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Federico Pigozzi

Tufts University (Levin laboratory)

Integrated information Consciousness is intrinsic causal power, measured as integrated information

Federico Pigozzi is a researcher in Michael Levin’s laboratory at Tufts University whose work gives causal emergence, Erik Hoel’s theory of higher-level causation, its strongest biological and machine-learning applications. His line runs in three connected steps. The 2025 Communications Biology paper with Adam Goldstein and Levin showed that associative conditioning in gene regulatory network models increases integrative causal emergence, evidence that learning-like processes and emergence scales move together. The 2026 preprint “The Causally Emergent Alignment Hypothesis” then proposed that alignment in artificial systems is itself a causally emergent property, examined on this site in the Pigozzi-Levin alignment analysis.

The program reaches in two further directions that matter for this site. With Levin, Pigozzi modeled catalytic networks relevant to the origin of life and found causal architecture rising before self-replicators arrive, covered in the causal emergence before self-replicators analysis. Emergence, on that result, precedes the systems biology usually credited with it. And with Cirrito and Levin, Pigozzi demonstrated AI-guided resetting of memories in gene regulatory network models, an intervention result that treats network memory as an editable, higher-level object.

For the consciousness debate, the position this work defends is that emergence is measurable, trainable, and manipulable rather than a metaphysical label. That aligns with the site’s measurement discipline: if higher-level causal structure can be quantified and shown to grow with learning, then claims about emergent minds inherit a quantity they can be wrong about, in both biological and artificial systems.

Known for. The causally emergent alignment hypothesis, causal emergence in gene regulatory networks, AI-guided memory resetting, causal architecture before self-replicators

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