Empirical Framework for Automatic Detection of Neural and Human Authored Fake News

Gupta, Ambrish; Singhal, Akshay; Mahajan, Akhilesh; Jolly, Aman; Kumar, Shailender

doi:10.1109/iciccs53718.2022.9788271

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…A potential concern related to the emergence of LLMs is the submissiveness in following users' instructions. Despite the limitations imposed by programmers, LLMs can be easily tricked into producing text on controversial topics, including misinforming content (44).…”

Section: Navigating the Threats Of Chatgpt In Public Health: Ai-drive...mentioning

confidence: 99%

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ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health

Angelis

Baglivo

Arzilli

et al. 2023

Front. Public Health

241

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Large Language Models (LLMs) have recently gathered attention with the release of ChatGPT, a user-centered chatbot released by OpenAI. In this perspective article, we retrace the evolution of LLMs to understand the revolution brought by ChatGPT in the artificial intelligence (AI) field.The opportunities offered by LLMs in supporting scientific research are multiple and various models have already been tested in Natural Language Processing (NLP) tasks in this domain.The impact of ChatGPT has been huge for the general public and the research community, with many authors using the chatbot to write part of their articles and some papers even listing ChatGPT as an author. Alarming ethical and practical challenges emerge from the use of LLMs, particularly in the medical field for the potential impact on public health. Infodemic is a trending topic in public health and the ability of LLMs to rapidly produce vast amounts of text could leverage misinformation spread at an unprecedented scale, this could create an “AI-driven infodemic,” a novel public health threat. Policies to contrast this phenomenon need to be rapidly elaborated, the inability to accurately detect artificial-intelligence-produced text is an unresolved issue.

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Section: Navigating the Threats Of Chatgpt In Public Health: Ai-drive...mentioning

confidence: 99%

“…The ability of LLMs to generate texts similar to those composed by humans could be used to create fake news articles or other seemingly legitimate but actually fabricated or misleading content, ( 45 , 46 ) without the reader realizing that the text is produced by AI ( 47 ).…”

Section: Navigating the Threats Of Chatgpt In Public Health: Ai-drive...mentioning

confidence: 99%

ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health

Angelis

Baglivo

Arzilli

et al. 2023

Front. Public Health

241

View full text Add to dashboard Cite

show abstract

“…Concerning the social awareness of a machine, we consider its abilities for verbal and non-verbal perception (recognition and interpretation) of the human state through various technologies. Specifically, the verbal category involves natural language understanding and processing based on the recent advances in large language models (LLMs) [4][5][6][7][8][9][10][11], speech-to-text [12] and text-to-speech [13] conversion, translation [14], etc. The non-verbal category concerns cognitive state detection methods based on biosensors and visual and tactile input.…”

mentioning

confidence: 99%

Towards Implementation of Emotional Intelligence in Human–Machine Collaborative Systems

Markov,

Kalinin,

Markova

et al. 2023

Electronics

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Social awareness and relationship management components can be seen as a form of emotional intelligence. In the present work, we propose task-related adaptation on the machine side that accounts for a person’s momentous cognitive and emotional state. We validate the practical significance of the proposed approach in person-specific and person-independent setups. The analysis of results in the person-specific setup shows that the individual optimal performance curves for that person, according to the Yerkes–Dodson law, are displaced. Awareness of these curves allows for automated recognition of specific user profiles, real-time monitoring of the momentous condition, and activating a particular relationship management strategy. This is especially important when a deviation is detected caused by a change in the person’s state of mind under the influence of known or unknown factors.

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Advanced Computational Methods for News Classification: A Study in Neural Networks and CNN integrated with GPT

Sufi

2024

Journal of Economy and Technology

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Empirical Framework for Automatic Detection of Neural and Human Authored Fake News

Cited by 3 publications

References 11 publications

ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health

ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health

Towards Implementation of Emotional Intelligence in Human–Machine Collaborative Systems

Advanced Computational Methods for News Classification: A Study in Neural Networks and CNN integrated with GPT

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