{"id":1333,"date":"2023-07-08T20:44:35","date_gmt":"2023-07-08T20:44:35","guid":{"rendered":"https:\/\/www.iaparabibliotecas.com\/?p=1333"},"modified":"2023-07-19T22:37:06","modified_gmt":"2023-07-19T22:37:06","slug":"leonardo-ai","status":"publish","type":"post","link":"https:\/\/www.iaparabibliotecas.com\/en\/leonardo-ai\/","title":{"rendered":"Unmasking the automaton: detecting texts generated by Artificial Intelligence"},"content":{"rendered":"

Artificial intelligence, particularly with large language models (LLMs), has made significant progress in generating human-like text. As AI-generated text becomes more prevalent in our daily lives, it is essential to develop skills and tools to identify such content. This guide will help you understand what an LLM is (Large Language Model<\/em>) and how it works, to learn some manual detection techniques or automatic tools to detect AI-generated text and, finally, will recommend some key media and information literacy courses to navigate the new era of Artificial Intelligence.<\/p>\n\n\n\n

What is a grand language model and how does it work?<\/h2>\n\n\n\n

A large language model (LLM) is a type of artificial intelligence that can understand, generate, and translate text by learning from large amounts of written content, such as books, websites, articles, and social media posts. Once trained, LLMs can efficiently perform a variety of tasks, such as summarizing articles, answering questions, or even creating new text that sounds as if it was written by a human.<\/strong>. They use a deep learning algorithm, which means they rely on a network that integrates a large number of mathematical functions to mimic the way our brains process information.<\/p>\n\n\n\n

LLMs operate based on probabilities: they learn to recognize patterns and relationships between contexts, words, and phrases in large amounts of data. They create text by selecting the next most likely word or phrase based on their understanding of the context and the words they have already generated.<\/p>\n\n\n\n

Given that LLMs, as GPT-4<\/a>, As AI becomes increasingly sophisticated, it's difficult to determine whether a text is generated by AI or written by humans. Text generated by LLM can be more consistent and less random than human handwriting, making it difficult to identify with absolute certainty. Although tools exist to detect AI-generated text, their detection rates can vary significantly, ranging from 26% to 90% accuracy.<\/strong>. This uncertainty highlights the importance of media and information literacy for humans to responsibly harness the potential of AI-generated content.<\/p>\n\n\n\n

Tips for manual detection of AI texts<\/h2>\n\n\n\n

AI-generated text has unique characteristics that can help distinguish it from human-written content. Some key points are:<\/p>\n\n\n\n

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  1. Check for consistency: <\/strong>It may contain inconsistencies in narrative, tone, or focus. Inconsistencies in genres, pronouns, tenses, and persons may be attributable to AI.<\/li>\n\n\n\n
  2. Analyze fluency:<\/strong> It may be too fluid or lack common human errors, such as typos or colloquialisms. Depending on the writer's level, it's important to expect some common errors, as well as colloquial language.<\/li>\n\n\n\n
  3. Search for repetitions:<\/strong> The author may repeat certain phrases or use similar sentence structures repeatedly. In these cases, it's advisable to review the author's writing history to determine if there are common structures and words they frequently use.<\/li>\n\n\n\n
  4. Examine the consistency:<\/strong> It can lose coherence or context throughout the text, straying from the main topic. Reviewing the main ideas and line of argumentation is key when dealing with more professional texts.<\/li>\n<\/ol>\n\n\n\n

    Automated tools for detecting AI-generated text<\/h2>\n\n\n\n

    Multiple tools and algorithms have been developed to detect AI-generated text, although none have achieved 100% reliability in independent results. Some of the most recognized are:<\/p>\n\n\n\n

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    1. OpenAI AI Classifier<\/a>:<\/strong> This tool analyzes text and assigns confidence levels to determine whether the content is AI-generated or human-written. Detection rates are around 26% with a 9% false positive rate (mistakenly identifying text as AI-generated when it was actually created by a human).<\/li>\n\n\n\n
    2. TurnItIn AI Handwriting Detector<\/a>:<\/strong> This paid tool, soon to be launched by the market leader in anti-plagiarism software, claims to have an accuracy rate of 97% in detecting AI-generated text.<\/li>\n\n\n\n
    3. GPTZero<\/a>It is the most widely used free app. Although it claims effectiveness rates of over 90%, there are no independent studies to support this.<\/li>\n\n\n\n
    4. Originality AI<\/a>:<\/strong> It claims to accurately detect text produced by GPT-3, GPT-3.5, and ChatGPT. It assigns a percentage probability to whether the text was generated by humans or AI. However, it is not perfect, with a success rate of 71%.<\/li>\n\n\n\n
    5. DetectGPT<\/a>Created by professors and academic researchers, it is a model for detecting AI-generated text with GPT-2 (a very old version) that improves detection rates from 81% to 95% in its latest version.<\/li>\n<\/ol>\n\n\n\n

      Keys to continuous learning<\/h2>\n\n\n\n

      Media and information literacy (Media and Information Literacy<\/a> or MIL) is crucial for understanding and evaluating AI-generated content. MIL helps users develop critical thinking skills and promotes the responsible consumption of digital content. Some key MIL skills and courses to help you develop them include:<\/p>\n\n\n\n