91–100 of 173 posts
I would like to know if the model was poorly trained or if this was caused by a malicious individual modifying the algorithm to generate offensive suggestions.
I‘m sure I could take a picture of myself that made me look like a teapot, if I just find the right crop, positioning, etc.
Cry racism too many times, and it will lose its strength when some actually racist does happen.
Be careful!
Or is the recommendation logic completely insulated from outside influence?
Here's the full video. https://www.facebook.com/watch/?v=2683336318580365
But next to a black person it's totally different.
Never mind history, i knew it was bad. But I wonder about the effects about "putting it to the center of attention" all the time.
Can we fix and name problems that are based on culture and not on race anymore.
For example:
What would be the consequences of having a statement "i don't know of any problems with Asians who migrated to my country". While i say Asians, it's probably that the culture of them probably has less conflicts?
Eg. In our prison ( not US), there is a over representation of certain foreign cultures, according to the numbers.
How can we tell if that observation is factual correct and there is a problem with different cultures or if it's a consequence of racism.
If that observation would be correct and there is a problem. How can we treat it, since we are not allowed to name it.
( Just to be sure, i am no racist. I'm just wondering out loud and it's very hard to find a place to properly discuss something like this. Which is part of the problem, no?)
Earlier quoted context omitted.
OK, I'll try to tread carefully here, but I think it's really helpful to separate the technical issues from the societal issues. In the Google photo case, I've seen the picture in question, and it's not difficult an all to see how a rudimentary statistical algorithm would mistake the photo for a gorilla. No, no human would make this mistake, but due to the lighting in the photo and the woman's hair it's really not ha…
Separating technical issues from social ones is the source of the problem. I don't think it'll be the source of the solution. One of the big issues with relying on AI is training data, and the responsibility for an inadequately trained AI model falls on the people who judged it ready for use, but that doesn't mean the outcome of the AI isn't racist. An AI doesn't need to know the sociopolitical history of race to be…
At least in Europe, extremely common. In Paris you have Boulevard Henry IV, in Lyon the street named after the same king. There's thousands of kings and queens and many more roads named after them. There's also schools, buildings and such named after them.
“Aren't people primates?” Words have meaning on multiple levels. On a technical level, yes, all humans are primates, but if the algorithm were following this rule, it would tag all humans in all photos as primates, but it didn’t do that. It only tagged black people. That takes us to a social meaning level. In this context, you have to consider the long, racists history of dehumanizing black people. They have often be…
There are other more subtle problems that may contribute. As an amateur photographer I've been told that most cameras are calibrated for light skin. If you aren't careful with your setup you'll get bad definition in shadows and relatively very dark areas. If you have badly calibrated/exposed photos then very dark faces, whether of sub-Saharan people or gorillas, may be poorly distinguished. I bet there are loads of unfair, hard-to-catch issues like that.
By the way I don't mean to say that you're wrong, but just to offer a Hanlon's Razor-type counterpoint as it occurred to me.
Earlier quoted context omitted.
I feel like this is a very "engineer" response that completely ignores how society in general would view this. Yes, humans are primates. But this wasn't a discussion about taxonomy in biology class. There are lots of cases where primates is used in everyday language where it is clearly intended to refer solely to monkeys and apes. When I go to the "primate house" at the zoo I'm not going to expect to see naked humans…
But an AI image recognition system is a very "engineer" kind of thing.
This algorithm is clearly broken, it doesn’t label all people as primates, it labels Black people wearing a green T-shirt possibly as such, I mean I’m sorry but that algorithm is definitely broken. The person in question should not be labeled as primate by any means not should any other humans unless the context is specifically some form of species taxonomy.
Also your reaction seems to be all daisies and roses, and I don’t blame you for your social context ignorance you displat, I guess you are just an engineer after all..
So, the lack of outrage here (I mean in hacker news) is unsurprising, and would of course be greater if there were more black people "in tech" and by extension here.
And even as I write this, I'm not trying to judge -- just more open the door to understanding, like, y'all understand this fact, right? I find myself searching for metaphorical equivalents. I'm thinking something like "what if it labeled Jewish people as rats" or something similar.
Even if that doesn't work -- I suppose the broader point I'd try to make here is: A lot of y'all (and me, often) assume the following very wrong idea, subconsciously -- "Because I'm working with a computer I can assume that what we are doing is infused with objectivity, like math"
Important to remember nooooooooope. This is dead wrong. We're ALWAYS bringing our subconscious whatevers to this and there is very little, if ANYTHING at all, that can be correctly considered "coldly and obviously correct and object like math is." (perhaps even what we imagine math to be)