Ensuring AI algorithms are fair and unbiased involves several measures:Ensuring AI algorithms are fair and unbiased involves several measures:

-Diverse Data: it is advisable to use datasets that are different and are taken from -different sources to minimize bias that is found in the data.
-Bias Detection: Use techniques that prevent biases in the data and models and quantify its effect.
-Algorithm Audits: Semi-periodically review the algorithms in order to assess and fix the sources of prejudice.
-Transparency: Ensure that the development process and logic behind decision made by AI are clear to all the stakeholders.
-Fairness Metrics: Engage in aspects of fairness metrics and guidelines that may be used in the assessment and prevention of biased result occurrences in various categories.
-Human Oversight: Introduce human supervision in rechecking and tweaking of AI outcomes especially in sensitive operations.
-Ethical Guidelines: Abide to already existing standards and policies or creating a new set of policies on artificial intelligence.
-Continuous Monitoring: In order to mitigate the problems with AI system new biases that might appear after deployment these should be continuously monitored.
With these measures, the developers of AI can thus strive to build algorithms that are free from prejudice.