guides pages

The importance of redress and remedy in AI systems Mechanisms should be in place to ensure that individuals and communities have access to effective redress and remedy for harms caused by AI systems. Permitting private redress mechanisms against companies helps to ensure that there is effective enforcement of rules by providing people with the power […]

The importance of accountability in AI systems Those responsible for the development and deployment of AI should be accountable for its impact on society, and mechanisms should be in place to hold them accountable, including any harm caused to individuals or communities. Accountability is important for ensuring that developers, deployers, and designers comply with legislation […]

The importance of transparency in AI systems AI developers should be transparent about the purpose, scope, and operation of their AI systems, including the algorithms, data inputs, and decision-making processes. Transparency is crucial to ensure that AI is developed with clarity on its potential benefits and risks. It helps to ensure that ethical issues are […]

The importance of protecting vulnerable groups in AI systems Special protections should be put in place for vulnerable groups, including children, persons with disabilities, and elderly individuals, to ensure that AI systems do not harm their rights and interests. Protecting vulnerable groups is important to ensure that security concerns about the exposure of their personal […]

The importance of inclusivity in AI systems AI should be developed and used in a way that is inclusive and accessible to all, including marginalized and disadvantaged communities. Inclusivity holds great significance since it ensures that when AI systems make decisions, they are the right and accurate decisions. Adherence to practices of inclusion in the […]

The importance of using high-quality and unbiased data in AI systems AI systems should be designed to use high-quality and unbiased data, in order to prevent biases and discriminatory outcomes. High-quality and complete data is representative and reduces the chances of bias. An AI system is simply as good as the quality of the input […]

The importance of fairness in AI systems AI systems should be designed and used in a way that promotes fairness and prevents bias and discrimination. Fairness in AI helps to ensure that AI models do not discriminate when making decisions, especially with respect to attributes such as country or origin, race, or gender. Thus, the […]

The importance of non-discrimination in AI systems AI systems should be developed and used in a way that does not discriminate against individuals or groups based on their race, ethnicity, gender, religion, or other characteristics. Fair and non-discriminatory AI helps ensure that AI systems are equitable and just, treating all persons fairly and without any […]