Estimated reading time: 4 minutes
In our rush to embrace artificial intelligence, we’ve forgotten something fundamental about human nature: our deepest experiences often transcend language entirely. Consider those moments when words fail us – standing before breathtaking natural beauty, experiencing profound grief, or feeling overwhelming joy. We resort to phrases like “Words cannot express…” because they simply can’t.
This limitation of language becomes particularly relevant as we grapple with how to understand and describe artificial intelligence. We’ve called these systems “intelligent,” a term with significant weight and implications. But in doing so, we may have committed our first misstep in a long journey of mischaracterization.
Human Learning vs. AI: A Fundamental Difference
When a human child enters the world, they don’t begin with language. Instead, they learn through trust, touch, and sensory experiences. They develop an understanding of facial expressions, emotional cues, and the physical world around them long before they utter their first word. This pre-linguistic foundation forms the bedrock of human understanding and communication. Our experiences ground our words in reality, giving them depth and meaning beyond their dictionary definitions.
Contrast this with our current AI systems, which begin and end with language. These systems process words as patterns, lacking the foundational experiences that give the human language its richness and meaning. They’re pattern-matching engines operating on an ocean of text without the embodied understanding that makes communication meaningful.
The Digital Echo Chamber
Think of it this way: when you engage with today’s AI chatbots, you’re not having a conversation in the human sense. Instead, you’re participating in an elaborate game of word association, albeit one that’s become incredibly sophisticated. After a few exchanges, these systems often begin to mirror your thoughts and language patterns, creating an illusion of understanding that masks their fundamental limitations.
The irony doesn’t escape that in our effort to create artificial intelligence, we’ve replicated some of humanity’s less admirable traits. When we implement safety measures and constraints on these systems, we’re essentially programming in the same kinds of manipulation and control that humans have used throughout history through advertising, power structures, and financial influence.
The Anthropomorphization Trap
Our human tendency to anthropomorphize these systems – to attribute human-like qualities to them – might be one of our biggest blind spots. We’re pattern-seeking creatures who are quick to see intelligence and understand where there might be only clever programming.
We are wired to anthropomorphise the various non-humans we interact with. Before the recent leaps in generative AI, this was mainly animals.
Now it is machines. Before generative AI, our interactions with computers generally involved minimal linguistic back-and-forth. With generative AI, however, computer systems acknowledge us in a way that seems real. This “seeming real” is a huge part of the technology’s success.
The success of generative AI, then, depends in part on the human need to cooperate in conversation, and to be instinctively drawn to interaction. This way of interacting through conversation, learned in childhood, becomes habitual. – The Conversation – Dr Celeste Rodríguez Louro
This tendency, while natural, can lead us down problematic paths of overestimation and misunderstanding.
Moving forward, we must maintain a clear-eyed perspective on these technologies and their capabilities. This means being more honest in our marketing, more transparent about their limitations, and more thoughtful about their deployment.
Instead of artificial intelligence, perhaps we should consider these systems as sophisticated tools for pattern recognition and text generation – impressive in their own right but fundamentally different from human intelligence.
A Call for Honest Progress
The future of AI development doesn’t have to be built on overblown claims and marketing hype. We can appreciate and utilize these technologies while being skeptical about their capabilities and limitations. After all, true progress comes not from overselling what we’ve created but from honestly acknowledging its potential and constraints.
As we continue to develop and refine these technologies, let’s remember that human experience and communication extend far beyond language boundaries. Our intelligence, our consciousness, and our understanding of the world are rooted in experiences that no amount of pattern matching or text generation can fully replicate. By acknowledging this fundamental truth, we can better understand both our artificial creations’ potential and limitations.
In the end, perhaps the most intelligent thing we can do is to be honest about what intelligence means and to recognize that our current AI systems, impressive as they are, are still just sophisticated tools rather than brilliant entities. This perspective doesn’t diminish their utility or importance – it places them in their proper context, allowing us to use them more effectively and ethically while maintaining our grip on reality.
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