How to use GenAI to fact-check a text for disinformation and fake news

Disinformation and fake news are serious problems in today’s world, and they can have negative impacts on society, politics, and public health. Detecting and debunking them can be challenging, especially when they are spread through social media and other online platforms.

Fortunately, there is a way to use GenAI, a powerful generative AI tool, to fact-check a text for disinformation and fake news. In this article, we will show you how to do that, using the best prompt and model for this task and some examples from real-world data.

What is GenAI and how does it work?

GenAI is a generative AI tool that can create various types of content, such as text, images, code, music, and more, based on a given prompt. A prompt is a short text that specifies what kind of content you want GenAI to generate. For example, if you want GenAI to write a poem about love, you can give it a prompt like “Write a poem about love”. GenAI will then use its internal knowledge and creativity to generate a poem that matches your prompt.

GenAI works by using large language models (LLMs), which are deep learning models that can process natural language (any language used by humans) and generate text that is similar in style and content to human-generated text. LLMs are trained on massive amounts of unlabelled text data from various sources, such as books, websites, social media posts, etc. This allows them to learn the patterns and rules of natural language, as well as the common topics and themes that humans write about.

One of the advantages of LLMs is that they can be fine-tuned for specific tasks and domains, using a technique called transfer learning. Transfer learning means that instead of training a model from scratch, you can use a pre-trained model and adapt it to your specific needs by providing some labelled data (data with correct answers or outputs). For example, if you want to use an LLM for sentiment analysis (detecting the emotion or attitude of a text), you can fine-tune it with some texts that have labels such as positive, negative, or neutral.

How to use GenAI to fact-check a text for disinformation and fake news?

One of the tasks that you can use GenAI for is fact-checking a text for disinformation and fake news. Disinformation and fake news are false or misleading information that are intentionally or unintentionally spread to deceive or influence people. Fact-checking means verifying the accuracy and credibility of the information by comparing it with reliable sources and evidence.

To use GenAI to fact-check a text for disinformation and fake news, you need to provide it with two things: a prompt and a model. A prompt is a short text that tells GenAI what you want it to do. A model is an LLM that has been fine-tuned for the task of fact-checking. Here are some examples of prompts and models that you can use:

• Prompt: Given a short text <text_to_check>, check whether there are some facts stated in the text that are NOT true. Report which parts of the text are not true and provide evidence or sources to support your claim.
• Model: Chain-of-Verification (CoVe), which is an LLM that uses a four-step process to fact-check its own draft response: (i) draft an initial response; (ii) plan verification questions to check its draft; (iii) answer those questions independently; (iv) generate its final verified response.
• Prompt: Given a short text <text_to_check>, classify it as either true or false. If false, explain why it is false and provide evidence or sources to support your claim.
• Model: RoBERTa, which is an LLM that has been fine-tuned on several large-scale datasets for natural language understanding tasks, such as natural language inference (determining whether one sentence entails or contradicts another sentence) and semantic similarity (measuring how similar two sentences are in meaning).
• Prompt: Given a short text <text_to_check>, rate its credibility on a scale from 1 (very low) to 5 (very high). Provide reasons for your rating and evidence or sources to support your claim.
• Model: ESIM+GloVe, which is an LLM that combines two models: ESIM (Enhanced Sequential Inference Model), which uses recurrent neural networks (RNNs) to encode sentences and infer their relationship; and GloVe (Global Vectors for Word Representation), which uses word embeddings (numeric representations of words) to capture semantic and syntactic information.

How to use the prompt and model effectively?

To use the prompt and model effectively, you need to follow some guidelines and best practices. Here are some tips to help you:

• Choose a prompt and a model that are suitable for your specific goal and data. For example, if you want to check the factual accuracy of a text, you might want to use the CoVe model, which can generate verification questions and answers. If you want to check the overall credibility of a text, you might want to use the ESIM+GloVe model, which can provide a rating and reasons.
• Provide a clear and concise prompt that specifies what you want GenAI to do. For example, if you want GenAI to check whether there are some facts stated in the text that are NOT true, you can use a prompt like “Given a short text <text_to_check>, check whether there are some facts stated in the text that are NOT true.” Avoid using vague or ambiguous terms that might confuse GenAI or lead to unwanted results.
• Provide a short and relevant text to check. For example, if you want to check a news article for disinformation and fake news, you can provide the headline and the first paragraph of the article as the text to check. Avoid providing too long or too short texts that might make it difficult for GenAI to process or generate a meaningful response.
• Evaluate the response generated by GenAI carefully and critically. For example, if GenAI reports that some parts of the text are not true, you should check the evidence or sources that it provides and verify them with other reliable sources. If GenAI classifies or rates the text as true or false, or high or low in credibility, you should consider the reasons and evidence that it provides and compare them with other criteria or indicators of credibility. Do not blindly trust or accept the response generated by GenAI without further verification or validation.

Frequently Asked Questions (FAQs)

Question: What is GenAI?

Answer: GenAI is a generative AI tool that can create various types of content, such as text, images, code, music, and more, based on a given prompt.

Question: What is natural language processing (NLP)?

Answer: NLP is a branch of artificial intelligence that deals with the analysis and generation of natural language (any language used by humans).

Question: What are large language models (LLMs)?

Answer: LLMs are deep learning models that can process natural language and generate text that is similar in style and content to human-generated text.

Question: How can I use GenAI to fact-check a text for disinformation and fake news?

Answer: You can use GenAI to fact-check a text for disinformation and fake news by providing it with two things: a prompt and a model. A prompt is a short text that tells GenAI what you want it to do. A model is an LLM that has been fine-tuned for the task of fact-checking.

Question: What are some examples of prompts and models that I can use?

Answer: Some examples of prompts and models that you can use are:

• Prompt: Given a short text <text_to_check>, check whether there are some facts stated in the text that are NOT true. Report which parts of the text are not true and provide evidence or sources to support your claim.
• Model: Chain-of-Verification (CoVe), which is an LLM that uses a four-step process to fact-check its own draft response.
• Prompt: Given a short text <text_to_check>, classify it as either true or false. If false, explain why it is false and provide evidence or sources to support your claim.
• Model: RoBERTa, which is an LLM that has been fine-tuned on several large-scale datasets for natural language understanding tasks.
• Prompt: Given a short text <text_to_check>, rate its credibility on a scale from 1 (very low) to 5 (very high). Provide reasons for your rating and evidence or sources to support your claim.
• Model: ESIM+GloVe, which is an LLM that combines two models: ESIM, which uses RNNs to encode sentences and infer their relationship; and GloVe, which uses word embeddings to capture semantic and syntactic information.

Summary

In this article, we have shown you how to use GenAI, a powerful generative AI tool, to fact-check a text for disinformation and fake news. We have explained what GenAI is and how it works, how to choose the best prompt and model for this task, and how to use them effectively. We have also provided some FAQs related to this topic. We hope that this article has been helpful and informative for you. If you have any questions or feedback, please feel free to contact us.