I don’t understand how the police decided this guy hadn’t planned to attack a church for racist reasons. Sounds like they didn’t find evidence at his house about his intention to attack a black church, but that doesn’t preclude racism as a reason.
Brandishing a shotgun, aiming it at black churchgoers, barricading a house for a standoff, and writing a detailed description of a mass shooting attack definitely don’t mean a thing…
I mean… I’m sure it was shocking to see the bull and horn show roll down the road… but I’d have just laughed it off as hilarious… not ever considering calling 911 to have the poor dude pulled over.
Who does that? Also… would have loved to see the cops face when he had to walk up to the car! Hahaha 🤣
While I probably wouldn’t get involved…. That guy is a menace to society driving like that.
The bill probably weighs half the weight of the car. And the car is certainly beyond weight capacity. It’s structural integrity is also compromised in an crash.
Those tires are certainly not rated for the load, either, and worst case scenario in a crash, that bull is going to go flying, not die and become the kind of road hazard that gets people killed.
And what happens if the gate thingy fails and falls open on a highway? What Happens when the bull shits all over the car/truck/whatever behind them and causes that driver to crash?
If the driver is dumb enough to think this was a good idea… what else is he up to…?
Yep. We can’t have state run vehicle inspections, but we have state run liquor stores.
I’m originally from FL. Once upon a time it was a liberal state, but it’s constantly flooded with new immigrants from the north that don’t want to pay taxes (aka Freeloaders) who are mostly right wingers. I’m hopeful that this trend will continue and that enough right wingers from PA will move there and result in PA becoming a little less conservative.
Huh? Most Canadian provinces have provincial liquor store, like SAQ, LCBO and MBLL. I don’t think that part is particularly backwards. Quebec even has the provincial SQDC store for cannabis.
Coming from New Mexico where you can buy alcohol at a pharmacy and chase your painkillers with it, I think having specific state controlled liquor stores is actually a pretty good idea.
I learned gun safety at 6, on a bb gun, killed my first deer at 10. Trying to teach a 4 year old who probably isnt even sentient at this point on a real loaded firearm is the stupidest thing you can do. Firearms safety isnt a hard thing to teach, it should be taught in schools along with the home imo. Shooting sports used to be a big part of the american school system.
for my kids @ 4 I taught them if you see a gun, don’t touch it…go get an adult. @ 7 started BB gun and had to show muzzle / Triger discipline and recite the rules of firearm safety EVERY time we went out to shoot it.
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.
In order to make the software detect the same you have to make it detect white adult less.
Comparing the performance between races says nothing about how safe a driverless car is. I am sure that the chances of a human hitting a dark skinned person dwarfs the chances of a driverless car. Trying to convince people driverless cars are racist only delays development, adoption and lawmaking which means more flawed meatbags behind the wheel which means more car accident deaths.
What he’s saying is these aren’t issues, they’re like saying a masculine voice can be heard from further away. Deeper voices just carry better
Part of it is bias/training data - we can fix that. But then you’re still left with the fact children are smaller and dark skinned people are darker - if you use the human visible range of light (which most cameras do), they’re always going to be harder to detect than larger more reflective people.
Our eyes and brains have an insane ability to focus and deal with varying levels of light, literally each cell adapts individually to each wavelength. We don’t have much issue picking out anyone until it becomes extremely dark or extremely far away - it’s not because the problem is easy, it’s because humans are incredible at it
You seem to be one of the people who understand this better.
And even humans are not incredible at it. It’s just inherently harder to identify the areas where there are less signal. I’d love to see a study, but see my edit and actually quantifying the equality we’re after.
Reality/physics/science/PDEs (whatever) work on “differences”. The less difference, the harder.
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.
While some of these cars use radar to an extent. I believe this is mostly focusing on image recognition, which is from a camera. Both are distinctly different in how they recognize objects.
Image recognition relies on cameras which relies on contrast. All of which is dependent on light levels. One thing to note about contrast is that it’s relative to its surroundings. I think this situation is more similar to your eyes recognizing things while driving in the dark than you think. I suggest you research how these things work before making claims.
A quick primer in colour: recall that light colours reflect more light than dark colours. This means image recognition devices relying on cameras using standard spectrums (i.e. not infrared) receive less light into the sensor when pointed at someone with dark skin. The problem is constant, but less pronounced depending on the background. That is, a black person against a white background would be easier for an algorithm to identify as a person than said black person against a mixed or dark background.
It’s not necessarily effort. Data can be expensive and difficult to obtain. If the data doesn’t exist then they have to gather it themselves which is even more expensive.
I agree that they should be making sure they can account for both cases as much as possible. But you have to remember that from the frame of reference of the model being trained and used in these instances, the only data they’re aware of is the data they were trained on and the data they are currently seeing. If most of the data samples in the entire world feature white people 60% of the time it’s going to be much better at recognizing white people. I don’t think anyone is purposely choosing to focus on white people; I think that those tend to be the data samples that are most easily obtained or simply the most prolific.
I also think we need to take into account quality of data. As mentioned before, contrast plays a big role in image recognition. High contrast with background results in, on average, better data samples and a better chance of usable data. Training models on data that is not conclusive on ambiguous can lead to ineffective learning and bad predictive scores.
I don’t think anyone is saying this isn’t a problem but I also don’t believe that this is a willful failure. I think that good data can be difficult to get and that data featuring white people tends to have easier time using image recognition successfully.
Someone else mentioned infrared imaging, which is a good idea but also more money and adds an extra point of failure. There are pros and cons to every approach and strategy.
Cost being used as an excuse not to expand the data set to represent all types of people is just excusing systemic racism and other discrimination. For example, if the system requires two arms for it to recognize a person that is also a problem, because a person comes in a wife variety of shapes, sizes, and colors.
If the system can't handle that then it doesn't regocnize people. If it costs too much to do right, then that means they can't afford to do it at all.
In some cases the data sets were only white, but engineers have been cognisant of this issue for decades so I don’t think that’s as common as you might believe. More frequently it’s just physics.
As for “putting in the effort,” companies are doing this, to their detriment. Ensuring that a small proportion of their customer base has a perfect experience is very expensive. In business the calculation between cost and profit is very important. If you’re arguing that companies should provide unprofitable products so that your sensibilities can be assuaged then I disagree. No company has a duty to provide a product to you.
Yes, it even says that toward the end of the article:
According to the researchers, a major source of the technology’s problems with kids and dark-skinned people comes from bias in the data used to train the AI, which contains more adults and light-skinned people.
It is a result of the systems being trained based on white adults
It's both. The system is racist because of how it was trained and because its developers were not black, therefore "it worked for them" during development. And because black people are harder for cameras to see, especially in low light environments.
Even with clothes on, the dark skin, in a dark environment, "breaks" the "this is human" pattern that the ai expects to see, since the ai can see only the clothes. It is like camouflage. Can the ai "see" a pair of pants? Maybe, eventually but it still reduces the certainty, since the ai sees fewer "signs".
Cameras should be using infrared to look for objects in the dark and not fucking hoping it looks slightly less dark than the surrounding pixels. It being “dark” is not an excuse. Cars drive at night and need to be engineered around that fact.
Edit: note this is about cameras. Ideally, you’d use radar which wouldn’t care but if you are just dual purposing cameras used for driving, this is the bare minimum.
These systems are often trained on data obtained from driving the car around. I think the only real solution would be planning routes through more diverse neighborhoods. Although any company that is taking this seriously from a safety perspective has multiple radars and a top mounted LiDAR on their vehicles. Those sensors should be sufficient for detecting humans regardless of race even in a completely dark environment. Relying solely on camera data is just asking for problems for this and many other reasons.
Especially when some of the object recognition is just looking for things in the way, not necessarily people.
They were testing pedestrian detection systems. I would guess that means these systems look for people.
No, it is not some simple explanation based on people’s eyes from the driver’s seat while driving in the dark.
It may not be the only problem, but it is a contributing factor.
The study examined eight AI-powered pedestrian detection systems used for autonomous driving research. Researchers ran more than 8,000 images through the software and found that the self-driving car systems were nearly 20% better at detecting adult pedestrians than kids, and more than 7.5% better at detecting light-skinned pedestrians over dark-skinned ones. The AI were even worse at spotting dark-skinned people in low light and low settings, making the tech even less safe at night.
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.
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.
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.
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.
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.
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.
Cheap paintball gun would probably easily gum up the works on a drones propellers with a couple shots. At least throw off the balance enough for it to go down, or at worst cover up the camera lens.
We will always give money to our industries to make up for the lack of long term planning in our system. I certainly do not understand what concept of fucking justice that is related to.
I certainly do not understand what concept of fucking justice that is related to.
This concept of justice:
higher scores will be given to projects that are likely to retain collective bargaining agreements and/or those that have an existing high-quality, high-wage hourly production workforce, such as applicants that currently pay top quartile wages in their industry.
And that’s good. But what would be better for the planet would be building up a public transportation system so robust that cars are unnecessary outside of rural areas.
I was just listening to a Parenti lecture where he talked about an interaction he had with someone who had been in high up in East Germany. He basically asked, “why did you put out those crappy little two cylinder engine cars?” And the ex-officials response was essentially, “we didn’t want to put them into cars at all, we thought if we provided an adequate public transportation system, that people would be satisfied, but they weren’t so we had to do what we could.”
I agree with you fully, that public transport would be the ideal solution, far and away above electric vehicles, which just providing one for every household in the US would require such s massive amount of material extraction that it by itself will cause significant climate outcomes, but, we must find a way around the impulse for private personal transportation that exists within people, and I don’t know how to do so. Moving without the mass of people could lead to rejection and reactionary movements. Moving with the mass will lead to climate destruction. How do we work with the masses to come to a compromise that allows the support of the masses, while reducing the number of private vehicles to nearly zero?
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