rather the empirical investigation of an artificial system performing an analysis. The paper builds on the seminal work of Alan Turing and reads the current debate using key ideas from Turing "Computing Machinery and Intelligence". This paper therefore reframes the debate on qualitative analysis with LLMs and states that rather than asking whether machines can perform qualitative analysis in principle, we should ask whether with LLMs we can produce analyses that are sufficiently comparable to human analysts. In the final part the contrary views to performing qualitative analysis with LLMs are analysed using the same writing and rhetorical style that Turing used in his seminal work, to discuss the contrary views to the main question.