What is Fairness in AI?
- Fairness in artificial intelligence can be defined as an attempt to correct the algorithmic bias such as race or ethnicity etc in an automated decision-making process. It is very important to address these algorithmic biases and mitigate them to follow the ethics of AI.
- This can be tricky and subjective at times because fairness can mean different to different people, and it is very difficult to jump to conclusions about it because fairness has different definitions. Fairness is a crucial concept and can’t be ignored.
- The main idea of fairness should be based on what is fair and must also be morally right. This simply means to connect fairness with equality and justice.
- The concept of fairness also protects a person or a group of people from discrimination or mistreatment and helps avoid bias where certain people have advantages over something.
- This concept is important in artificial intelligence because it is important for artificial systems to function with fairness so that they don’t favor or disadvantage certain people based on their gender, race, or ethnicity.
Fairness and Bias in Artificial Intelligence
Fairness and bias in artificial intelligence (AI) are critical issues that have gained significant attention in recent years. As AI systems are increasingly being used in various domains and applications, it is crucial to ensure that these systems are fair, unbiased, and equitable. Here’s a detailed overview of fairness and bias in AI.
Table of Content
- What is Bias in AI?
- Types of Bias in AI
- What is Fairness in AI?
- Types of Fairness in AI
- Addressing Fairness and Bias in AI
- Comparison of Bias and Fairness
- Conclusion