Fortunately, there are several solutions to limit and correct algorithm biases.

Biased algorithms that favor white / rich / qualified / men / hailing from developed countries…?

The enhancement developed and added to the patent consists in the innovations introduced in it through the algorhythms deployed in the method for remote multipoint monitoring and timeline analysis.

If algorithm biases are – in part – linked to the cognitive biases of those who programme them, we can understand the importance of diversity among developers.

This does not only benefit the coverage and annotation of the datasets, but also prevents ‘algorithm bias’.

The EESC also addresses the issue of “algorithm bias”: the code is indeed the reflect of the values of the person who has created and developed it.

The EESC also addresses the issue of “algorithm bias”: the code is indeed the reflect of the values of the person who has created and developed it.

Myrtille Picaud: Beyond biases in algorithms, which have trouble recognizing black persons and women, the reliability of facial recognition systems is still limited.