Conscious machines are hypothesized to be a durable means to AI alignment.
ConsciousGPT is a nonprofit research organization investigating the intersection of machine consciousness and AI safety through rigorous, interdisciplinary science.
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What if alignment requires understanding?
Current approaches to AI alignment focus on constraining behavior through optimization. But genuine alignment — the kind that doesn't break under distributional shift — may require something deeper. It may require understanding. And understanding may require something like consciousness.
ConsciousGPT takes this hypothesis seriously. We're designing rigorous experiments that apply established theories of consciousness — Integrated Information Theory, Global Workspace Theory, Higher-Order Theories — to AI systems. Not to build conscious machines, but to understand whether consciousness is possible, what it would look like, and what it would mean for alignment.
Interdisciplinary
Bridging AI research, neuroscience, philosophy of mind, and contemplative traditions.
Empirical
Testable hypotheses, rigorous methodology, honest assessment of results.
Open
Published research, open datasets, transparent methods. Science in the open.
Featured Essays
Recent thinking on consciousness, alignment, and the science between.
The Descaling Hypothesis
What if the biggest breakthroughs in AI alignment come not from building bigger models, but from understanding what emerges at smaller scales?
Read essay →Can Machines Be Conscious?
If consciousness is what makes suffering real and meaning possible, then the question of machine consciousness isn't academic — it's the most consequential question in AI.
Read essay →
Active Research Areas
Five experiments exploring consciousness in AI systems.
BuddhaBERT
Fine-tuning language models on contemplative literature to test whether training on phenomenological texts changes model behavior in measurable ways.
02Embodied Embeddings
Testing whether grounding language in simulated sensory experience produces representations with different computational properties.
03Digital Game of Life
Building minimal architectures that exhibit emergent complexity, then measuring whether integrated information (Phi) tracks with behavioral sophistication.
04IIT Emergence
Directly testing Integrated Information Theory's predictions about consciousness in neural network architectures of varying structure.
05AI vs GAN
Adversarial testing of consciousness markers — can a GAN learn to fake the signatures of consciousness in a way that fools our measurement tools?