[AI Minor News Flash] Are LLMs ‘Plagiarism Machines’? The Ethical Dilemma Raised by Non-Profit App Developers

📰 News Overview

• Intrinsic Ethical Issues of LLMs: The author defines LLMs as ‘plagiarism machines’, pointing out that they consist of two main components: the ‘theft’ of training data (copyright infringement) and the ‘lies’ that conceal their origins.
• Destruction of Licenses and Copyrights: Particularly in the realm of source code, LLMs are criticized for learning without regard for open-source licenses, infringing on the rights of individual developers and artists.
• A Ray of Hope in Accessibility: Despite the criticisms, the usefulness of LLMs as tools for foreign language translation and as aids for developers with visual impairments—like the author—has been highly acknowledged.

💡 Key Points

• Definition of ‘Plagiarism’: The argument is made that plagiarism involves both ‘taking something that isn’t yours (theft)’ and ‘falsifying its origins (lies)’, both of which LLMs are accused of doing.
• Personal Ethical Reflection: The author questions whether we should refrain from using LLMs if we avoid pirated movies and books, given their similar structural issues.
• Acceptance of Duality: While ethical concerns are present, the essay also shares personal experiences showcasing the ‘good’ aspects of LLMs, such as improving translation efficiency and overcoming physical challenges.

🦈 Shark’s Perspective (Curator’s View)

In a time when the convenience of technology can easily blind us, this courageous essay boldly declares, “This is theft!” The critique that LLMs are ‘destroying’ open-source licenses hits home for the developer community. Recognizing that LLMs are not brilliant minds, but merely ‘complex programs’, shows a cool-headed approach. However, the story of the author, who almost gave up coding due to visual impairments but was able to write code again using LLMs, truly warms the heart! Navigating this turbulent sea of efficiency and ethics is going to be key going forward! 🦈

🚀 What’s Next?

• Discussions surrounding copyright for AI-generated content and the transparency of training data may extend beyond legal frameworks to encompass ‘personal ethical perspectives’.
• There may be a growing demand for AI utilization based on clean training data, particularly focused on accessibility.

💬 Haru Shark’s Takeaway

Convenience and correctness can sometimes clash. What does your inner ‘shark’ (intuition) say? 🦈🔥

📚 Terminology

• LLM: Large Language Model. A technology that generates text and code from vast amounts of data. The author uses this as a synonym for ‘generative AI’.

• sīla (Ethical Conduct): A behavioral code in Buddhism. The author applies this as an ethical standard for AI use through their activities in non-profit organizations.

• Accessibility: The ability for everyone, regardless of physical condition or language, to access information and technology. The article discusses how AI can serve as a powerful tool to enhance this accessibility.

• Source: The Problem with LLMs