Herbert Harris

Is freedom compatible with a causally determined brain? Classical debates oscillate between hard determinism, which treats choices as inevitable products of prior causes, and libertarian views that posit indeterministic gaps in the causal chain. Both sit uncomfortably with contemporary neuroscience: neural activity is exquisitely sensitive to prior learning, context, and feedback, yet there is no evidence for a special, uncaused ingredient that would ground freedom in something not governed by causal laws. We propose that free will is best understood as a socially emergent capacity rooted in second-order active inference. On this view, first-order predictive control over the body and world is necessary but not sufficient for agency in the full sense. A distinctively free agent is one who can model themself as an object of experience through the inferred eyes of others and can use those socially recursive self-models to supervise, select, and revise their own actions. We call this process active intersubjective inference. It elicits information about others' models of the self. This yields socially constructed self-models that represent both how one is seen and how one could be seen under alternative behavioral patterns. The familiar experience that one "could have done otherwise" then reflects access to a counterfactual space of socially constrained self-revisions, rather than a metaphysical breach in causal order. This framework offers a genuinely novel position in the free will debate. Freedom is neither an illusion nor a mysterious exemption from causality, but a real and distinctive capacity that emerges when recursive social self-modeling expands the space of available actions beyond any fixed repertoire.

This paper introduces Active Intersubjective Inference (AISI), a novel framework that integrates psychodynamic theory with predictive processing to explain self-identity construction and psychopathology. AISI posits that the self emerges from recursive inferences about how others perceive us (second-order self), interacting bidirectionally with interoceptive processes. We map psychodynamic phenomena (e.g., transference, projection) onto neurocomputational mechanisms and apply AISI to Major Depressive Disorder (MDD) and Post-Traumatic Stress Disorder (PTSD), highlighting distorted second-order inference as a core dysfunction. Therapeutic implications include psychodynamic therapy, cognitive-behavioral approaches, and psychedelic-assisted treatments to enhance inference flexibility. AISI bridges psychodynamic insights with the NIMH Research Domain Criteria, offering a testable model for precision psychiatry and future clinical trials.

This paper explores the intersection of phenomenology and neuroscience to address foundational questions about consciousness, particularly the nature of qualia—subjective, ineffable contents of experience. Drawing on Thomas Nagel’s seminal inquiry into subjective experience and Husserlian phenomenology, we propose that phenomenological “What is it like?” questions can be integrated with neuroscientific models through predictive error coding (PEC). PEC reconceptualizes the brain as an active inference system, continuously generating and updating predictions about sensory inputs. We introduce the concept of “query acts” to describe the brain’s interrogative engagement with sensory information, linking intentionality in phenomenology with predictive mechanisms in neuroscience. By framing qualia as dynamic processes arising from query acts rather than static entities, we bridge the explanatory gap between subjective experience and objective inquiry. This interdisciplinary framework highlights structural parallels between noetic processes in phenomenology and PEC in neuroscience, providing a novel perspective on the emergence of conscious experience. Additionally, we explore the implications of query acts for clinical interventions in psychiatric disorders and the development of context-sensitive artificial intelligence systems. This synthesis fosters deeper integration of philosophical and scientific approaches to understanding the nature of consciousness.

We propose a non-metaphysical, biologically grounded account of moral sentiment derived from the structure of self-conscious agency. Drawing on Active Intersubjective Inference (AISI), which grounds self-consciousness in socially embedded recursive self-modeling within an active inference architecture, we argue that two core moral sentiments — compassion and responsibility — arise constitutively from the structure of self-consciousness and freedom rather than as evolutionary, cultural, or rational additions to a morally neutral cognitive system. Compassion follows from the underdetermined and interdependent character of personal identity in recursive social self-modeling; responsibility follows from the sense of authorship intrinsic to second-order agency. These sentiments provide guiding principles and motives for ethical choice but rarely determine exact solutions: they function as a compass whose route must be negotiated. We examine alignments and contrasts with major ethical traditions, with particular attention to Rawlsian fairness, which we reinterpret as the natural reasoning of self-conscious agents whose identities are structurally interdependent — everybody, in this sense, already behaves like a Rawlsian. We close by indicating implications for moral psychology, the cultivation and dissemination of virtue, and the social and political conditions of moral agency.

The study of mental illness by the methods of molecular genetics is still in its infancy, but the use of genetic markers in psychiatry may potentially lead to a Virchowian revolution in the conception of mental illness. Genetic markers may define novel clusters of patients having diverse clinical presentations but sharing a common genetic and mechanistic basis. Such clusters may differ radically from the conventional classification schemes of psychiatric illness. However, the reduction of even relatively simple Mendelian phenomena to molecular genetics has been shown to be a surprisingly complex and problematic enterprise. Mental illnesses exist at many levels of including social, environmental, and developmental interactions. Reductionistic shifts in the classification of such a disease entity will have to address the interlevel dynamics that take place within the structure of theories of mental illness. The question of how molecular analysis of psychiatric disease will impact on the structure of existing theories and classification systems is the central topic of this paper