AI Programs Exhibit Racial and Gender Biases, Research Reveals (theguardian.com)

An anonymous reader quotes a report from The Guardian: An artificial intelligence tool that has revolutionized the ability of computers to interpret everyday language has been shown to exhibit striking gender and racial biases. The findings raise the specter of existing social inequalities and prejudices being reinforced in new and unpredictable ways as an increasing number of decisions affecting our everyday lives are ceded to automatons. In the past few years, the ability of programs such as Google Translate to interpret language has improved dramatically. These gains have been thanks to new machine learning techniques and the availability of vast amounts of online text data, on which the algorithms can be trained. However, as machines are getting closer to acquiring human-like language abilities, they are also absorbing the deeply ingrained biases concealed within the patterns of language use, the latest research reveals. Joanna Bryson, a computer scientist at the University of Bath and a co-author, warned that AI has the potential to reinforce existing biases because, unlike humans, algorithms may be unequipped to consciously counteract learned biases. The research, published in the journal Science, focuses on a machine learning tool known as "word embedding," which is already transforming the way computers interpret speech and text.

Comments

from the biased report...

[turkeydance]

"And the AI system was more likely to associate European American names with pleasant words such as “gift” or “happy”, while African American names were more commonly associated with unpleasant words." ...what were those unpleasant words?

Re:Simple solution

[lorinc]

Just like for regular humans. People almost never question the religion there were born with, or views on races and culture for that matter.

Or rather...

[PatientZero]

AIs could incorporate existing biases.

Say you train an AI that will accept or reject loan applications by giving it a stack of previous loans. If the human loan officers were biased against minorities—rejecting otherwise acceptable applications—that AI may end up doing the same. This bias is much easier to detect in human behavior but less so with AI which can't explain why it made any particular choice or even what its criteria are.

Re:Or rather...

[guises]

You're missing what the parent is saying - you can't just tell the AI to ignore race/gender, it's baked into how we talk and act. Telling the AI to ignore gender, for example, would require finding every last thing which correlates with gender (basically impossible) and telling the AI to ignore those (which would mean cutting out large portions of what it needs to function).

E.g.: Your AI makes a statement, "Women be like this, while men be like this." And you tell your AI, "No AI, bad."

So your AI rethinks it and comes up with another statement, "People with vaginas be like this, while people with penises be like this." And you tell your AI, "No AI, bad."

So your AI rethinks it and comes up with another statement, "People named Betty or Veronica be like this, while people named Archie or Jughead be like this." And you tell your AI, "No AI, bad."

So your AI rethinks it and comes up with another statement, "People who wear makeup be like this, while people who don't be like this." And you tell your AI, "No AI, bad."

Etc. You could do this forever and you still wouldn't catch them all, they'd just get more subtle.

Re: Or rather...

[ShanghaiBill]

Making loans to people of color is more risky.

It depends on the color. Asian Americans have lower default rates than whites.

of course

[argStyopa]

..the begged question is that gender or racial bias and stereotypes are intrinsically "wrong". They are to our 21st century sensibilities, but they served humanity pretty well for millions of years.

Maybe where you have a society where women ARE primarily concerned with raising children, there are better outcomes than when men raise children or women go off to pursue their careers. Maybe where you have a society where obvious strangers are marginalized and driven away, the remainder ends up more cohesive.
I'd be curious how these AI biases would develop if 'fed' only native African literature and information.

I'm not making an 'appeal to nature' here, saying what "should" be or "shouldn't" be.
One might suggest that, evolutionarily speaking, maintaining a bias is harder than not, assuming no reinforcement. That our language (pretty fundamental to being human, after all) is pervasive with such institutional biases would suggest that there is a value/benefit to such.