Driverless Cars Are Worse at Spotting Kids and Dark-Skinned People, Study Says

Also what is the safety target? Humans are extremely unsafe. Are we looking for any improvement or are we looking for perfection?

They should. But also, good. You should absolutely feel anxiety operating a multi-ton piece of heavy machinery. Even if everybody was super diligent about making themselves visible, there would still be the off cases. Someone's boss held them late and they missed the last bus so now they need to walk home in the dark when they dressed expecting to ride home in the day. Someone is down on their luck and needs to get to the nearest homeless resource and doesn't have access to bright clothes. Drivers should never feel comfortable that obstacles will always be reflective and bright. Our transportation infrastructure should not be built to lull them into that false sense of comfort.

Italian fork lift pit crew FTW!

I would say it's because dark stuff on dark background is harder to detect than other way around. Roads are dark, shadows are dark, pavement is sometimes dark, houses are quite often dark, so it blends.

I'd rather call for more powerful algorithms than bigger data sets.

because proper driverless cares properly use LIDAR, which doesn't give a shit about your skin color.

And can easily see an object the size of a child out to many metres in front, and doesn't give a shit if its a child or not. It's an object in the path or object with a vector that will about to be in the path.

So change 'Driverless Cars" to "Elon's poor implementation of a Driverless Car"

Or better yet..

"Camera only AI-powered pedestrian detection systems" are Worse at Spotting Kids and Dark-Skinned People

First impression I got is driverless cars are worst at detecting kids and black people than drivers

A stealth bomber gives less signal because of angles and materials and how they interact with radar, not because they are small or painted a dark color.

If a dark skinned person and a white skinned person are both wearing the same pants and long sleeved shirts, why would skin color be a factor beyond some kind of poorly implemented face recognition software like auto focus on cameras that also don't work well for dark skinned folks? Especially when some of the object recognition is just looking for things in the way, not necessarily people.

No, it is not some simple explanation based on people's eyes from the driver's seat while driving in the dark. It is a result of the systems being trained based on white adults (probably men based on most medical and tech trials) instead of being trained on a comprehensive data set that represents the actual population.

Except that’s not the source of this problem. AI can be great at detecting patterns with little data, if it’s properly trained. But this article is clear that the reason of this failure is in the lack of training data. This means that the AI never learned kids and dark-skinned people exist and it’s unreliable in detecting them.

It is easier to see dark object on bright background.

That's only part of it though. This issue is almost as old as we have had similar image/facial recognition technologies. Data is where models get their conclusions from.

Yes but isn’t it easier to say RACISM

It's not a discriminatory bias

You don’t know that.

Speaking as someone who inherited a computer vision codebase from Asian devs and quickly found that it didn’t work on white skin…

Implementation decisions matter, and those decisions will always be biased towards demonstrating successful output for the people who plan, bankroll, and labor on the project.

How much of the 20% or 7.5% difference in detection is due purely to inevitable drawbacks of size and skin tone?

Who knows.

What we do know is that we did measure a difference, and we do live in a culture where we’re more likely to hear a CEO say:

“It works!” …and then see an article months later that adds “…except for children and black people.”

rather than:

“It doesn’t work!” …and then see an article months later that adds “…except for adults and white people.”

And that fact means we should seriously consider whether our attention (and intention) is being fairly applied here.

Wow. that’s all kinds of incorrect

It’s not a discriminatory bias or even one that can really have anything done about it.

It is absolutely data training bias. Whether it is the data that ML was trained on or the data that programmers were trained on is irrelevant. This is a problem of the computer not recognizing that a human is a human

It’s purely physics.

It is not. See below:

Is it harder to track smaller objects or larger ones?

No, not if the scale of your hardware is correct. A 3’ tall human may be smaller than a 6’ one, but it is larger than a 10” traffic light lens or a 30” stop sign. The systems do not have quite as much trouble recognizing those smaller objects. This is a problem of the computer not recognizing that the human is a human.

Is it harder for an optical system to track something darker. In any natural scene.

Also no. If that were the case, then we would have problems with collision bias against darker vehicles, or not being able to recognize the black asphalt of the road. Optical systems do not rely on the absolute signal strength of an object. they rely on contrast. A darker skin tone would only have low contrast against a background with a similar shade, and that doesn’t even account for clothing which usually covers most of a persons body. Again, this is a problem of the computer not recognizing that the human is a human.

smaller and darker individuals have less signal. Less signal means lower probability of detection,

No, they have different signals. that signal needs to be compared to the background to determine whether it exists and where it is, and then compared to the dataset to determine what it is. This is still a problem of the computer not recognizing that the human is a human.

It’s the same reason a stealth bomber is harder to track than a passenger plane. Less signal.

Close, but not quite.

1. In this case the “less signal” only works because it is compared to a low signal background, creating a low contrast image. It is more like camouflage than invisibility. Radar uses a single source of “illumination“ against a mostly empty backdrop so the background is “dark”, like looking up at the night sky with a flashlight.
2. The less signal is not because the plane is optically dark. It has a special coating that absorbs some of the radar illumination and a special shape that scatters some of the radar illumination, coming from that single source, away from the single point sensor. Humans of any skin tone are not specially designed to absorb and scatter optical light from any particular type of light source away from any particular sensor. Even at night, a vehicle should have a minimum of 2 headlights as sources of optical illumination (as well as streetlights, other vehicles. buildings, signs and other light pollution) and multiple sensors. Furthermore, the system should be designed to demand manual control as it approaches insufficient illumination to operate.

This is a problem of the computer not recognizing that the human is a human.

You sound like an imaging specialist with no experience

I’m sure that will be of great comfort to any dark-skinned person or child that gets hit.

If those are known, expected issues? Then they had better program around it before putting driverless cars out on the road where dark-skinned people and children are not theoreticals but realities.

I'd go so far as to claim that sometimes it is worse than Reddit. Sometimes.

Apparently nighttime and black people are both dark in color. Nobody thought to tell the cameras or the software this information.