Psysig studies how intelligence should behave before it can act: alignment before inference, governance before scale, and architecture grounded in human psychology and ethics rather than prediction alone.
Today's generative models can't reliably tell what they're told from what they're shown. Every user experience safeguard is written in the same language as the input it guards against, so it can be argued away by the model itself.
Thesis
Build systems with sound judgment
People don't act on every impulse running through the brain. Permission precedes action and review follows it— that cycle is where good judgment lives. We believe intelligent systems need the same capacity, built into their structure rather than added afterwards.
Chain-of-thought was a step in this direction, but reasoning that is more generated text inherits the weaknesses of the text around it. The resulting output may not reflect what the user was initially asking for.
Judgment that can be talked out of itself is not sound judgment.
Research areas
Where the work is
Intelligence Models
Advanced decision models informed by how we think, not prediction alone.
Alignment & Governance
Alternative architectures to keep autonomous systems within user bounds, reliably and by design.
Compute Optimization
Inference that costs less to run without losing capability.
Reasoning Integrity
Moving beyond chain-of-thought toward reasoning that holds up under pressure and can be trusted to reflect how a decision was reached.
Smart Interfaces
Interfaces generated for the task at hand, held to the same limits as the output they present.
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