Lore

Akshay Kore's Trustworthy-AI Framework

A 2018 framework arguing that a system which isn't trustworthy isn't useful. Trustworthiness is broken into five dimensions:

• Explicable — decisions can be explained
• Transparent — how the system works is visible
• Non-biased — doesn't encode or amplify unfair discrimination
• Privacy-centered — respects and protects user data
• Beneficial to society — net positive externalities, not just to the operator

Cited by Simonetta Batteiger as a practical audit checklist for whether an AI-driven feature is launch-ready, alongside the EU AI Act Trustworthiness Dimensions as a regulatory counterpart.

Из тем: AI and the Changing Shape of Product Work