How does human experience factor into generative AI? To answer this, we must first understand the unique nature of human experience, which encompasses our specific interactions and interpretations of life’s events.
Experiential Knowledge: A Human Domain Link to heading
It’s important to recognize that experiential knowledge – knowledge obtained through lived experiences – is uniquely human. As individuals, we construct meaning from our experiences which shapes our understanding of the world around us. We are experts in our own life stories. Can a machine learn this expertise?
AI models are trained on vast amounts of data, encompassing virtually everything that has been written or happened in the past. They excel at generalizing across various subjects based on this data. But can they grasp my individual experiences? My unique interpretation of specific events? This aspect of ’nowness’, the immediacy and uniqueness of personal experience, seems beyond their grasp.
The Attraction to Expertise Link to heading
People are naturally drawn to expertise. When we recognize someone as an expert in a particular field or topic, we trust their insights and value their opinions more highly than those of a novice. This credibility stems not only from theoretical knowledge but also from unique individual experiences that inform their perspective.
Herein lies another challenge for AI: It knows what we as a society have agreed upon as truth - it can draw upon established facts and widely accepted theories - but it doesn’t possess its own unique experiences to lend nuance or innovative viewpoints. Does this mean there will always be a space reserved for human input – for fresh perspectives or alternative ways to perceive things?
The Limitations and Possibilities Link to heading
One could argue that AI is excellent at quantitative research, but does it fall short in qualitative aspects? AI can generate a multitude of possibilities based on its programming, but it can’t test these possibilities in the physical world beyond statistical validation. There seems to be a missing link between AI’s data-driven output and the experiential essence that adds depth to human knowledge.
However, this doesn’t diminish the potential of AI as a tool for humans. We could use it to generate text based on generic data, or even guide it to write from an individual’s perspective. With careful adjustments and revisions, an AI-generated text could reflect human thoughts and ideas. But would the distinction be apparent to readers?
Does this mean that there will always be a boundary separating human cognition from artificial intelligence? Or will we find innovative ways for AI to tap into our individual experiences, creating a symbiotic relationship where machine learning contributes to our understanding while still preserving the uniqueness of human experience? Only time – and continued exploration – will tell.
So let us continue to ponder, explore, and push the boundaries of what is possible with generative AI and its relation to our uniquely human experiences. After all, isn’t that what progress is all about?