Responsible AI
In Part 2 of this book, we covered multiple applications of large language models (LLMs), gathering also a deeper understanding of how many factors could influence their behavior and outputs. In fact, LLMs open the doors to a new set of risks and biases to be taken into account while developing LLM-powered applications, in order to mitigate them with defensive attacks.
In this chapter, we are going to introduce the fundamentals of the discipline behind mitigating the potential harms of LLMs – and AI models in general – which is Responsible AI. We will then move on to the risks associated with LLMs and how to prevent or at least mitigate them using proper techniques. By the end of this chapter, you will have a deeper understanding of how to prevent LLMs from making your application potentially harmful.
We will cover the following key topics:
- What is Responsible AI and why do we need it?
- Responsible AI architecture
- Regulations...