Technology

37724 readers

434 users here now

A nice place to discuss rumors, happenings, innovations, and challenges in the technology sphere. We also welcome discussions on the intersections of technology and society. If it’s technological news or discussion of technology, it probably belongs here.

Remember the overriding ethos on Beehaw: Be(e) Nice. Each user you encounter here is a person, and should be treated with kindness (even if they’re wrong, or use a Linux distro you don’t like). Personal attacks will not be tolerated.

Subcommunities on Beehaw:

This community's icon was made by Aaron Schneider, under the CC-BY-NC-SA 4.0 license.

founded 2 years ago

MODERATORS

[email protected]

Covert Racism in AI: How Language Models Are Reinforcing Outdated Stereotypes (hai.stanford.edu)

submitted 1 month ago by [email protected] to c/[email protected]

14 comments fedilink hide all child comments

you are viewing a single comment's thread
view the rest of the comments

[–] [email protected] 13 points 1 month ago (2 children)

While it may be obvious to you, most people don't have the data literacy to understand this, let alone use this information to decide where it can/should be implemented and how to counteract the baked in bias. Unfortunately, as is mentioned in the article, people believe the problem is going away when it is not.

[–] [email protected] 9 points 1 month ago (1 children)

The real problem are implicit biases. Like the kind of discrimination that a reasonable user of a system can't even see. How are you supposed to know, that applicants from "bad" neighborhoods are rejected at a higher rate, if the system is presented to you as objective? And since AI models don't really explain how they got to a solution, you can't even audit them.

[–] [email protected] 3 points 1 month ago (1 children)

I have a feeling that's the point with a lot of their use cases, like RealPage.

It's not a criminal act when an AI did it! (Except it is and should be.)

[–] [email protected] 6 points 1 month ago

"It's not redlining when an algorithm does it!"

[–] [email protected] 4 points 1 month ago* (last edited 1 month ago) (1 children)

[–] [email protected] 3 points 1 month ago

I suppose to wrap up my whole message in one closing statement : people who deny systematic inequality are braindead and for whatever reason, they were on my mind while reading this article.

In my mind, this is the whole purpose of regulation. A strong governing body can put in restrictions to ensure people follow the relevant standards. Environmental protection agencies, for example, help ensure that people who understand waste are involved in corporate production processes. Regulation around AI implementation and transparency could enforce that people think about these or that it at the very least goes through a proper review process. Think international review boards for academic studies, but applied to the implementation or design of AI.

I’ll be curious what they find out about removing these biases, how do we even define a racist-less model? We have nothing to compare it to

AI ethics is a field which very much exists- there are plenty of ways to measure and define how racist or biased a model is. The comparison groups are typically other demographics.... such as in this article, where they compare AAE to standard English.