Version 1
: Received: 12 March 2024 / Approved: 12 March 2024 / Online: 13 March 2024 (07:03:07 CET)
How to cite:
Samuel, J.; Khanna, T.; Sundar, S. Fear of Artificial Intelligence? NLP, ML and LLMs Based Discovery of AI-Phobia and Fear Sentiment Propagation by AI News.. Preprints2024, 2024030704. https://doi.org/10.20944/preprints202403.0704.v1
Samuel, J.; Khanna, T.; Sundar, S. Fear of Artificial Intelligence? NLP, ML and LLMs Based Discovery of AI-Phobia and Fear Sentiment Propagation by AI News.. Preprints 2024, 2024030704. https://doi.org/10.20944/preprints202403.0704.v1
Samuel, J.; Khanna, T.; Sundar, S. Fear of Artificial Intelligence? NLP, ML and LLMs Based Discovery of AI-Phobia and Fear Sentiment Propagation by AI News.. Preprints2024, 2024030704. https://doi.org/10.20944/preprints202403.0704.v1
APA Style
Samuel, J., Khanna, T., & Sundar, S. (2024). Fear of Artificial Intelligence? NLP, ML and LLMs Based Discovery of AI-Phobia and Fear Sentiment Propagation by AI News.. Preprints. https://doi.org/10.20944/preprints202403.0704.v1
Chicago/Turabian Style
Samuel, J., Tanya Khanna and Srinivasaraghavan Sundar. 2024 "Fear of Artificial Intelligence? NLP, ML and LLMs Based Discovery of AI-Phobia and Fear Sentiment Propagation by AI News." Preprints. https://doi.org/10.20944/preprints202403.0704.v1
Abstract
Confusion, fear and mixed sentiments prevail in the minds of people towards what is arguably one of the most important of dynamics of modern human society: Artificial Intelligence (AI). This study aims to explore the contributions of news media towards this phenomenon - we analyze nearly seventy thousand recent news headlines on AI, using natural language processing (NLP) informatics methods, machine learning (ML) and large language models (LLMs) to draw insights and discover dominant themes. Our theoretical framework was derived from extant literature which posits the power of fear producing articles and news headlines which produce significant impacts on public behavior even when available in small quantities. We applied extensive textual informatics methods using word and phrase frequency analytics, sentiment analysis and human experts based thematic analysis to discover insights on AI phobia inducing news headlines. Our rigorous analysis of nearly seventy thousand headlines using multiple validation methods in NLP (exploratory informatics including BERT, Llama 2 and Mistral based topic identification), ML (supervised informatics) and LLMs (neural nets for sentiment classification, with BERT, Llama 2 and Mistral) demonstrates the presence of an unreasonable level of emotional negativity and fear inducing verbiage in AI news headlines. The framing of AI as being dangerous or as being an existential threat to humanity can have a profound impact on public perception, and the resulting AI phobia and confusion in public perceptions are inherently detrimental to the science of AI. Furthermore, this can also impact AI policy and regulations, and harm society. We conclude with a discussion deducing implications for society and make recommendations for education and policies that could support human identity and dignity.
Keywords
AI phobia; Artificial Intelligence; AI; natural language processing; large language models; machine learning; topics; sentiment; emotion; fear; risk; threat; news; headlines; ML; NLP; LLMs
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
