this post was submitted on 29 Aug 2024
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That's what is usually meant by AI bias: a bias in the material used to train the model that reflects in its behavior
But why is it even mentioned then? It's FUCKING OBVIOUS. It's like saying "AIs are biased towards english and neglect latin" or smth ffs
I feel like not everyone is conscious of these biases and we need to raise the awareness and try preventing for example HR people from buying AI-based screening software that has a strong bias that is not disclosed by their vendors (because why would you advertise that?)
I was confused how a resume or application would be largely affected, but the article points out that software is often used to look over social media now as part of hiring (which is awful).
The bias when it determined guilt or considered consequences for a crime is concerning as more law enforcement agencies integrate black box algorithms into investigative work.
Great comparison, a dialect used by millions of people to a dead language. It really shows how much you care about the people who speak that dialect...
AIs are trained on what is written in the Internet. Latin is not spoken, it's written. But even then, it's rarely used. African american is a dialect, it's only present in speech.
You need to get out more. I totally get that you would think that’s the case, but only if you’re not exploring parts of the internet outside your bubble. It’s absolutely written.
There are actually quite a few books written in AAVE...the earliest I'm aware of is their eyes were watching god, from the 1930s. The Color Purple, Beloved, The Sellout, the books of Chester Himes...
What is obvious to you is not always obvious to others. There are already countless examples of AI being used to do things like sort through applicants for jobs, who gets audited for child protective services, and who can get a visa for a country.
But it's also more insidious than that, because the far reaching implications of this bias often cannot be predicted. For example, excluding all gender data from training ended up making sexism worse in this real world example of financial lending assisted by AI and the same was true for apple's credit card and we even have full-blown articles showing how the removal of data can actually reinforce bias indicating that it's not just what material is used to train the model but what data is not used or explicitly removed.
This is so much more complicated than "this is obvious" and there's a lot of signs pointing towards the need for regulation around AI and ML models being used in places it really matters, such as decision making, until we understand it a lot better.