Description: Behavioral bias refers to the distortions that arise from the decisions and behaviors of individuals involved in the development of artificial intelligence (AI). This type of bias can manifest at various stages of the AI creation process, from data collection to algorithm design and model implementation. Often, developers, engineers, and data scientists bring their own beliefs, experiences, and prejudices, which can influence how data is selected and processed. As a result, AI can perpetuate or even amplify these biases, leading to unfair or discriminatory decisions in practical applications. Ethics in AI becomes a crucial topic, as behavioral bias can affect vulnerable groups and contribute to social inequality. Identifying and mitigating this bias is essential to ensure that AI systems are fair, transparent, and accountable. In this context, it becomes evident that diversity in development teams and the implementation of ethical practices are fundamental to addressing behavioral bias and promoting a more equitable and representative AI.
