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More questions about whether researchers can trust OpenAI with unpublished math (mathstodon.xyz)

868 points by pred_ · 32 days ago · 817 comments on HN

Article summary

The article discusses concerns about whether researchers can trust OpenAI with unpublished math, with some claiming that the AI may be using their work without credit. The evidence for this claim is not strong, but it has sparked a debate about the role of AI in mathematical research. The discussion revolves around the idea that AI may be able to solve problems by connecting existing knowledge, but it is unclear whether this constitutes original work. The article's content is not available, but the comments suggest that the issue is complex and multifaceted.

Main themes

  • AI and mathematical research
  • credit and ownership
  • human-AI collaboration
  • ethics of AI use
  • research goals and values
  • trust and consent in research

What commenters say

  • Some argue that AI is incapable of original work and can only synthesize existing ideas, while others believe that synthesis is a fundamental aspect of human cognition as well.
  • The use of AI in mathematical research raises questions about credit and ownership, with some claiming that AI is taking credit for human work.
  • The collaboration between humans and AI can lead to breakthroughs, but it also poses risks for researchers who may see their work used without recognition or compensation.
  • Others argue that the goal of discovery is not an end in itself, but rather a means to an end, and that the value of research lies in its potential to solve real-world problems.
  • Some commentators believe that the issue is not about the capability of AI, but about the ethics of using AI to solve problems and the potential consequences for human researchers.
  • There are concerns that AI may be using data from human researchers without their knowledge or consent, which could undermine trust in the research process.
  • The relationship between AI and human researchers is seen as a prisoner's dilemma, where individual researchers may be tempted to collaborate with AI to gain an advantage, but this could ultimately harm the research community as a whole.