Recently, I was using Visual Studio Copilot while learning from Corey Schafer’s videos, and I noticed something concerning. The autocomplete suggestions were identical to the tutorial—down to every variable name and value. Yet, Copilot doesn’t credit Corey, who invested time, money, and effort into creating those videos. What’s worse is that the AI is essentially using his hard work for free and could even profit from it by charging me a monthly subscription fee later!
This issue reminded me of a broader problem I came across recently—AI training data being scraped from platforms like LibGen and Sci-Hub. Not only does this violate copyright laws, but it also completely disregards crediting the original creators. It’s troubling to think that their work is being used, repackaged, and sold without them receiving any recognition or benefits.
If you’re a well-known researcher in your field, chances are your work is being used freely by these models. Ironically, AI systems trained on such data could eventually replace the very people who contributed to this knowledge base—especially in fields like programming.
Copyright laws and patenting have long been drivers of innovation. They gave creators and researchers the motivation to invest their time and resources, knowing they’d be rewarded. But now, major corporations are mining vast amounts of information from the internet without giving anything back to society. In the near future, what incentive will a scientist or creator have to innovate when they know an advanced AI model might freely use their work, improve upon it, and profit without sharing the rewards?
For example, when I watch Corey Schafer’s videos on YouTube, he earns a small amount of money. I can also recommend his content to friends, bringing him more viewers and, in turn, more revenue. This gives Corey motivation to create more high-quality content. However, if an AI uses even a single piece of his information, it should also compensate him—just like YouTube does. Otherwise, this system will eventually demotivate creators, scientists, and the entire tech community, leading to a collapse of innovation.
What are your thoughts on this?
Completely agree with you on this. Data compliance is an important aspect in AI model development and training. Mostly, getting right data availability is the critical task in AI model lifecycle and needs to be classified as public or private data. There needs to be a global policy on how to use the datasets and provide due benefit to the data owners.
The concern you've raised highlights a critical ethical and legal challenge in the AI and tech landscape. I completely agree that creators and researchers should be fairly credited and compensated for their contributions. Although I'm not a legal expert, I believe that training AI models on copyrighted or proprietary data without adequate consent definitely violates the principles of intellectual property. In my opinion, I think AI models should integrate mechanisms that uphold data ownership, transparency, and accountability to avoid any misuse or unfair exploitation of creators' works. This approach will ultimately uphold trust, fairness, and continuous innovation.
It’s time to extend the FAIR Principles of data sharing
"Research into pressing societal challenges increasingly depends on data coming from across different disciplines and research contexts. Gordon Blair argues that to create a research culture that makes the best use of available data, the 2016 FAIR principles need to be extended in ways that address issues that have emerged in the decade following their creation...
From addressing climate change to ensuring food security, the world’s grand challenges demand a more united, data-driven response that rises above disciplinary silos and individual priorities. This would ensure the future of science is not only FAIR but truly fit for purpose..."
https://blogs.lse.ac.uk/impactofsocialsciences/2025/01/22/its-time-to-extend-the-fair-principles-of-data-sharing/
- Badges
- Science topic
- Similar topics
- Filing