Glosarium AI
Kamus lengkap Kecerdasan Buatan
Continuous algorithmic auditing
Systematic and ongoing process of evaluating AI algorithms to detect biases, discriminations and ethical drifts throughout their operational lifecycle.
Ethical dashboard
Centralized visualization interface displaying real-time ethical performance metrics and key indicators of an AI system to facilitate decision-making.
Post-deployment monitoring
Set of monitoring mechanisms activated after the deployment of an AI model to ensure the maintenance of initial ethical standards in the face of new data.
Ethical performance indicators
Quantitative metrics specifically designed to measure and track the compliance of an AI system with predefined ethical principles such as fairness and non-discrimination.
Ethical feedback loop
Systematic mechanism allowing users and stakeholders to report ethical concerns and initiate automatic or manual system corrections.
Ethical risk score
Composite index quantifying the probability that an AI system violates established ethical principles, calculated from multiple continuously monitored risk factors.
Ethical drift monitoring
Active surveillance of changes in an AI system's behavior that could compromise its initial ethical guarantees, often due to the evolution of input data.
Ethical traceability log
Immutable register documenting all decisions, actions and modifications affecting the ethical characteristics of an AI system to ensure accountability.
Continuous value validation
Iterative process regularly checking that AI system decisions and predictions remain aligned with the organization's fundamental ethical values.
Early ethical warning system
Proactive mechanism detecting warning signs of potential ethical violations and triggering interventions before damages materialize.
Ethical governance framework
Formal organizational structure defining responsibilities, processes, and tools to ensure consistent and systematic ethical oversight of AI systems.
Dynamic fairness metrics
Adaptive indicators measuring algorithmic fairness in real-time, accounting for contextual and demographic changes to maintain distributive justice.
Ethical compliance control
Systematic checks ensuring that the AI system's operation complies with applicable regulations, internal policies, and ethical standards.
Continuous ethical impact assessment
Periodic and iterative analysis of the ethical consequences of an AI system on individuals and society, enabling proactive adaptation to emerging impacts.
Algorithmic transparency monitoring
Continuous monitoring of the explainability level and documentation of algorithmic decisions to ensure maintained transparency to stakeholders.
Real-time bias dashboard
Specialized interface dynamically displaying measures of algorithmic discrimination and bias to enable immediate detection and correction.
Automatic Remediation System
Autonomous mechanism that automatically corrects ethical deviations detected by the monitoring system, according to predefined rules and intervention thresholds.
Procedural Fairness Tracking
Specific monitoring ensuring that AI decision-making processes respect the principles of consistency, impartiality, and possibility of appeal.
Explainability Monitoring
Continuous surveillance of an AI system's ability to provide comprehensible justifications for its decisions, essential for trust and accountability.
Ethical Responsibility Framework
Formal structure establishing responsibility chains and reporting mechanisms for potential or confirmed ethical violations of AI systems.