Extended Cognition
The hypothesis that tools and environments can be genuine parts of cognitive processes.
Open →Interface grows out of research traditions in psychometrics, cognitive science, human-AI interaction, automated decision-making, AI governance and knowledge-work design.
Research traditions in cognitive science and human-centred design that ground Interface's augmentation and ergonomics principles.
The hypothesis that tools and environments can be genuine parts of cognitive processes.
Open →How cognitive activity distributes across people, artefacts and environments.
Open →Designing tools and workflows to fit human cognitive capacities and reduce unnecessary load.
Open →How people understand, trust and work alongside AI systems.
Open →Research traditions in psychometrics, measurement theory and assessment design that ground Interface's measurement and validation capabilities.
The theory and practice of measuring psychological attributes through observable responses.
Open →The conditions under which numbers can legitimately represent attributes.
Open →Establishing that measurements and inferences capture what they are intended to capture.
Open →Building assessments from intended inferences backward to evidence design.
Open →Research traditions in AI governance, accountability and assurance that ground Interface's trust and compliance architecture.
Policies and practices for deploying and holding AI systems accountable.
Open →AI systems whose outputs can be understood, audited and justified.
Open →Algorithmic systems that make or inform decisions affecting people, and the governance questions this raises.
Open →Methods for establishing AI systems are safe, reliable and fit for purpose.
Open →Research traditions in data sovereignty, local computing and open systems that ground Interface's deployment and ownership principles.
The principle that people and organisations should control their own data.
Open →Software that prioritises user ownership and avoids cloud dependency.
Open →Architectures designed for interoperability and portability rather than lock-in.
Open →Running AI on infrastructure you control, independent of third-party providers.
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