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To build trust, it's critical that AI systems should operate reliably, safely, and consistently. It should be able to operate as they were originally designed, respond safely to unanticipated conditions, and resist harmful manipulation, especially in the hands of third-party organisations.
When AI systems help inform decisions that have tremendous impacts on people's lives, it's critical that people understand how those decisions were made. The stakeholders can then identify potential performance issues, fairness issues, exclusionary practices, or unintended outcomes.
Xaana is committed to delivering Responsible AI solutions through reproducible and automated workflows by keeping humans in the loop to assess fairness, explainability, error analysis, and performance. With our products, make real-life interventions with causal analysis in the responsible AI dashboard and generate a scorecard at deployment time. Contextualise responsible AI metrics for both technical and non-technical audiences to involve stakeholders and streamline compliance review.
Overall, we focus on providing privacy and interpretability features to our products, educating users on how to use them responsibly, and collaborating with advocacy organisations and the policy community on how AI technology may be utilized now and in the future, to safeguard human interests.
