Fact Checking With Generative Ai A Systematic Cross Topic Examination

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We are the leading scholarly society concerned with the research and teaching of political science in Europe, headquartered in the UK with a global membership. Our groups and networks are pushing the boundaries of specialist sub-fields of political science, helping to nurture diversity and inclusivity across the discipline. This unique event has helped tens of thousands of scholars over nearly five decades hone research, grow networks and secure publishing contracts. An engaging platform for discussion, debate and thinking; Europe's largest annual gathering of political scientists from across the globe. A comprehensive programme of cutting-edge qualitative and quantitative methodological training delivered by experts. An in-depth breakdown of the research paper "Fact-checking with Generative AI: A Systematic Cross-Topic Examination of LLMs Capacity to Detect Veracity of Political Information" by Elizaveta Kuznetsova, Ilaria Vitulano, et al.

Insights and enterprise applications by OwnYourAI.com. This pivotal study provides a rigorous, large-scale audit of five leading Large Language Models (LLMs)including ChatGPT-4, Google Gemini, and Llama 3 variantsto assess their capability in fact-checking political statements. By testing them against a dataset of over 16,500 claims previously verified by professional journalists, the researchers uncovered critical performance nuances. The key finding is that while LLMs show promise, their performance is "modest" and highly inconsistent. Models are significantly more adept at identifying definitively false statements than they are at validating true information or parsing nuanced, mixed-veracity claims. Crucially, accuracy varies dramatically depending on the subject matter.

Performance is higher for sensitive, high-profile topics like COVID-19 and political controversies, likely due to built-in "guardrails," but falters on complex subjects like economic and fiscal policy. This research underscores a fundamental reality for enterprises: off-the-shelf LLMs are not a reliable, one-size-fits-all solution for automated fact-checking. Achieving dependable accuracy requires strategic model selection, domain-specific fine-tuning, and the development of custom guardrailsa core competency of OwnYourAI.com. The study's strength lies in its systematic "AI auditing" methodology. This approach provides a blueprint for any organization looking to responsibly deploy AI. Instead of relying on vendor claims, they conducted a structured, empirical test to measure real-world performance.

This is the exact process we champion at OwnYourAI.com before deploying any enterprise solution. The study's most direct contribution is a head-to-head comparison of leading LLMs. The results are not about declaring a single "winner," but about understanding the distinct strengths and weaknesses of each architecture. Overall, ChatGPT-4 and Google Gemini led the pack, but even their performance was far from perfect, especially when dealing with statements that weren't definitively false. The F1 score is a measure of a model's accuracy, balancing precision and recall. A score of 1.0 is perfect.

Notice the consistent trend: performance is highest for "False" statements and significantly lower for "True" statements across all models. Received 2024 Jan 24; Accepted 2024 May 15; Collection date 2024. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it... For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. Generative AI (Gen AI), exemplified by ChatGPT, has witnessed a remarkable surge in popularity recently. This cutting-edge technology demonstrates an exceptional ability to produce human-like responses and engage in natural language conversations guided by context-appropriate prompts.

However, its integration into education has become a subject of ongoing debate. This review examines the challenges of using Gen AI like ChatGPT in education and offers effective strategies. To retrieve relevant literature, a search of reputable databases was conducted, resulting in the inclusion of twenty-two publications. Using Atlas.ti, the analysis reflected six primary challenges with plagiarism as the most prevalent issue, closely followed by responsibility and accountability challenges. Concerns were also raised about privacy, data protection, safety, and security risks, as well as discrimination and bias. Additionally, there were challenges about the loss of soft skills and the risks of the digital divide.

To address these challenges, a number of strategies were identified and subjected to critical evaluation to assess their practicality. Most of them were practical and align with the ethical and pedagogical theories. Within the prevalent concepts, “ChatGPT” emerged as the most frequent one, followed by “AI,” “student,” “research,” and “education,” highlighting a growing trend in educational discourse. Moreover, close collaboration was evident among the leading countries, all forming a single cluster, led by the United States. This comprehensive review provides implications, recommendations, and future prospects concerning the use of generative AI in education. Keywords: Gen AI, ChatGPT, Education, Challenges, Solutions, Theory, Authors’ perspective, UNESCO

Artificial Intelligence (AI) refers to the field where machines or computer programs are designed to perform tasks that typically require human intellect, such as language processing, learning, problem-solving, and decision-making (Dalalah & Dalalah, 2023). Within AI, Gen AI constitutes a subset designed to produce new content, such as text, images, audio, or other data formats, often in a creative or human-like fashion. At the forefront of AI research and development stands OpenAI, a research company dedicated to advancing AI technology (Yilmaz & Yilmaz, 2023). Among OpenAI notable achievements is ChatGPT (Yilmaz & Yilmaz, 2023), a prominent member of the generative pre-training transformer (GPT) model family and the largest publicly accessible language model (Dave, Athaluri & Singh, 2023) through...

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