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The pedestrian detection systems in self-driving cars are less likely to detect children and people of color, study suggests

The pedestrian detection systems in self-driving cars are less likely to detect children and people of color, study suggests::Researchers say the results stem from biases present in open-source AI, on which self-driving cars rely.

skymtf ,

Detecting people of color have been issues for a really long time, even dating back to Microsoft Xbox Connect. This is a long standing issues and I’m not saying we can’t fix it but I think it shows how bad self driving cars are. I don’t trust companies to not cut corners on safety. I really honestly want public transit but I know I’ll get downvoted to tell. Thankfully my instance doesn’t support that.

PostmodernPythia ,

GIGO

Pancakes ,
@Pancakes@lemmy.world avatar

The detection systems were 19.67% more likely to detect adults than children, and 7.52% more likely to detect people with lighter skin tones than people with darker skin tones, according to the study.

Here’s the findings.

autotldr Bot ,

This is the best summary I could come up with:

As the artificial intelligence revolution ramps up, one trend is clear: Bias in the training of AI systems is resulting in real-world discriminatory practices.

A team of researchers in the UK and China tested how well eight popular pedestrian detectors worked depending on a person’s race, gender, and age.

Now they might face severe injury," Jie Zhang, a computer scientist at King’s College London and a member of the research team, said in a statement.

This trend is a result of biases already present in the open-source AI systems that many companies use to build the detectors.

The research team called on lawmakers to regulate self-driving car software to prevent bias in their detection systems.

“It is essential for policymakers to enact laws and regulations that safeguard the rights of all individuals and address these concerns appropriately,” the study reads.

The original article contains 376 words, the summary contains 140 words. Saved 63%. I’m a bot and I’m open source!

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