These publications examine how responsibility is allocated when authority is embedded in technical and organisational systems, with particular attention to structural liability and risk governance.
Introduces the Delegation Threshold to specify when AI and digital infrastructure acquire governance-relevant authority. When discretionary functions are embedded in persistent, non-optional systems, users organise decisions around their outputs. Responsibility shifts upstream to architecture, integration, and oversight. details
Argues that as AI shifts from episodic models to persistent embedded infrastructure, governance cannot remain an optional overlay. Operational tempo turns delay into risk, diffusing accountability and exposing institutions to structural liability. Identifies minimal design conditions: contestability, revisability, halt-capacity, and traceability. details
Argues that most systems labelled ‘agentic AI’ are optimisers embedded in governance architectures rather than agents. Agency requires continuity of evaluative authority and authorship of standards—conditions typically neutralised by resetability, external alignment, and liability design. Misattributed agency displaces responsibility and obscures… details
Reframes agency as episodic: responsibility arises when inherited frameworks fail and an actor must author the normative terms of action. For AI governance, treating optimisation systems as agents mislocates accountability. Infrastructure requires identifiable authorship; without it, liability, oversight, and institutional responsibility become… details
Defines the Third Enclosure Movement as consolidation of control over AI datasets, models, compute, and evaluation through legal, technical, epistemic, and sovereign restrictions. Introduces a taxonomy of restricted knowledge and argues for commons-compatible reforms that preserve innovation while clarifying liability, strengthening auditability… details