Six biases that expose AI biases
Artificial Intelligence systems, whose adoption at the enterprise and individual level is growing rapidly, are not neutral. They have biases that reflect both the data on which their models are trained and the decisions made by those who design these systems. It is therefore necessary to understand and address the biases of algorithms that affect information, decision-making and digital rights.
This is stressed by the UDIT, whose leaders also warn about the risks of hyperconnectivity and the role of AI in everyday life, which is becoming increasingly relevant.
