If a tree falls in the forest and no one is around to hear it, does it make a sound? This classic riddle has puzzled minds for ages, but it’s more than just a quirky brain teaser. At its core, it’s about presence, perception, and whether something unobserved really counts.
This question is surprisingly relevant to the world of AI. When it comes to large language models (LLMs) like ChatGPT, it seems they only “hear” the trees that have fallen in front of an audience – those lives and experiences that have been published, documented, or otherwise shared with the world. But what about the vast forest of unheard stories and unwritten experiences? Most human lives aren’t captured in books or online articles, yet they’re rich with unique perspectives, wisdom, and personal history. Without these stories, AI is missing a huge piece of what it means to be human.
The Missing Majority in AI Training
LLMs rely on immense datasets built from what’s available in print and online. Curators choose sources from a wide variety of books, articles, webpages, and research papers, aiming to create a well-rounded representation of human knowledge. However, the reality is that most people’s stories and experiences are never published. They’re lived quietly, passed down through oral traditions, or kept within personal memories. And this creates a gap in AI’s understanding, one that may affect its ability to connect with and reflect real human experiences.
Can Published Work Really Capture All of Humanity?
Some may argue that published books and research can act as stand-ins for broader humanity. These published works are undeniably valuable, but they’re just a sliver of the full picture. They come from those who had the opportunity or resources to record their thoughts – often leaving behind the lives and voices of those who never found a place on a page. Ordinary people with extraordinary stories, unique insights, and untold perspectives don’t make it into these datasets, so LLMs learn without the invaluable knowledge these people hold.
A Surprising Opportunity: Capturing Every Story
At Voice of Reason AI, we’ve encountered this gap firsthand. While working on tools to support memory and social interaction, especially for people with early-stage dementia, we saw an unexpected opportunity. As part of helping people preserve their memories, we realized we could also create a more inclusive form of knowledge. By using AI to document the life stories of our users, we’re building written biographies for people who might otherwise go unheard.
Imagine if AI had access to these stories – not just the lives of published authors but of ordinary individuals. AI could draw from a richer pool of human experience, learning not only from those whose stories have reached the public but from people who’ve lived through challenges, found creative solutions, and navigated unique lives without ever writing a book or publishing an article.
Building a More Complete Human Story
This system, starting with users who have memory challenges, captures life experiences that might otherwise be lost. For individuals dealing with early-stage dementia, it offers a way to remember and share with loved ones. But it also plants the seed for something more. These stories, captured and stored, could one day be part of a new wave of knowledge – helping LLMs develop a broader understanding of human life, empathy, and common experiences.
The Future: An AI That Knows Us All
So what if AI could learn from the “forest” of all human experience, not just the “trees” that happened to fall within view? With access to life stories from people all around the world, AI would have a much more diverse foundation. It could interact with a better understanding of everyday lives, sharing deeper insights and relating in ways we haven’t yet imagined.
At Voice of Reason AI, we’re excited to see how capturing life stories can add to this future. Because when it comes to the richness of human experience, everyone’s story deserves to be heard – whether it’s recorded or not. We’re here to help AI listen, even when no one else is around to hear the tree fall.