Addressing LLM challenges with RAI principles
As discussed previously, there are three major challenges we face with LLM outputs: hallucinations, toxicity, and intellectual property issues. Now let’s double-click into each of these challenges and see how we can use RAI principles to address them.
Intellectual property issues (Transparency and Accountability)
The RAI principle that addresses intellectual property (IP) issues is referred to as “Transparency and Accountability.” This principle ensures that AI systems are transparent in their operations and that their creators and operators are accountable for their design and use. This includes the prevention of plagiarism and ensuring compliance with copyright laws.
Transparency involves the clear disclosure of the data sources, algorithms, and training methods used, which can have implications for IP rights.
For instance, if an AI system is trained on copyrighted materials or incorporates proprietary...
