‘Data poisoning’ anti-AI theft tools emerge — but are they ethical?

Generative AI models raise concerns about intellectual property (IP) theft due to their ability to scrape content from the internet. To combat this, technologists are developing tools like digital watermarks and data poisoning techniques to protect copyrighted material.

Data poisoning manipulates training data to introduce unexpected behaviors into AI models, creating inaccurate responses and reducing users’ trust in them. In theory, this protects the rights of content creators by encouraging foundation model builders not to scrape any material that might be poisoned.

However, the ethics of using such tools are debatable. While they can help protect IP, they can also be misused to harm AI systems. As the legal landscape evolves to address these issues, companies are exploring ways to ethically use AI while ensuring the protection of intellectual property rights.