Responsible AI refers to the practice of developing and deploying artificial intelligence systems in a manner that prioritises ethical considerations, fairness, transparency, accountability, and the overall well-being of individuals and society. It encompasses a set of principles, guidelines, and techniques aimed at mitigating potential risks, biases, and unintended consequences associated with AI technologies.
Key principles of responsible AI include:
- Fairness: AI systems should treat all individuals and groups fairly and without discrimination.
- Transparency: AI systems should be understandable and provide explanations for their decisions.
- Accountability: AI systems should be able to be held accountable for their decision and actions.
- Privacy: AI systems should protect the privacy and personal data of individuals.
- Avoid harm: AI systems should seek to limit any unintended harm.
Designing and implementing responsible AI systems is a complex and involved task that requires a holistic approach. Consideration should be given to how policy, people, processes and technology can all be designed to work together to implement AI systems that are responsible.
This repository provides an example of how bias in AI models can be identified and mitigated, this is an important part of achieving fairness in AI systems.