Such bias can occur either through the way in which algorithms are trained with data sets that are discriminatory in themselves, by using sets that contain latent discriminatory biases, by the overabundance of historical data that oversize mobile phone number list elements that lead to the multiplication of data. discriminatory effects, or by the conscious choice to underrepresent what is not hegemonic.
Finally, and without the mobile phone number list intention of exhausting all the existing modalities of manifestation of the algorithmic bias, this can also be a consequence of the technical limitations of the design; consequence of the unforeseen use of algorithms in new contexts of use and by a public different from that for which they were mobile phone number list intended, or also consequence of the interpretation of data that is reinserted and increases discrimination exponentially in the same algorithmic system.
To the question of whether discrimination mobile phone number list due to algorithmic bias is avoidable, a frank and negative answer is possible: it is not possible to avoid it in the current state of science, and that is why, considering this point, artificial intelligence should not be used in critical areas related to the exercise of our rights, such as video surveillance/biometric surveillance, profiling, electronic surveillance, judicial or administrative decision-making, decision-making resulting in the distribution of access rights and the determination of the extent of our rights, among other areas (for example, health , credit/financing, housing, education, consumption, etc.).