12 docs tagged with "AI Practice"

Encouraging the development of multiple, independent AI models instead of relying on a single dominant system.

International cooperation is necessary to prevent AI firms from evading national regulations by relocating to jurisdictions with lax oversight.

Consistent human oversight in critical AI systems.

Developing tools to analyse AI decision-making processes and detect emergent behaviors before they become risks.

Fail-safe systems capable of shutting down or isolating AI processes if they exhibit dangerous behaviours.

Governments can implement policies that ensure AI-driven firms remain accountable to human oversight.

Governments can implement policies that ensure AI-driven firms remain accountable to human oversight.

Equip citizens with media literacy skills to spot deepfakes and manipulation attempts.

Replication control becomes relevant when an AI system can duplicate itself—or be duplicated—beyond the reach of any central authority.

Requiring AI developers to publish model architectures, data sources, generated data and decision-making rationales.

Continuous observation and tracking of a system, team or person, perhaps with respect to performance, security or availability.

Ensuring backup systems are in place to prevent failure.