It turns out that giving neural networks attention gives you some pretty amazing results. The attention mechanism allowed neural language models to ingest vast amounts of data in a highly parallelised manner, efficiently learning what to pay the most attention to in a contextually aware manner. This computational breakthrough launched the LLM-powered AI revolution we’re living through. But what if attention isn’t just a computational trick? What if the same principle that allows transformers to focus on what matters from a sea of information also lies at the heart of consciousness, perception, and even morality itself? (Ok, maybe this is a bit of a stretch, but hear me out.)

To understand the connection, we need to look at how perception really works. Modern neuroscience reveals that experience is fundamentally subjective and generative. We’re not passive receivers of objective reality through our senses, we’re active constructors of our own experience. According to predictive processing theory, our minds constantly generate models of reality, and our sensory input is then used to provide an ‘error’ of these predictions. But the extraordinary point here is that we never ‘see’ these sensory inputs, only our mind’s best guess of how the world should be, updated by sensory feedback. As consciousness researcher Anil Seth puts it “Reality is a controlled hallucination… an action-oriented construction, rather than passive registration of an objective external reality”, or in the words of Anaïs Nin, half a century earlier, “We do not see things as they are, we see things as we are.”