In finance, fairness is a required constraint on AI systems: regulatory scrutiny and the immediate effects of decisions make it central to development and deployment. section 1.1
Fairness
The principle that decisions and outcomes should treat affected people or groups equitably and avoid unjustified discrimination.
How Financial AI in Practice covers it
- How deep it goes
- Names fairness as a requirement but does not define measures, tests, or implementation steps.
- How it connects
- Connects fairness with explainability, compliance, and AI in finance.
Also explained in
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Think Like a Software Engineering ManagerFairness is the equitable and impartial treatment of people according to consistent standards and processes.
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Generative AI in ActionFairness is the property of treating people equitably and avoiding unjustified disparities in the outcomes or treatment produced by an AI system.
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Starting Data Analytics with Generative AI and PythonThe property of treating relevant individuals or groups equitably and avoiding unjustified disparities in AI systems or their use.
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Introduction to Generative AI, Second EditionFairness is the property of treating individuals and groups equitably in an algorithmic system's design, operation, and outcomes.
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Machine Learning System DesignThe property that a model’s behavior or performance does not produce unjustified disparities across relevant demographic or other groups.
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Inside AIFairness is the property of treating people equitably and avoiding unjustified disparities in system outcomes.
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Causal AIFairness is the property that an algorithmic or statistical system treats individuals or groups according to specified equity criteria.
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Building Reliable AI SystemsThe property of an AI system treating people and groups equitably and avoiding unjustified disparities in outcomes.
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The Art of AI Product DevelopmentFairness is the property of treating relevant people or groups equitably in an AI system's behavior and outcomes.
Compare how 10 books explain fairness →
Related concepts
- bias detectionmeasured by · Bias detection is the systematic assessment of data, decisions, or system behavior to identify distortions or unjustified disparities across groups or conditions.
- machine learningpart of · Machine learning is a field of computational methods in which systems learn patterns or relationships from data to make predictions, decisions, or other outputs.
- livenesskind of · Liveness is a correctness property requiring that a system eventually makes specified progress or produces a desired event or condition.
- Gini impuritymeasured by · Gini impurity is a measure of class-label heterogeneity in a set or decision-tree node, calculated from the proportions of its classes.
- diversity, equity, and inclusionpart of · Diversity, equity, and inclusion is an organizational principle and practice promoting representation, fairness, participation, and belonging for people with different identities and backgrounds.
This explainer was generated by Manning's knowledge graph from the text of Financial AI in Practice. The section links point to the parts of the book it draws on.