Ethical and Societal Implications of Large Language Models: Can We Trust Machines With Human Language?

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Author(s): Wasswa Shafik (Dig Connectivity Research Laboratory (DCRLab), Uganda & School of Digital Science, Universiti Brunei Darussalam, Brunei)
Copyright: 2026
Pages: 32
Source title: Theory, Practice, and Future Direction of Large Language Models
Source Author(s)/Editor(s): Ismail Lamaakal (University Mohammed Premier, Morocco), Yassine Maleh (Sultan Moulay Slimane University, Morocco), Khalid El Makkaoui (University Mohammed Premier, Morocco), Ibrahim Ouahbi (University Mohammed Premier, Morocco)and Ahmed Abd El-Latif (Prince Sultan University, Saudi Arabia)
DOI: 10.4018/979-8-3693-8387-2.ch007

Keywords: Artificial Intelligence / Computer Science & IT / Engineering Science Reference / Programming Languages

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Abstract

Large language models (LLMs) are powerful AI tools with broad applications, but they also pose significant ethical and societal challenges. These include risks of inherent bias in training data, leading to biased outputs that may amplify stereotypes or unfair treatment. LLMs raise concerns regarding data privacy, as they may inadvertently use sensitive or personally identifiable information. Additionally, the widespread use of LLMs for generating disinformation poses threats to public trust and information integrity. Addressing these issues requires transparent model development, responsible data use, and strong ethical guidelines to mitigate risks while maximizing the societal benefits of LLMs.

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Ethical and Societal Implications of Large Language Models: Can We Trust Machines With Human Language?

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