mlsanityData to 7 Oct 2026

Exploring ChatGPT and its Impact on Society

arXiv 2403.14643 ↗First posted 21 Feb 2024cs.CY cs.AI cs.CLcited by 6

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Abstract (arXiv)

Artificial intelligence has been around for a while, but suddenly it has received more attention than ever before. Thanks to innovations from companies like Google, Microsoft, Meta, and other major brands in technology. OpenAI, though, has triggered the button with its ground-breaking invention ChatGPT. ChatGPT is a Large Language Model (LLM) based on Transformer architecture that has the ability to generate human-like responses in a conversational context. It uses deep learning algorithms to generate natural language responses to input text. Its large number of parameters, contextual generation, and open-domain training make it a versatile and effective tool for a wide range of applications, from chatbots to customer service to language translation. It has the potential to revolutionize various industries and transform the way we interact with technology. However, the use of ChatGPT has also raised several concerns, including ethical, social, and employment challenges, which must be carefully considered to ensure the responsible use of this technology. The article provides an overview of ChatGPT, delving into its architecture and training process. It highlights the potential impacts of ChatGPT on the society. In this paper, we suggest some approaches involving technology, regulation, education, and ethics in an effort to maximize ChatGPT's benefits while minimizing its negative impacts. This study is expected to contribute to a greater understanding of ChatGPT and aid in predicting the potential changes it may bring about.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 20 of its 90 references that are in the map. First posted on arXiv 21 Feb 2024.

Builds on

20 of 90 references.

References · 20

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8 more
  1. 2023ChatGPT: Jack of all trades, master of nonecited by 204
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  3. 2023Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Modelscited by 144
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 3; 2026: 1.

6 papers.