The potential of artificial intelligence (AI) is expansive and will be used in ways we cannot yet imagine.
We all have a duty to guide AI’s development to facilitate innovation and fair competition while guarding against bias.
This white paper explores why context is critical for AI standards. Read this paper to learn:
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- How graph data platforms capture contextual information and make better predictions
- Why ensuring fairness and minimizing bias is critical to increasing trust in AI
- How graph-native learning on connected data supports explainability and increases accuracy
Fill out the form to get your copy of Toward AI Standards: Why Context Is Critical for Artificial Intelligence.