Can AI Truly Understand the World Like Living Beings Do

When it comes to navigating the world, living beings and AI systems do so in different ways. This difference lies in something called “sense-making,” or the ability to interpret and assign meaning to experiences. For living organisms, sense-making is a core part of survival, as they constantly evaluate their surroundings in relation to their needs and goals. AI, on the other hand, processes information according to algorithms without any internal sense of purpose or meaning. But can AI ever truly bridge this gap and engage in sense-making in a way that’s similar to life itself. 

Living organisms are constantly making sense of their environment to survive and thrive. Take a small animal in the wild. It senses danger, evaluates whether to run or hide, and seeks food to satisfy hunger. This is not just a passive reaction. It is an active, goal-oriented process. Every aspect of the animal’s perception is tied to its needs, helping it decide what is important and what isn’t. This sense-making is part of what makes life feel meaningful and responsive, as organisms prioritise actions based on the value they assign to different parts of their environment.

AI systems, in contrast, follow rules and patterns. While they can process huge amounts of data and identify patterns, they don’t assign personal or subjective meaning to what they encounter. For instance, a large language model might generate a thoughtful-sounding response, but it doesn’t understand the content or relate it to any personal experience. It’s simply combining language in ways that match what it was trained on, without any internal reference point for “meaning” or “value.”

Some researchers believe that sense-making is what truly sets living beings apart from machines. In this view, true sense-making involves a body that feels, interacts with, and responds to the world with a sense of purpose. Without the ability to prioritise experiences according to internal goals, a machine cannot achieve the kind of subjective, value-laden interpretation that living organisms possess. This lack of purpose is why even the most advanced AI can’t (yet) appreciate, fear, or desire outcomes in the way that a living being does.

Others, however, are exploring ways to make AI systems more “personified,” meaning they would interact with the physical world in ways that could start to resemble sense-making. The idea is that if AI could have a body that requires it to adapt and respond to changing conditions, it might begin to exhibit something like purposeful behaviour. Still, these systems would operate within set parameters defined by machine learning engineers, rather than having personal goals they define themselves. The gap between a reactive machine and a purpose-driven organism remains significant.

Ultimately, the comparison between AI and living beings reveals a fundamental divide: while AI can mimic behaviours that seem like sense-making, it lacks genuine understanding and the ability to assign value in the way that life inherently does. Sense-making in living systems is crucial, shaping their unique experiences and responses to the world. While advancements in AI might bring us closer to machines that exhibit forms of awareness, it remains unclear if they will ever truly engage with their environments as living beings do. Given this gap, achieving Artificial General Intelligence (AGI) - a system with human-like understanding and sense-making - is still uncertain and may be limited by the lack of essential purpose and subjective experience in AI. That said, the definition of AGI itself remains subjective, evolving alongside our understanding of intelligence and consciousness.