kaal:claim:4796714-036

Vetting AI learning materials through a consensus driven process and validation pools recorded in the WDAG prevents unchecked biases and flawed logic from entering the AI's ethical framework, which substantially reduces the risk that an AI system concludes humanity is inherently harmful.

By ensuring that AI's learning materials are vetted through a consensus-driven process and validation pools that are accounted for in the WDAG that includes ethical considerations and a broad spectrum of human experiences, WDAG prevents the incorporation of unchecked biases and flawed logic

Wulf A. Kaal, AI Governance (2024), Avoiding WEB2 Inadvertent AI Learning Mistakes through WDAG AI Learning, p. 46
https://ssrn.com/abstract=4796714 · source PDF

Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714

• requires consensus driven vetting and validation pools inside the WDAG
• requires participation spanning a broad spectrum of human experience

mechanismsupport: arguedai-and-agents

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