# Think Fast, Think Slow, Think Critical: Designing an Automated Propaganda Detection Tool

arXiv: https://arxiv.org/abs/2402.19135 · HTML: https://mlsanity.com/paper/2402.19135/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 86 references that are in the map.
- First posted on arXiv 29 Feb 2024.

## Builds on (most cited first, 19 of 19)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity](https://mlsanity.com/paper/2302.04023/) (2023)
- [From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models](https://mlsanity.com/paper/2305.08283/) (2023)
- [Fine-Grained Analysis of Propaganda in News Articles](https://mlsanity.com/paper/1910.02517/) (2019)
- [Explanations Can Reduce Overreliance on AI Systems During Decision-Making](https://mlsanity.com/paper/2212.06823/) (2022)
- [SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles](https://mlsanity.com/paper/2009.02696/) (2020)
- [A Survey on Computational Propaganda Detection](https://mlsanity.com/paper/2007.08024/) (2020)
- [Detecting Propaganda Techniques in Memes](https://mlsanity.com/paper/2109.08013/) (2021)
- [Prta: A System to Support the Analysis of Propaganda Techniques in the News](https://mlsanity.com/paper/2005.05854/) (2020)
- [Detecting Fake News Using Machine Learning : A Systematic Literature Review](https://mlsanity.com/paper/2102.04458/) (2021)
- [Interpretable Propaganda Detection in News Articles](https://mlsanity.com/paper/2108.12802/) (2021)
- [Examining the Impact of Provenance-Enabled Media on Trust and Accuracy Perceptions](https://mlsanity.com/paper/2303.12118/) (2023)
- [Exploring Lightweight Interventions at Posting Time to Reduce the Sharing of Misinformation on Social Media](https://mlsanity.com/paper/2101.11824/) (2021)
- [Large Language Models for Propaganda Detection](https://mlsanity.com/paper/2310.06422/) (2023)
- [User Perceptions of Automatic Fake News Detection: Can Algorithms Fight Online Misinformation?](https://mlsanity.com/paper/2304.07926/) (2023)
- [Trustworthy Misinformation Mitigation with Soft Information Nudging](https://mlsanity.com/paper/1911.05825/) (2019)

## Built on by (most cited first, 10 of 10)

- [SPHERE: An Evaluation Card for Human-AI Systems](https://mlsanity.com/paper/2504.07971/) (2025)
- [PropXplain: Can LLMs Enable Explainable Propaganda Detection?](https://mlsanity.com/paper/2502.16550/) (2025)
- [Iffy-Or-Not: Extending the Web to Support the Critical Evaluation of Fallacious Texts](https://mlsanity.com/paper/2503.14412/) (2025)
- [Effective Yet Ephemeral Propaganda Defense: There Needs to Be More than One-Shot Inoculation to Enhance Critical Thinking](https://mlsanity.com/paper/2503.16497/) (2025)
- [Learning Deliberately, Acting Intuitively: Unlocking Test-Time Reasoning in Multimodal LLMs](https://mlsanity.com/paper/2507.06999/) (2025)
- [NativQA Framework: Enabling LLMs and VLMs with Native, Local, and Everyday Knowledge](https://mlsanity.com/paper/2504.05995/) (2025)
- [Biased by Design: Leveraging AI Biases to Enhance Critical Thinking of News Readers](https://mlsanity.com/paper/2504.14522/) (2025)
- [Proactive Defense: Compound AI for Detecting Persuasion Attacks and Measuring Inoculation Effectiveness](https://mlsanity.com/paper/2511.21749/) (2025)
- [ProBel: Propaganda Detection with Techniques, Spans, and Explanations](https://mlsanity.com/paper/2608.22388/) (2026)
- [Reasoning for Propaganda Detection via Label-Guided CoT Optimisation](https://mlsanity.com/paper/2610.17271/) (2026)

## Abstract (arXiv)

In today's digital age, characterized by rapid news consumption and increasing vulnerability to propaganda, fostering citizens' critical thinking is crucial for stable democracies. This paper introduces the design of ClarifAI, a novel automated propaganda detection tool designed to nudge readers towards more critical news consumption by activating the analytical mode of thinking, following Kahneman's dual-system theory of cognition. Using Large Language Models, ClarifAI detects propaganda in news articles and provides context-rich explanations, enhancing users' understanding and critical thinking. Our contribution is threefold: first, we propose the design of ClarifAI; second, in an online experiment, we demonstrate that this design effectively encourages news readers to engage in more critical reading; and third, we emphasize the value of explanations for fostering critical thinking. The study thus offers both a practical tool and useful design knowledge for mitigating propaganda in digital news.