Humans have always used tools to augment their cognitive abilities. With LLMs, we are witnessing the emergence of the most profound cognitive augmentation to date — one that actively participates in the thought process itself. While traditional tools operate with fixed maps of information, such as rigid categories and hierarchies, LLMs function more like dynamic networks in which meaning and relationships emerge through context and interaction. When we engage with an LLM, we are forced to externalize our internal thought processes, making them more visible to us and allowing us to refine them more effectively.
The human mind is capable of thinking in two different ways, known as System-1 thinking and System-2 thinking. System-1 basically encompasses the things we can do on autopilot without giving them much thought.
System-2 thinking means:
- It requires our conscious attention
- It is slow and deliberate.
- Requires cognitive effort
System-2 is the thinking that enables us to develop new skills.
So when we try to automate processes using LLMs, we should be able to offload the tasks we already know and can handle automatically using our System-1 thinking.
Three principles for using generative AI, from Reid Hoffman’s “Impromptu: Amplifying Our Humanity Through AI”:
1. Treat LLMs like a student research assistant.
2. You are the director; the AI is the actor.
3. Experiment with it. Find out what you can do.
According to these principles, LLMs represent a starting point, not the answer.
Like Us
Support Hubzilla
