The quality of artificial intelligence (AI) models is critical to ensure that AI systems deliver fit-for-purpose results.
The quality of an AI model can be approached from different points of view. There are several ISO standards that address different quality aspects of AI models, such as robustness (ISO 24029), fairness (ISO 12791), reliability (ISO 2407, ISO 24028, ISO 24368, ISO 6254, ISO 8200), performance (ISO 4213), sustainability (ISO 20226) or transparency (ISO 12792).
Why is the quality of AI models important?
The quality of artificial intelligence (AI) models is critical to ensure accurate, reliable and ethical results. High-quality models produce more accurate predictions and are able to generalise to new data, ensuring informed decisions in critical applications such as medicine, finance or autonomous transportation. In addition, the quality of models helps reduce bias, avoiding unfair or discriminatory decisions, which is essential to maintain fairness, especially in sensitive areas.
A high-quality AI model is more efficient in the use of computational resources, which reduces costs and improves operational sustainability. It also ensures compliance with regulations and ethical principles, guaranteeing that AI operates within legal frameworks and transparency.
The quality of the models builds user confidence, which favours their adoption and effective use, thus maximising the benefits of AI while minimising the associated risks.
Assess the quality of your AI models with I2SC
At I2SC, we offer expert advice on assessing the quality of AI models based on international standards. Our team will accompany you at every stage of the process to assess and improve the quality of the models of your AI systems.
Contact us to find out more about our AI model quality assessment and improvement service.
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