Friston’s Free-Energy Principle and Active Inference

Theoretical neuroscientist Karl Friston conceptualizes consciousness as the natural outcome of his “free-energy principle for action and perception (active inference),” which stresses the primacy of minimizing in all organisms the difference between perceptual expectations (required for homeostasis) and real-time sensory inputs (Friston et al., 2017). In this mechanism, human brains seek to minimize the difference—reduce the “surprise,” as it were—by generating internal models that predict the external world.

Consciousness as Process and Inference

As a physicist and psychiatrist, Friston says: “I find it difficult to engage with conversations about consciousness. My biggest gripe is that the philosophers and cognitive scientists who tend to pose the questions often assume that the mind is a thing, whose existence can be identified by the attributes it has or the purposes it fulfills.”

The deeper question, he asks, is “what sorts of processes give rise to the notion (or illusion) that something exists?” Thus, Friston treats consciousness “as a process to be understood, not as a thing to be defined.” Simply put, his argument is that “consciousness is nothing more and nothing less than a natural process such as evolution or the weather” (Friston, 2017).

Friston's perspective on process leads him to “an elegant, if rather deflationary, story about why the mind exists.” It focuses on “inference,” which Friston characterizes as “actually quite close to a theory of everything—including evolution, consciousness, and life itself.” We are processes, and processes can only reason towards what is “out there” based on “sparse samples of the world”; hence, the criticality of inference. This view, Friston says, “dissolves familiar dialectics between mind and matter, self and world, and representationalism (we depict reality as it is) and emergentism (reality comes into being through our abductive encounters with the world)” (Friston, 2017).

But how did inert matter ever begin the processes that led to consciousness? It starts with complex systems that are self-organizing because they possess “attractors,” which are “cycles of mutually reinforcing states that allow processes to achieve a point of stability, not by losing energy until they stop, but through what's known as dynamic equilibrium. An intuitive example is homeostasis ….” (Friston, 2017).

It's at this point that Friston focuses on inference, “the process of figuring out the best principle or hypothesis that explains the observed states of that system we call ‘the world.’” Every time you have a new experience, he says, “you engage in some kind of inference to try to fit what's happening into a familiar pattern, or to revise your internal states so as to take account of this new fact.”

That's why attractors are so crucial, he stresses, “because an attracting state has a low surprise and high evidence.” A failure to minimize surprise means “the system will decay into surprising, unfamiliar states”—which would threaten its existence. “Attractors are the product of processes engaging in inference to summon themselves into being,” he says. “In other words, attractors are the foundation of what it means to be alive” (Friston, 2017).

Friston applies the same thinking to consciousness and suggests that consciousness must also be a process of inference. “Conscious processing is about inferring the causes of sensory states, and thereby navigating the world to elude surprises … This sort of internalization of the causal structure of the world ‘out there’ reflects the fact that to predict one's own states you must have an internal model of how such sensations are generated” (Friston, 2017).

Learning as well as inference, Friston continues, relies on minimizing the brain's free energy. “Cortical responses can be seen as the brain's attempt to minimize the free energy induced by a stimulus and thereby encode the most likely cause of that stimulus. Similarly, learning emerges from changes in synaptic efficacy that minimize the free energy, averaged over all stimuli encountered” (Friston, 2005).

In short, consciousness is the evolved mechanism for simulating scenarios of the world. It is the internal emergent model that monitors and minimizes the free energy principle, the difference between internal perceptual expectations and real-time sensory input that reflects the external world. Friston proposes that “the mind comes into being when self-evidencing has a temporal thickness or counterfactual depth, which grounds the inferences it can make about the consequences of future actions.” Consciousness, he contends, “is nothing grander than inference about my future” (Friston, 2017).

Markovian Monism and The Beautiful Loop Theory

Friston's consciousness as active inference leads to its metaphysical stamp as “Markovian monism,” which, he says, rests upon the information geometry induced in any system whose internal states can be distinguished from external states—such that “the (intrinsic) information geometry of the probabilistic evolution of internal states and a separate (extrinsic) information geometry of probabilistic beliefs about external states that are parameterized by internal states.” Friston calls these information geometries intrinsic (i.e., mechanical, or state-based) and extrinsic (i.e., Markovian, or belief-based). He suggests the mathematics may help frame the origins of consciousness (Friston et al., 2020).

The Beautiful Loop Theory

In their paper, “A beautiful loop: An active inference theory of consciousness,” neuroscientists Ruben Laukkonen, Karl Friston, and Shamil Chandaria present “a computational theory of consciousness grounded in active inference.” They offer three conditions implying that active inference can model consciousness. They write, “The first condition is the simulation of a world model, which determines what can be known or acted upon; namely, an epistemic field. The second is inferential competition to enter the world model. Only the inferences that coherently reduce long-term uncertainty win, evincing a selection for consciousness that we call Bayesian binding. The third is epistemic depth, which is the recurrent sharing of the Bayesian beliefs throughout the system. Due to this recursive loop in a hierarchical system (such as a brain), the world model contains the knowledge that it exists. This is distinct from self-consciousness, because the world model knows itself non-locally and continuously evidences this knowing (i.e., field-evidencing).”

The model they formally propose is “a hyper-model for precision-control, whose latent states (or parameters) encode and control the overall structure and weighting rules for all layers of inference. These globally integrated preferences for precision enact the epistemic agency and flexibility reminiscent of general intelligence.” The authors claim that their Beautiful Loop Theory is “also deeply revealing about altered states, meditation, and the full spectrum of conscious experience,” including psychedelic experiences and minimal states (Laukkonen, Friston, & Chandaria, 2025).

Several theories of consciousness build on the free-energy paradigm, including Solms's Affect, Carhart-Harris's Entropic Brain and the Projective Consciousness Model.