Building Trust in AI: Verify Performance

Establish confidence in AI platforms through Getting-AI-Right, a testing framework dedicated to governing generative AI. Certify your Generative AI and become part of our thriving community

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Trustworthiness

Build Trust in AI

Validate AI performance against international principles for trustworthy and ethical generative AI development

  • Assurance
  • Comprehensive AI systems testing
  • Collaboration

Validate AI Performance, Build Trust

Ensure ethical AI development and deployment by validating generative AI performance against recognized principles

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Frequently Asked Questions

Frequently Asked Questions

We have put together some commonly asked questions

What is the purpose of this AI validation system?

The purpose of our AI validation system is to emphasize the significance of building trust in AI systems by evaluating their performance based on globally accepted principles

How does the system test the data sourcing, labeling, and classification of datasets used for training AI models?

Our system employs a meticulous process to test the data sourcing, labeling, and classification of datasets. It ensures the quality and integrity of the data used to train AI models

Who can contribute to this project?

We encourage practitioners and researchers from various backgrounds to contribute to this project

What are the benefits of being a part of this community?

By joining our community, you can actively contribute to shaping the future of AI validation. You will collaborate with experts in the field and play a crucial role in advancing the trustworthiness of AI systems

Is the system compatible with different types of AI systems?

Yes, our AI validation system is compatible with different types of AI systems

How can I get started with using this AI validation system?

Getting started is easy! Simply visit our website and sign up to join our community. You will gain access to the resources, tools, and guidelines needed to implement the AI validation system effectively