What an article, Marcela. Although, to be honest I can't say that I'm entirely surprised by your findings. This is exactly why we have to be extra thoughtful and careful with the information we train these algorithms and Large Launge Models with. They are only as fair as the information we program them with.
Yes! Transparency is the key. I guess it’s difficult for the public sector, especially tax administrations being completely transparent because of tax secrecy but at least we should know how the algorithms were designed
What an article, Marcela. Although, to be honest I can't say that I'm entirely surprised by your findings. This is exactly why we have to be extra thoughtful and careful with the information we train these algorithms and Large Launge Models with. They are only as fair as the information we program them with.
Yes! You have a good point
This is a powerful reminder that biased systems usually come from biased histories.
What stands out most is how quietly proxy data can turn into real harm when no one checks it.
It’s why transparency and constant oversight aren’t optional, they’re the bare minimum.
Yes! Transparency is the key. I guess it’s difficult for the public sector, especially tax administrations being completely transparent because of tax secrecy but at least we should know how the algorithms were designed
Exactly