Five ethical principles for generative AI in scientific research
- URL: http://arxiv.org/abs/2401.15284v2
- Date: Mon, 12 Feb 2024 05:11:56 GMT
- Title: Five ethical principles for generative AI in scientific research
- Authors: Zhicheng Lin
- Abstract summary: Generative artificial intelligence tools are rapidly transforming academic research and real world applications.
This paper offers an initial framework by developing analyses and mitigation strategies across five key themes.
We argue that global consensus coupled with professional training and reasonable enforcement are critical to promoting the benefits of AI while safeguarding research integrity.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Generative artificial intelligence tools like large language models are
rapidly transforming academic research and real world applications. However,
discussions on ethical guidelines for generative AI in science remain
fragmented, underscoring the urgent need for consensus based standards. This
paper offers an initial framework by developing analyses and mitigation
strategies across five key themes: understanding model limitations regarding
truthfulness and bias; respecting privacy, confidentiality, and copyright;
avoiding plagiarism and policy violations when incorporating model output;
ensuring applications provide overall benefit; and using AI transparently and
reproducibly. Common scenarios are outlined to demonstrate potential ethical
violations. We argue that global consensus coupled with professional training
and reasonable enforcement are critical to promoting the benefits of AI while
safeguarding research integrity.
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