Culling Misinformation from Gen AI: Toward Ethical Curation and Refinement

TL;DR

This paper discusses the risks of misinformation and ethical concerns associated with generative AI tools like ChatGPT and deepfakes, proposing guidelines and collaborative efforts to mitigate harm while fostering innovation.

Contribution

It provides an analysis of misinformation issues related to AI, especially ChatGPT and deepfakes, and offers future policy guidelines for ethical AI use and harm reduction.

Findings

AI can spread misinformation across various sectors

Collaboration with law enforcement and developers is crucial

Guidelines can help balance innovation and safety

Abstract

While Artificial Intelligence (AI) is not a new field, recent developments, especially with the release of generative tools like ChatGPT, have brought it to the forefront of the minds of industry workers and academic folk alike. There is currently much talk about AI and its ability to reshape many everyday processes as we know them through automation. It also allows users to expand their ideas by suggesting things they may not have thought of on their own and provides easier access to information. However, not all of the changes this technology will bring or has brought so far are positive; this is why it is extremely important for all modern people to recognize and understand the risks before using these tools and allowing them to cause harm. This work takes a position on better understanding many equity concerns and the spread of misinformation that result from new AI, in this case, specifically ChatGPT and deepfakes, and encouraging collaboration with law enforcement, developers, and users to reduce harm. Considering many academic sources, it warns against these issues, analyzing their cause and impact in fields including healthcare, education, science, academia, retail, and finance. Lastly, we propose a set of future-facing guidelines and policy considerations to solve these issues while still enabling innovation in these fields, this responsibility falling upon users, developers, and government entities.