This repo contains the initial version of the AI Product cards.
Drawing from the classification of AI applications for the public sector, this repo entails documenting the individual building blocks that constitute the AI use cases.
This would facilitate the correct utilization of the models as an approach to increase the transparency of building AI solutions in different contexts and by different stakeholders.
In addition to the requirement of flexibility to accommodate a diverse range of AI tasks, the design of AI cards should prioritize ease of reuse and adaptability.
Some of the attributes of an AI card involve the learning algorithm, associated metrics, adaptability properties, optimization techniques, specific details of the datasets used for training and evaluation, as well as data distribution characteristics.
Moreover, the design of these cards will enable customization and extendability, ensuring they can be tailored to specific needs and use cases.
The main considerations - social impact, reproducibility, and evaluation - form the main aspects of our templates.
The primary contribution of the AIPC framework centers around facilitating swift AI adoption by providing scaffolding strategies.
