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Glossario IA

Il dizionario completo dell'Intelligenza Artificiale

162
categorie
2.032
sottocategorie
23.060
termini
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Ethical Impact Assessment (EIA)

Systematic methodology for identifying, evaluating, and mitigating the potential ethical consequences of an AI system before and during its deployment.

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Impact Assessment

Structured process of systematically analyzing the potential and actual effects of an AI technology on individuals and society.

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Ethical Risk Assessment

Systematic identification of potential ethical threats and assessment of their likelihood of occurrence and severity.

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Algorithmic Fairness Metrics

Quantitative indicators that measure the level of fairness and impartiality of an AI system across different demographic groups.

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Differential Impact Analysis

Assessment of the varied effects of an AI system on different population subgroups to identify disparities.

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Bias Mapping

Systematic process of identifying and documenting all potential sources of bias in the AI lifecycle.

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Context Sensitivity Assessment

Analysis of the suitability of an AI system to the cultural, social, and contextual specificities of its application domain.

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Algorithmic Social Impact

Measurement of the direct and indirect consequences of algorithmic decisions on social structure and human relationships.

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Transparency Assessment

Analysis of the level of explainability and understandability of an AI system's decision-making processes for its users.

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Fundamental Rights Impact Analysis

Specific evaluation of the effects of an AI on essential human rights such as non-discrimination, privacy, and freedom of expression.

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Algorithmic Accountability Assessment

Method to determine clear responsibility chains in complex and automated AI systems.

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Algorithmic Harm Indicators

Specific metrics designed to detect and quantify potential harm caused by automated decisions.

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Cumulative Impact Assessment

Analysis of the combined and synergistic effects of multiple AI systems operating simultaneously on the same population.

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Ethics by Design Framework

Methodological approach integrating ethical considerations from initial design and throughout AI development.

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Privacy Impact Analysis

Specific evaluation of the risks and consequences of an AI system on personal data protection and user privacy.

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Impact on Diversity and Inclusion

Measurement of the effects of an AI system on the representation and fair treatment of underrepresented or marginalized groups.

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Intersectional Bias Assessment

Analysis of complex forms of discrimination emerging from the intersection of multiple identity characteristics in AI systems.

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