Which pillar ensures that AI systems do not discriminate?

The correct answer is based on the fundamental concept of fairness in AI systems. Fairness is essential to ensure that AI technologies do not discriminate against individuals or groups based on sensitive attributes such as race, gender, age, or socio-economic status. It involves designing algorithms and data processes in a way that mitigates biases, leading to equitable treatment and outcomes for all users.

In the context of AI in dentistry, fairness means that AI applications should provide equal and unbiased access to diagnostic tools, treatment recommendations, and care resources regardless of a patient's background. This ensures not only ethical compliance but also builds trust between patients and healthcare providers, and promotes health equity.

While compliance, explainability, and security are also crucial pillars in AI systems, they do not specifically target the issue of discrimination in the same direct manner that fairness does. Compliance relates to adhering to regulations and legal standards, explainability focuses on making AI decision-making processes understandable to users, and security entails protecting data from breaches – none of which directly address the core mission of preventing discrimination.