The CISR Framework: A Layered, Axiomatic Constraint on Explanations of Consciousness
Rakesh Goswami
PhilPapers (PhilPapers Foundation) December 28, 2015 preprint DOI: 10.5281/zenodo.18072389 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper |
|---|---|
| Key points | Argues that treating functional, cognitive, or neural explanations as explanations of conscious experience is a methodological error rather than an empirical discovery. Proposes the CISR Framework, which separates four explanatory layers—a non-operational experiential ground (C₀), observational experiential registration (I-layer), neural-functional interpretation (R-layer), and optional symbolic or computational representation (S-layer)—with explicit axioms and mapping constraints, aiming to clarify how explanations relate to experience without reducing phenomenology to function or representation. |
Abstract
The CISR Framework is a meta-theoretical and axiomatic approach to one of the most persistent problems in consciousness studies: the confusion between explaining functions and explaining experience. Modern neuroscience, cognitive science, and artificial intelligence have achieved remarkable success in predicting behavior, modeling cognition, and explaining neural mechanisms. Yet these successes are frequently interpreted as explanations of conscious experience itself. The CISR Framework argues that this interpretive leap is not an empirical discovery, but a methodological error. Rather than proposing a new mechanism or metaphysical theory, CISR introduces a disciplined separation between four explanatory layers: a non-operational experiential ground (C₀), observational experiential registration (I-layer), neural –functional interpretation (R-layer), and optional symbolic or computational representation (S-layer). Explicit axioms and mapping constraints clarify what each explanatory practice can—and cannot—legitimately claim. CISR does not attempt to solve the “hard problem” of consciousness. Instead, it reframes the problem by showing why many debates persist despite empirical progress: explanatory success at one level is repeatedly mistaken for sufficiency at another. By enforcing methodological boundaries, CISR preserves the achievements of neuroscience and AI while preventing category errors, reductionist overreach, and unwarranted claims of machine consciousness. The framework is intentionally neutral with respect to metaphysical positions such as physicalism, dualism, or panpsychism. Its contribution lies not in explaining what consciousness is, but in clarifying how explanations relate to experience without collapsing phenomenology into function or representation. CISR is intended as a shared constraint framework—usable across neuroscience, philosophy of mind, and artificial intelligence—where progress is measured by conceptual rigor rather than ontological inflation.