Version 1
: Received: 18 November 2023 / Approved: 20 November 2023 / Online: 20 November 2023 (05:12:03 CET)
How to cite:
Goga, A.S. Recent developments and Ethics of Artificial Intelligence. Safeguards of ChatGPT4 and BARD. Preprints2023, 2023111211. https://doi.org/10.20944/preprints202311.1211.v1
Goga, A.S. Recent developments and Ethics of Artificial Intelligence. Safeguards of ChatGPT4 and BARD. Preprints 2023, 2023111211. https://doi.org/10.20944/preprints202311.1211.v1
Goga, A.S. Recent developments and Ethics of Artificial Intelligence. Safeguards of ChatGPT4 and BARD. Preprints2023, 2023111211. https://doi.org/10.20944/preprints202311.1211.v1
APA Style
Goga, A.S. (2023). Recent developments and Ethics of Artificial Intelligence. Safeguards of ChatGPT4 and BARD. Preprints. https://doi.org/10.20944/preprints202311.1211.v1
Chicago/Turabian Style
Goga, A.S. 2023 "Recent developments and Ethics of Artificial Intelligence. Safeguards of ChatGPT4 and BARD" Preprints. https://doi.org/10.20944/preprints202311.1211.v1
Abstract
With the rapid advancement of Artificial Intelligence (AI), ensuring ethical safeguards is paramount, especially for powerful Large Language Models (LLMs). This paper delves into the challenges and implications of AI's transformative potential, particularly the risks associated with the generation of harmful content. A comprehensive review of existing ethical guidelines and risk assessment strategies is provided, highlighting notable efforts like the Asilomar AI Principles and the IEEE Ethically Aligned Design guidelines. The novel concept of "indelible ethical frameworks" is introduced, emphasizing the embedding of ethical constructs deep within AI systems to make them resistant to tampering. A critical analysis of this approach is presented, acknowledging its potential while addressing its challenges. The paper also explores the intricacies of ethically programming LLMs, emphasizing the significance of prompt engineering and the handling of unusual prompts. Through a series of witty exposés, the ethical journey of language models is narrated, likening their programming challenges to real-world ethical dilemmas. The piece concludes with proposed methodologies for researching AI safeguards, advocating for both reverse engineering complemented by ethical hacking and longitudinal monitoring with audit trails. These methodologies aim to reinforce the ethical integrity of AI systems, ensuring they are beneficial, transparent, and aligned with societal values..
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.
