Description: The term ‘unbiased’ refers to the absence of bias or prejudice, especially in the context of algorithms and artificial intelligence (AI) data. In a world where automated decisions can influence critical aspects of life, such as hiring, criminal justice, and access to services, unbiasedness becomes a fundamental ethical principle. Unbiasedness implies that AI systems must be designed and trained in such a way that they do not favor one group over another, ensuring that all individuals are treated equitably. This is particularly relevant in the development of machine learning models, where training data may contain inherent biases that, if not addressed, can perpetuate existing inequalities. The pursuit of unbiasedness in AI is not only a technical challenge but also a moral imperative, as biased decisions can have devastating consequences for affected communities. Therefore, unbiasedness becomes a key objective in AI research and development, driving the need for responsible and transparent practices in algorithm creation and data management.
