How reinforcement learning with human feedback helps ensure that businesses are building ethical generative AI models.
The race to build generative AI is revving up, marked by both the promise of these technologies’ capabilities and the concern about the dangers they could pose if left unchecked.
We are at the beginning of an exponential growth phase for AI. ChatGPT, one of the most popular generative AI applications, has revolutionized how humans interact with machines. This was made possible thanks to reinforcement learning with human feedback (RLHF).
In fact, ChatGPT’s breakthrough was only possible because the model has been taught to align with human values. An aligned model delivers responses that are helpful (the question is answered in an appropriate manner), honest (the answer can be trusted), and harmless (the answer is not biased nor toxic).
This has been possible because OpenAI incorporated a large volume of human feedback into AI models to reinforce good behaviors. Even with human feedback becoming more apparent as a critical part of the AI training process, these models remain far from perfect and concerns about the speed and scale in which generative AI is being taken to market continue to make headlines.Human-in-the-loop more vital than ever
Lessons learned from the early era of the “AI arms race” should serve as a guide for AI practitioners working on generative AI projects everywhere. As more companies develop chatbots and other products powered by generative AI, a human-in-the-loop approach is more vital than ever to ensure alignment and maintain brand integrity by minimizing biases and hallucinations.
Without human feedback by AI training specialists, these models can cause more harm to humanity than good. That leaves AI leaders with a fundamental question: How can we reap the rewards of these breakthrough generative AI applications while ensuring that they are helpful, honest and harmless?
The answer to this question lies in RLHF — especially ongoing, effective human feedback loops to identify misalignment in generative AI models. Before understanding the specific impact that reinforcement learning with human feedback can have on generative AI models, let’s dive into what it actually means.What is reinforcement learning, and what role do humans play?
To understand reinforcement learning, you need to first understand the difference between supervised and unsupervised learning.
