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Responsible AI
An approach to AI development and deployment that prioritizes safety, fairness, transparency, and accountability.
TL;DR
- —An approach to AI development and deployment that prioritizes safety, fairness, transparency, and accountability.
- —Understanding Responsible AI is critical for effective AI for companies.
- —Remova helps companies implement this technology safely.
In Depth
Responsible AI is the practical implementation of AI ethics principles. It includes bias testing, explainability, human oversight, privacy protection, and environmental consideration. Organizations implementing responsible AI programs need technical controls (guardrails, audits) alongside policy frameworks.
Related Terms
AI Ethics
The principles and guidelines governing the responsible development and use of AI systems.
AI Governance
The framework of policies, processes, and controls that guide responsible AI development and usage within organizations.
AI Bias
Systematic errors in AI outputs that result from biased training data or flawed model design.
Explainability (XAI)
The ability to understand and explain how an AI model arrives at its outputs or decisions.
Glossary FAQs
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