We currently have 10 entries in this glossary.
AI Bias & Fairness: The tendency of AI to reflect training data biases, leading to unfair outcomes that need mitigation.
AI Bias & Fairness: The tendency of AI to reflect training data biases, leading to unfair outcomes that need mitigation.
Algorithmic Justice: Efforts to address biases and inequalities in AI algorithms, promoting fairness for all.
Algorithmic Justice: Efforts to address biases and inequalities in AI algorithms, promoting fairness for all.
Explainable AI (XAI): Techniques that make AI decision-making processes transparent and understandable.
Explainable AI (XAI): Techniques that make AI decision-making processes transparent and understandable.
Human-in-the-Loop (HITL): Integrating human judgment with AI decision-making, ensuring optimal outcomes and alignment with human values.
Human-in-the-Loop (HITL): Integrating human judgment with AI decision-making, ensuring optimal outcomes and alignment with human values.
Responsible AI: Designing, developing, deploying, and using AI in a way that is ethical, transparent, accountable, and aligned with human values.
Responsible AI: Designing, developing, deploying, and using AI in a way that is ethical, transparent, accountable, and aligned with human values.
