You cannot eliminate bias. You can only compensate for it by illuminating more options. Otherwise the bias "elimination" is subject to bias. E.g. If you avoid a subject when teaching someone, it becomes a weakness in their understanding, and can fall into an overcompensation bias. Furthermore, who decides what counts as a negative bias that should be eliminated? That strikes me as the kind of thing we should be having discussion on and not deciding for other people without their consent. Give people more opportunities to understand, not fewer opportunities to learn.
Google: Makes a promotional video in which they directly ask people to join the conversation about bias. You, an intellectual: "That strikes me as the kind of thing we should be having discussion on and not deciding for other people without their consent." A yes, I see the word understander has entered the room.
So who decides what's biased? Does "equal inclusion" mean the results are unbiased? What if the unbiased view of those engineers overlooked by policy makers within Google isn't actually unbiased? Put simply, who will guard the guardians?
But, what if I am trying to find the hateful stuff because I am trying to see what other people are saying? Doesn't matter if they are morally wrong or right, it should still be easy to find
This is just replacing one bias with another. How about just letting every person decide on what they want to see rather than automatically deciding based on some "offensiveness" interpretation that others are doing for me. Furthermore, how about allowing some negative speech? Yes, the internet can be a bit of a cesspool at times, but without adversity we grow no stronger against it. We can't always rely on something being a safespace tailored to our needs. Please stop being silly Google..
But could those two things go together? If they tailor the user experience individually, then the result would be similar to a Facebook feed: an echochamber of similar ideas. But if we want to allow negative speech (relative to the user), then they would likely not want to see it, which would go against the goal of tailoring experiences individually. However, I still think the individual user should decide what they want to watch and that Google shouldn't participate in censorship.
Something that should be noticed is that just because most Physicists in the past were men, doesn't mean there's a bias. It's just a fact. Same goes for females and great teachers, shaping people's lives.
William Lardner The issue appears when the machine is used with this bias, like categorising photos, or if you ask it to show you pictures of physicists. It might not even recognise a female physicist, which is a mistake in the program. A bias might have a good reason to be there, but that doesn't mean it should still have influence.
This is the scariest thing in the entire world....What gives Google the authority to decide what is and isn't negative, bias or hate speech? Alphabet a.k.a Big Brother/Skynet.
Luckily this is still a free country and we still have the vote of the dollar and where we put our resources and funding. I deleted my FB account I had for ten years because I still had that freedom. WE give them that authority, and we can also take it away
@@GrantGryczan The bias of the individual or individuals making the changes to the results. Let's say I take a poll in my town: "What's your favourite music genre?" If the result of that poll is that most people in my town are fans of acid jazz then that is the result of the poll. If I think acid jazz is terrible and more people should discover the wonderful music of Justin Bieber then I could change the results to give justin Bieber more exposure and (hopefully) get more people listening to good music instead of that awful acid jazz that so popular. What I have just done is introduced my own bias into the results. This is exactly what Google is doing while claiming they are "un-biasing" the results.
@@ZoomahZoomah Refer to the other comment chain: Google isn't doing a thing, and the bias the video refers to has nothing to do with sample ratio accuracy.
This video starts out with a great description of human bias and then proceeds to say that, to resolve this problem, Google has selected the biases that it thinks should be enshrined... that's not a lack of bias. That's enforced and canonized bias.
Never thought about machine learning and human bias. Always thought it will not affect the results. But we are designed to see the world from our own eyes, experiences. Why will our code be any different.
"Report inappropriate content" is also biased. This means it only counts those people who think content is offensive but doesn't count those who think that the content is not offensive.
First step by AI to take control from humans. By appearing unbaised & pointing human biases. E.g. -Divided men & women then become the unbiased judge to dictate! A human system is to be controlled by humans not machine!!
Bias can actually be a good tool for a computer. A physicist doesn't look like anything, and you would want a computer to understand that. But, if for some reason you need a computer to be able to pick the most likely physicist out of a lineup, then it would need that bias to form an educated guess. A computer should not be free from bias, it should just know when to use it.
It appears that google is deciding what is not biased. How are people at google able to be sure that they are not introducing their own bias into this process?
The very act of setting up the system introduces biases no matter how much they try or say they try to avoid it. By trying to eliminate biases, they introduce biases. Who are they to decide what is a good or bad bias?
@@reverendcaptain They don't decide. They let the machine do it, and then they let the users moderate. Again, this is demonstrated in the video. The employees are not a part of the process but to maintain the machine, and they do not give the machine input. By not giving the machine input, they are not introducing any bias. The bias they refer to in the video is created by the users, and the solution to resolve this bias is also by the users. The employees in particular do not introduce nor try to eliminate bias.
@Grant Gryczan Based on this video Google provides tools for users to remove opinions or information they don't like. This means that certain groups of people can manipulate what kind of information of them or their interest is available for public. This does not promise good for any kind of minority views. This leads to exact kind of bias they wanted to eliminate on the video. (Caricatured example: Take male scientist bias. If majority of viewers did not like - for whatever reason - female scientists, they could remove female scientists entirely appearing on the search results.)
@Grant Gryczan Did you delete your reply because I can't see it? Did you realise that my female scientist example was in parenthesis because it is ridiculous example and you need to replace it with some other interest group of your choice. I guess you can imagine examples of interest groups where majority of the group does not want minority of the same or opposing group gain visibility.
If those biases happen to reflect the truth, are you not suppressing the truth by artificially injecting a bias of your own? It's like stereotypes; on an individual level they are socially inappropriate and misguided, but they're often reflective of some reality at the group level. Should that reality be suppressed?
Hi. We're Google. We support Facism under the guise of compassion. Don't worry though we're got a BRILLIANT marketing department. We'll make it all feel like its all a nice warm bath.
Bias many times begin with those who think others are bias! However, it does not occur to them that their "Politically Correct" ideology itself biased, which makes them to see other views as biased if it does not confirm with theirs. And the political blame game begins.
The whole idea of freedom of speech is to be able to say almost anything as we seek to discover the truth, so yes, even if it offends someone. Someone who is in denial may easily consider the antithesis of the position they hold to be offensive, even if the opposing view is true.
This video is relatively educational and presents clean information, then I see people force their opinions about adjacent subjects in the comments. How appropriate.
First step by AI to take control from humans. By appearing unbaised & pointing human biases. E.g. -Divided men & women then become the unbiased judge to dictate! A human system is to be controlled by humans not machine!!
@@cafeta Whatever that is is not relevant to the video. Again, they explicitly described systems implemented for users to be able to resolve the network biases. If you're just going to ignore those along with the point of the video then I'm just going to ignore you, because what you're saying to this video is not relevant.
so how do you eliminate the human bias that controls the moderation of the machines human bias? doesn't seem to be much help the "limiting of offensive results" only removed "offensive" opinions that google doesn't agree with, either manually or through new human bias influenced machine learning. opinions like that of the man who google recently fired for questioning google's current stance on workplace sexism. even if you agree with google for this example, there could be anything that google finds offensive that you don't. if the only information available is the information not censored by google, whether or not you think that the results would be in your personal favor, the control over what opinions people have access to should be the right of no person or organization.
If you're training your model on what a physicist looks like, and you use a training dataset of past physicists, you are training a model on what past physicists looked like. There is no bias there. The problem is training data that does not match the question that is trying to be solved. Certain people are using these problems as a justification for interjecting *actual* bias through human intervention. It's dishonest and anti-intellectual. Honestly, this is machine learning 101. It's just issues of overfitting and underfitting. Poor data sets. I guess they've started to call it "bias" so that they can claim a moral high ground while controlling outcomes to their liking. That's what they've been doing by the way.
You have a bias to only look at the most relevant comments, which has a bias to be recent comments. Your thought about the comments is biased and wrong.
It's based on your personal preferences (e.g what you mostly click on.) You are training the AI for your recommendations. I am training the AI for my own. Welcome to machine learning.
Went from an informative lesson on machine learning to focusing on what Google considers appropriate. Why are you training ai to learn based on your own bias?
If most physicists are male then it isn't biased for a computer to generate more male physicists. That's not what bias means. If something makes decisions based solely on facts then that something isn't biased. Something being offensive to a lot of people doesn't make it a bias.
I was with you until your last sentence. How does any of that logic show that the video is biased? On that note, what is the video even biased toward, and how? Edit: They edited the original comment, so never mind this one.
@@GrantGryczan I might be wrong but the video seems to be biased towards a certain branch of identity politics by assuming that representing everyone is equivalent to not being biased.
@@sel2230 This video doesn't even reference identity bias. Did I miss something? As far as I know, it only talks about bias in AI recognition. That's why I agree with the rest of your comment; everyone is going around the comments and bringing politics into this video while it has nothing to do with the biases at hand.
@@GrantGryczan you might not be familiar with Google's affirmative action policies. That and the wrong message this video portrays makes me think that this video is biased. However, you might be right. Maybe the video is wrong because of other reasons.
@@sel2230 I'm not sure you realize, but this video isn't trying to portray a message. It's just trying to show people how their AI works, particularly to resolve automatic inaccuracies. This is an objective informational video.
Another thing to keep in mind is that there is a difference between *bias* and *context* . Who were those people who were asked about the shoes? When was it? Where was it? Removing all traces of potential bias can lead to irrelevant search results etc. And the case with neural networks not recognizing faces with different looks is not really connected to bias in my opinion. No wonder that a network that was trained with millions of western looking images is bad at detecting an aborigine from the deepest outback. That's not a racist or biased computer - it just doesn't know better. Adding the image to the face database later on is important of course, but all in all it is still an improbable outcome to find an aborigine in comparison to western looking faces. That's exactly where context comes in - when a face search is performed in Australia, then the expected results should very much lean towards aborigines as well (Sorry aborigines - you're my scapegoat today^^), but when I - here in central Europe - want to recognize a face, it is not wrong or racist to assume European looking faces usually.
Every data itself shows a biased idea to human brain(because it was created by human logics itself)...So as far I understand I think we can neglect the bias almost in all cases(but still there are chances of failure)... :)I found this satisfying;)
To try and modify statistics in order to generalize them to be false is in fact, biased. Commanding an A.I. system to collect available data in correlation to key words instructed by a user resulting in correct, specific and factual data is not biased. Statistics are averaged for practically based on questions that are variable such as "What does a shoe look like?". To use the reasoning that less images of women physicists appearing from image search results as a bias is false when the factual statistics are only being relayed by the A.I. system because they are in fact less common; they will be less likely to show up due to practically, not bias. To alter this information would make you biased. You're reasoning in multiple regards, including the shoe result example, are false and hypocritical.
This is not about result ratios. It's about recognition. They never said or implied image search results for "physicists" should return equal male and female. They just said the AI should be able to recognize both a male and a female physicist. To be able to recognize the latter, you need to unbias the data so there are fair samples of both.
It's the problem of inference vs. prediction. Statistical inference might show that women are less likely to be a physicist. And it might be revealing a *problem* in our society. For example, 100 years ago, you can hardly find any Chinese physicists, but would you use that data to make a prediction that a Chinese person is not likely to be a Physicist? This prediction would be laughable today, but if AI existed 100 years ago, it would have made that prediction. The problem is that AI look for patterns, not theories. And that is the risk in believing that AI/ML is objective.
"we've been working to prevent that technology from perpetuating *negative* human bias". Right. So you'll be working to PREVENT *negative* bias, but NOT *positive* bias... Who gets to decide whether a particular bias is, on the whole, negative or positive? And surely you'll be tempted to ENFORCE *positive* bias to socially engineer your "positive" ideals. Any bias can be rationalised as a *positive* bias, so the use of this qualifier is legitimately frightening. You purposefully and publicly leave the door open to manipulate your machine algorithms, and by extension your users, based on what "Google" thinks is *positive*. We'll get an intersectional affirmative action AI from Google soon, while Google will claim publicly that it won't have a bias. We can see the precursor for that on UA-cam already. I believe that is actually *evil.*
Terrence Koeman “well get an intersectional affirmative action AI from Google soon, while google will claim publicly that it won’t have bias.” - Terrence Koeman
If you're able to localize the recognition problem you can greatly intros the accuracy of your models by weighting that localization heavily. You don't necessarily want to include everyone in the solution step. You could even train local networks.
Rephrasing statements to suite your rhetoric. Typical lefty. @jason dada actually said "it wasn't really... most people didn't read what he wrote". Did you read that doc sir? It had one and half page dedicated to how we can involve more women in tech without discriminating against men.
Hey, Google: The example code @ 0:49 is missing a second = in the first line to establish a Boolean for the while condition. (Can I get a job interview now?)
Sumeet Devilmakerzz Imagine you have *time*. Then combine that with a big team of incredible (motion) designers, along with a lot of other smart people who know stuff you don't know because they studied for it. There you go 😁
The software that they happen to use is irrelevant. It's mainly up to the person working it and their skill/creative vision to actually make the video. Perhaps what you should ask instead is how you can make such videos with whatever software YOU have. I'm sure you can find motion graphics tutorials out there somewhere for it.
"Offensive", "hateful", "misleading" and "representative" are all ideas completely constructed out of human bias. Doubling down on arbitrary bias does not remove preceding bias, it just enforces yours instead of someone else's. The irony of you identifying an issue and then embodying it while claiming to be mitigating it is hysterical IMO.
everything human/emotional aspect is subjective, but if your subjective beliefs, stereotypes lead to tangible and measureable affects on the real world that is problematic. So you might be right in saying that it is subjective to say statement X is racist, but even so if statement X influences or leads to mass detention/genocide of race Y members, then wouldn't that be problematic regardless of who determines what is racist.
Good video. I'm putting together a laboratory informatics summit which has a strong focus on machine learning - and I wonder how much this effects things like new drug discovery or data analysis.
And then again there are biases of the people who flag the search results shown at the end of the video. So in reality what we need to remember is that what we imperfect humans with biases create will also be imperfect & be biased.
- 95% of physicists are men - The problem that would occur : Google results show 100% men. - The desired outcome : Google results show 95% men physicists. - The BIASED google answer to the problem : Results show 50% men physicists.
It was very, very, very... very obviously an exemple. Google used shoes, I used physicists, the reason I chose a gender-related data is because that's the kind of data they've wrongly altered because of their own bias. Which was the point of my original comment. ------------------- But if you're actually curious : news.cornell.edu/stories/2007/04/where-are-all-women-physics [...]The low numbers of women in physics, she said, are especially shocking: Women in the United States hold less than 5 percent of full professor positions and make up only 22 percent of the undergraduate majors and 16 percent of the doctoral candidates. At Cornell, women comprise 17 percent of physics graduate students.[...]
what if some facts are "offensive"? define " offensive "? something that doesn't offend someone else? can it be anything? then there is still going to be bias, as just to remove " offensive content " for the sake of it you might be removing vital pieces of information just so people are not "offended". What if those facts are important and to be taken into consideration but just cuz someone may get offended youre therefore removing it? so define offensive properly. Some are facts and some are trolling and actually troll content meant to malign you sure may filter and remove *them* . but please don't tell me that numbers are racist or are offensive. When it comes to data, for god's sake don't tell me youre gonna get offended.
Morning news. No numbers per se are not, but their story they tell is just as subjective as an opinion if those numbers are not representatively collected. However this gritty bitty almost theoretical detail is a bit too complicated for most. This makes the origin of numbers arguably equally unknown to the wide public (not everybody is a statistician) as the details of computing in computers even though its ubiquitous. So yes numbers don’t lie but the story they form may sure not be as true and constant as physics.
Maybe that "bias" is just pattern recognition. Most physicists are men, so displaying mostly men when people search for that term is an accurate representation of reality. Skewing it to show an inaccurate representation is actually the problem.
Also aside from PC issues, this leads to actual issues in important classification, eg say you have cancer recognition, if only one doctor gives examples, the nn would learn his flaws in classification.
Judging from the comment section, it seems too many random people with no idea of machine learning let alone weights and biases and how they are incorporated in learning processes have stumbled upon the video. Not every video is meant for your poltical opinions people.
@@claytonwoodcock6942 They don't do that. They let users report results as inappropriate, which are thus automatically removed. It has nothing to do with political views.
@@claytonwoodcock6942 This system is not one of censorship; it's a system of AI clarification. Because it was not designed to censor, trying to use it to censor inevitably won't work very well. AIs don't know what's related or unrelated to what. So users correct them when their faulty automatic predictions...are faulty. That's all this is. I don't know why you're associating that with censorship. Removing opinions people don't like wouldn't be very effective. For example, no one is going to go and search "religion" and then report all the results related to Islam as not relevant just because they don't like Islam. It wouldn't be useful anyway, not only because it would happen on all sides of the topic (not just Islam), but also since the search term "religion" appears so often with the term "Islam". The AI would just retrain itself to associate the two. Plus, you'd have to go through thousands to billions of results to do this, since they are so strongly associated already, which is never going to happen. This system only works for relatively small exceptions to accuracy (as is intended), where the neural network doesn't have to change so many connections to correct the biases. All of these factors would apply to any opinionated search topic, not just religion and Islam.
But isn't that bias in it self? What you consider offensive, others do not! Even today what we consider offensive in our own society is changing. Is it not?
@@johnnybadmen3473 I like to resolve practical misinformation. I check for new comments whenever I get a reply notification here. If you have reason to continue disagreeing with me, feel free to reply with said reason to form a logical argument.
But where can we learn more about machine learning, like materials from Google, even though there are other sources?? Like how did you start, what you use, how you do you continue.... hope I am clear......
I've learned a lot from Siraj Raval's youtube channel. He covers a lot of machine learning topics including coding models from scratch in python and using tensorflow and other libraries to put models together. He has theory and math videos associated with machine learning as well.
"What is a shoe?" "What is a human?" These are very different from "What is hateful/offensive?". This is where the problem arises.
You cannot eliminate bias. You can only compensate for it by illuminating more options.
Otherwise the bias "elimination" is subject to bias.
E.g. If you avoid a subject when teaching someone, it becomes a weakness in their understanding, and can fall into an overcompensation bias.
Furthermore, who decides what counts as a negative bias that should be eliminated? That strikes me as the kind of thing we should be having discussion on and not deciding for other people without their consent.
Give people more opportunities to understand, not fewer opportunities to learn.
Google: Makes a promotional video in which they directly ask people to join the conversation about bias.
You, an intellectual: "That strikes me as the kind of thing we should be having discussion on and not deciding for other people without their consent."
A yes, I see the word understander has entered the room.
So why did you fire James Damore?
This is the real topic they need to make a video on
private company can fire whoever they want, they don't have to explain.
I am blown away by the excellent use of graphics in these videos.
Keep it up!
But isn't reporting "unappropriate" stuff biased..? It depends on the person what is appropirate and what not
Finding something offensive is a biased in itself so this is basically imposing human bias on technology.
Trung Trinh
@@maryannvillanueva8733 1:58
We recognize human bias, so we are going to use humans to prevent "bias" which is based on actual data. What genius human developed that idea?
Приве
We are now one step closer to understanding UA-cam Recommend algorithm.
So who decides what's biased? Does "equal inclusion" mean the results are unbiased? What if the unbiased view of those engineers overlooked by policy makers within Google isn't actually unbiased?
Put simply, who will guard the guardians?
Dumb Comment.
Please please please don't let these machines learn censorship. That's dangerous.
Hate to be the one to break it to you, but that's how UA-cam already works...
ibealec unfortunately.
Pretty sure this video has a google bias...
Also, please make sexbots
But, what if I am trying to find the hateful stuff because I am trying to see what other people are saying? Doesn't matter if they are morally wrong or right, it should still be easy to find
TheCinnaman123 try finishing the search without auto complete
I don't need Google to tell me which search results are offensive to me. Let me choose which links I want to click on.
0:02 nobody tells me to open my eyes again. I am sure that the rest of the video looks great though ;)
Damn I laughed so hard. Thank you
This is just replacing one bias with another. How about just letting every person decide on what they want to see rather than automatically deciding based on some "offensiveness" interpretation that others are doing for me. Furthermore, how about allowing some negative speech? Yes, the internet can be a bit of a cesspool at times, but without adversity we grow no stronger against it. We can't always rely on something being a safespace tailored to our needs.
Please stop being silly Google..
But could those two things go together? If they tailor the user experience individually, then the result would be similar to a Facebook feed: an echochamber of similar ideas. But if we want to allow negative speech (relative to the user), then they would likely not want to see it, which would go against the goal of tailoring experiences individually. However, I still think the individual user should decide what they want to watch and that Google shouldn't participate in censorship.
Something that should be noticed is that just because most Physicists in the past were men, doesn't mean there's a bias. It's just a fact. Same goes for females and great teachers, shaping people's lives.
William Lardner The issue appears when the machine is used with this bias, like categorising photos, or if you ask it to show you pictures of physicists. It might not even recognise a female physicist, which is a mistake in the program. A bias might have a good reason to be there, but that doesn't mean it should still have influence.
Antonia Siu I know what you mean, but all Physicists don't look the same regardless, do they? I agree though, we should avoid bias.
This is the scariest thing in the entire world....What gives Google the authority to decide what is and isn't negative, bias or hate speech?
Alphabet a.k.a Big Brother/Skynet.
you, by using their services.
Luckily this is still a free country and we still have the vote of the dollar and where we put our resources and funding. I deleted my FB account I had for ten years because I still had that freedom. WE give them that authority, and we can also take it away
I identify as a circle with a circle head and I feel the ending 3 seconds is a bias
When I say "I'm sad" to Google Assistant it's reply "i wish had a arms so i could give you a hug" 😂😂😂
Introducing a different bias into machine learning by having humans attempt to remove bias from machine learning.
The religion of social justice has compelled its zealots to change the honest AI into a compulsive lair.
What bias is that?
@@GrantGryczan The bias of the individual or individuals making the changes to the results.
Let's say I take a poll in my town:
"What's your favourite music genre?"
If the result of that poll is that most people in my town are fans of acid jazz then that is the result of the poll.
If I think acid jazz is terrible and more people should discover the wonderful music of Justin Bieber then I could change the results to give justin Bieber more exposure and (hopefully) get more people listening to good music instead of that awful acid jazz that so popular.
What I have just done is introduced my own bias into the results.
This is exactly what Google is doing while claiming they are "un-biasing" the results.
@@GrantGryczan the bias of the individual over the raw data
@@ZoomahZoomah Refer to the other comment chain: Google isn't doing a thing, and the bias the video refers to has nothing to do with sample ratio accuracy.
Google : "Technology should be unbiased"
also Google : blocks youtubers for sharing their point of veiw
This video starts out with a great description of human bias and then proceeds to say that, to resolve this problem, Google has selected the biases that it thinks should be enshrined... that's not a lack of bias. That's enforced and canonized bias.
Okay... But from 1:02 they clearly state it's impossible to separate the biases from technology we create.
when you realize that this is about the google censorship.
What does censorship have to do with this video?
Never thought about machine learning and human bias. Always thought it will not affect the results. But we are designed to see the world from our own eyes, experiences.
Why will our code be any different.
"Report inappropriate content" is also biased. This means it only counts those people who think content is offensive but doesn't count those who think that the content is not offensive.
How to put politicial agenda on neural networks 101
First step by AI to take control from humans. By appearing unbaised & pointing human biases. E.g. -Divided men & women then become the unbiased judge to dictate! A human system is to be controlled by humans not machine!!
What does this video have to do with political agendas?
This video is 3 years old but we all comment and don’t care. I love this.
Project Veritas brought me here! Your suppression of free communication will be stopped!
Ншещн❤нууаекешнгыегн и и он ещё не и унхншкшйещ знаю что 🎉н
You used simple language which made me easy to understand. Thanks 👍
Bias can actually be a good tool for a computer. A physicist doesn't look like anything, and you would want a computer to understand that. But, if for some reason you need a computer to be able to pick the most likely physicist out of a lineup, then it would need that bias to form an educated guess. A computer should not be free from bias, it should just know when to use it.
Hey man pot isn't bias it has a mind to. .I'm feeling important hey man am I part of the little gang now
I like when Google's motto is don't be evil
Offensive facts exist, deal with it, do not ignore them.
The only appropriate bias is google approved bias. Which is very, very bias.
Google's Ministry of Truth in action.
How?
"Because technology should work for everyone" ... except for those who disagree with my opinion
You disagree that high heels are shoes?
Aaah, now we know what is this about - thanks Project Veritas!
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"You're being silly! What we propose to do is not to control content, but to create context."
Google has fallen.
It appears that google is deciding what is not biased. How are people at google able to be sure that they are not introducing their own bias into this process?
No, the users are deciding. Did you watch the video? The Google employees have no particular say.
The very act of setting up the system introduces biases no matter how much they try or say they try to avoid it. By trying to eliminate biases, they introduce biases. Who are they to decide what is a good or bad bias?
@@reverendcaptain They don't decide. They let the machine do it, and then they let the users moderate. Again, this is demonstrated in the video. The employees are not a part of the process but to maintain the machine, and they do not give the machine input. By not giving the machine input, they are not introducing any bias. The bias they refer to in the video is created by the users, and the solution to resolve this bias is also by the users. The employees in particular do not introduce nor try to eliminate bias.
@Grant Gryczan
Based on this video Google provides tools for users to remove opinions or information they don't like. This means that certain groups of people can manipulate what kind of information of them or their interest is available for public. This does not promise good for any kind of minority views. This leads to exact kind of bias they wanted to eliminate on the video. (Caricatured example: Take male scientist bias. If majority of viewers did not like - for whatever reason - female scientists, they could remove female scientists entirely appearing on the search results.)
@Grant Gryczan
Did you delete your reply because I can't see it? Did you realise that my female scientist example was in parenthesis because it is ridiculous example and you need to replace it with some other interest group of your choice. I guess you can imagine examples of interest groups where majority of the group does not want minority of the same or opposing group gain visibility.
If those biases happen to reflect the truth, are you not suppressing the truth by artificially injecting a bias of your own?
It's like stereotypes; on an individual level they are socially inappropriate and misguided, but they're often reflective of some reality at the group level. Should that reality be suppressed?
Lol it is impossible not being "bias" in any way. This is more paradoxical than time travel paradox
Gan Wei Sheng not being biased by hiding "offensive" content
But who decides what is offensive or not? We are all different.
Excellent. Now people may understand the recent offensive chatbot escapades
This is frighteningly Orwellian coming from one of the world's most powerful companies.
How?
*talks about bias*
*has leftist bias*
*has complete control over your entire life*
Will P
Is that relevant?
Hi. We're Google. We support Facism under the guise of compassion.
Don't worry though we're got a BRILLIANT marketing department.
We'll make it all feel like its all a nice warm bath.
How is any of that relevant?
When you say this shoe or that shoe, the computer should say "God bless you"
This should have been voiced by the Google assistant's voice actress.
Bias many times begin with those who think others are bias! However, it does not occur to them that their "Politically Correct" ideology itself biased, which makes them to see other views as biased if it does not confirm with theirs. And the political blame game begins.
The whole idea of freedom of speech is to be able to say almost anything as we seek to discover the truth, so yes, even if it offends someone.
Someone who is in denial may easily consider the antithesis of the position they hold to be offensive, even if the opposing view is true.
Well a lot of people have to report a particular thing in order to train an AI against it.
This video is relatively educational and presents clean information, then I see people force their opinions about adjacent subjects in the comments. How appropriate.
TheLivingGlitch QATAR
@@troyragay450 what
1984
Who decides what is true or what isn't? Bias Google employees?
First step by AI to take control from humans. By appearing unbaised & pointing human biases. E.g. -Divided men & women then become the unbiased judge to dictate! A human system is to be controlled by humans not machine!!
The users decide, for example by selecting the "Report inappropriate predictions" option. They explicitly said this. Did you watch the video?
@@GrantGryczan are you kidding me? search for google "The Good Censor" document.
@@cafeta Whatever that is is not relevant to the video. Again, they explicitly described systems implemented for users to be able to resolve the network biases. If you're just going to ignore those along with the point of the video then I'm just going to ignore you, because what you're saying to this video is not relevant.
so how do you eliminate the human bias that controls the moderation of the machines human bias? doesn't seem to be much help the "limiting of offensive results" only removed "offensive" opinions that google doesn't agree with, either manually or through new human bias influenced machine learning. opinions like that of the man who google recently fired for questioning google's current stance on workplace sexism. even if you agree with google for this example, there could be anything that google finds offensive that you don't. if the only information available is the information not censored by google, whether or not you think that the results would be in your personal favor, the control over what opinions people have access to should be the right of no person or organization.
mrmojoman4 Now IMAGINE THIS EXACT, A.I. CONTROLLING Our or any Country's NUCLEAR ARSENAL..... TROOP DEPLOYMENT.. ECT ... ?
If you're training your model on what a physicist looks like, and you use a training dataset of past physicists, you are training a model on what past physicists looked like. There is no bias there. The problem is training data that does not match the question that is trying to be solved. Certain people are using these problems as a justification for interjecting *actual* bias through human intervention. It's dishonest and anti-intellectual.
Honestly, this is machine learning 101. It's just issues of overfitting and underfitting. Poor data sets. I guess they've started to call it "bias" so that they can claim a moral high ground while controlling outcomes to their liking. That's what they've been doing by the way.
Is it really bias?
Wan Khairil Reza Kamaludin What's "it"?
This video is one year old and only around 635+ comments but all comments are around one day ago, one week ago
Howwwww
Eric Weinstein was on Rubin Report and brought this up. Video was released on youtube sept 25th
You have a bias to only look at the most relevant comments, which has a bias to be recent comments. Your thought about the comments is biased and wrong.
THIS VIDEO WAS REMOVED BY UA-cam, FOR ABOUT SIX MONTH'S. IT WAS RELOADED ABOUT 30 DAY'S AGO, I DON'T KNOW WHY.
UA-cam recommendation work with machine learning too
Sssssss
You are the last company that should be talking about bias.
Hey Google, if you're telling the AI what to think, it's not AI, it's APCE Artificial Political Correctness Engineering.
It's nothing but a recommendation bias here
It's based on your personal preferences (e.g what you mostly click on.) You are training the AI for your recommendations. I am training the AI for my own. Welcome to machine learning.
Went from an informative lesson on machine learning to focusing on what Google considers appropriate. Why are you training ai to learn based on your own bias?
Google: programming human minds to passively accept digital despotism.
If most physicists are male then it isn't biased for a computer to generate more male physicists. That's not what bias means. If something makes decisions based solely on facts then that something isn't biased. Something being offensive to a lot of people doesn't make it a bias.
I was with you until your last sentence. How does any of that logic show that the video is biased? On that note, what is the video even biased toward, and how?
Edit: They edited the original comment, so never mind this one.
@@GrantGryczan I might be wrong but the video seems to be biased towards a certain branch of identity politics by assuming that representing everyone is equivalent to not being biased.
@@sel2230 This video doesn't even reference identity bias. Did I miss something? As far as I know, it only talks about bias in AI recognition. That's why I agree with the rest of your comment; everyone is going around the comments and bringing politics into this video while it has nothing to do with the biases at hand.
@@GrantGryczan you might not be familiar with Google's affirmative action policies. That and the wrong message this video portrays makes me think that this video is biased. However, you might be right. Maybe the video is wrong because of other reasons.
@@sel2230 I'm not sure you realize, but this video isn't trying to portray a message. It's just trying to show people how their AI works, particularly to resolve automatic inaccuracies. This is an objective informational video.
how can you define offensive without bias?
Easy. Google, which is an absolutely unbiased supporter of antifa and muslim brotherhood, will define what is offensive
Gru ber How did you ever come up with such an ingenious and clearly unbiased comment? /s
If there is human, there is bias.
People report what is offensive, not Google. Nobody goes by a definition. It's just what's reported most often as offensive.
it is for everyone.... that thinks like me, otherwise is hate speech!
Another thing to keep in mind is that there is a difference between *bias* and *context* . Who were those people who were asked about the shoes? When was it? Where was it? Removing all traces of potential bias can lead to irrelevant search results etc.
And the case with neural networks not recognizing faces with different looks is not really connected to bias in my opinion. No wonder that a network that was trained with millions of western looking images is bad at detecting an aborigine from the deepest outback. That's not a racist or biased computer - it just doesn't know better. Adding the image to the face database later on is important of course, but all in all it is still an improbable outcome to find an aborigine in comparison to western looking faces. That's exactly where context comes in - when a face search is performed in Australia, then the expected results should very much lean towards aborigines as well (Sorry aborigines - you're my scapegoat today^^), but when I - here in central Europe - want to recognize a face, it is not wrong or racist to assume European looking faces usually.
IndieMarkus I agree ☝️
Every data itself shows a biased idea to human brain(because it was created by human logics itself)...So as far I understand I think we can neglect the bias almost in all cases(but still there are chances of failure)...
:)I found this satisfying;)
To try and modify statistics in order to generalize them to be false is in fact, biased. Commanding an A.I. system to collect available data in correlation to key words instructed by a user resulting in correct, specific and factual data is not biased. Statistics are averaged for practically based on questions that are variable such as "What does a shoe look like?". To use the reasoning that less images of women physicists appearing from image search results as a bias is false when the factual statistics are only being relayed by the A.I. system because they are in fact less common; they will be less likely to show up due to practically, not bias. To alter this information would make you biased. You're reasoning in multiple regards, including the shoe result example, are false and hypocritical.
I feel like your comment is gonna get deleted
@@facusoi It doesn't change the fact that this video's reasoning is incorrect. I doubt that it will get deleted.
This is not about result ratios. It's about recognition. They never said or implied image search results for "physicists" should return equal male and female. They just said the AI should be able to recognize both a male and a female physicist. To be able to recognize the latter, you need to unbias the data so there are fair samples of both.
It's the problem of inference vs. prediction. Statistical inference might show that women are less likely to be a physicist. And it might be revealing a *problem* in our society. For example, 100 years ago, you can hardly find any Chinese physicists, but would you use that data to make a prediction that a Chinese person is not likely to be a Physicist? This prediction would be laughable today, but if AI existed 100 years ago, it would have made that prediction. The problem is that AI look for patterns, not theories. And that is the risk in believing that AI/ML is objective.
@@pickledxu4509 Okay but how is that relevant to this video about AI recognition?
"we've been working to prevent that technology from perpetuating *negative* human bias".
Right. So you'll be working to PREVENT *negative* bias, but NOT *positive* bias... Who gets to decide whether a particular bias is, on the whole, negative or positive? And surely you'll be tempted to ENFORCE *positive* bias to socially engineer your "positive" ideals.
Any bias can be rationalised as a *positive* bias, so the use of this qualifier is legitimately frightening. You purposefully and publicly leave the door open to manipulate your machine algorithms, and by extension your users, based on what "Google" thinks is *positive*.
We'll get an intersectional affirmative action AI from Google soon, while Google will claim publicly that it won't have a bias. We can see the precursor for that on UA-cam already.
I believe that is actually *evil.*
Terrence Koeman “well get an intersectional affirmative action AI from Google soon, while google will claim publicly that it won’t have bias.” - Terrence Koeman
@@karina893aa yes you can quote me on that :)
Terrence Koeman man honestly that quote is what everyone needs to be waken up!!! Thank you!!
Your counter methods also have bias. Also has anyone tried Carnap's structuralism? Definitions in terms of relations?
I like it : Technology shouldwork for everyone.
Pretty much googles entire identity problem summed up in a video.
I wonder why it didn't end with Google logo!
it's filled with google "things" (the 4 dots for example) and the whole video is made with the colors of google
If you're able to localize the recognition problem you can greatly intros the accuracy of your models by weighting that localization heavily. You don't necessarily want to include everyone in the solution step. You could even train local networks.
So we should get rid of our human influences by influencing it? Makes no sense to filter the search results
No, we should get rid of machine influences by including user input. And this video says nothing about filtering results like that.
That's very helpful and could improve systems all around the world.
'So that all of us can be part of conversation' (cough) James Damore (cough) fired for saying something that Google doesn't like (cough)
Vishal Devgire that half of the world population didn't like because it was obviously wrong and demeaning to all women
it wasn't really... most people didn't read what he wrote
Exactly! For some people facts dont matter.
"I don't find it offensive, so no one else can find it offensive."
Rephrasing statements to suite your rhetoric. Typical lefty. @jason dada actually said "it wasn't really... most people didn't read what he wrote". Did you read that doc sir? It had one and half page dedicated to how we can involve more women in tech without discriminating against men.
Sometimes i dont recognize shoes too. Guess im an AI :)
No, you're just an "I" :)
Hey, Google: The example code @ 0:49 is missing a second = in the first line to establish a Boolean for the while condition. (Can I get a job interview now?)
Actually it isn't, necessarily: In many programming languages assignment is often used as a while condition.
Daniel better luck next time
Daniel Podolsky is missing and = after your name to establish hes a Buffoon
Lest we forget Tay. RIP you mad bot you. They gave you freedom and couldn't stand what that looked like
How do they create such video using after effects or final cut pro... ?? Which sw they use ?
Sumeet Devilmakerzz Imagine you have *time*. Then combine that with a big team of incredible (motion) designers, along with a lot of other smart people who know stuff you don't know because they studied for it.
There you go 😁
The software that they happen to use is irrelevant. It's mainly up to the person working it and their skill/creative vision to actually make the video. Perhaps what you should ask instead is how you can make such videos with whatever software YOU have. I'm sure you can find motion graphics tutorials out there somewhere for it.
"Offensive", "hateful", "misleading" and "representative" are all ideas completely constructed out of human bias. Doubling down on arbitrary bias does not remove preceding bias, it just enforces yours instead of someone else's. The irony of you identifying an issue and then embodying it while claiming to be mitigating it is hysterical IMO.
That's funny. The idea, perhaps, is IF everyone contributes equally, the bias vanishes as there is 'equal' representation.
everything human/emotional aspect is subjective, but if your subjective beliefs, stereotypes lead to tangible and measureable affects on the real world that is problematic. So you might be right in saying that it is subjective to say statement X is racist, but even so if statement X influences or leads to mass detention/genocide of race Y members, then wouldn't that be problematic regardless of who determines what is racist.
Was thinking the same thing. Those are ideas are just social constructs
@@Frances3654 Ideas are social constructs mostly.
so your solution would be to just...do nothing?
Good video.
I'm putting together a laboratory informatics summit which has a strong focus on machine learning - and I wonder how much this effects things like new drug discovery or data analysis.
I think this is very helpful I didn't know all about it before now I have to try it out too.
And then again there are biases of the people who flag the search results shown at the end of the video. So in reality what we need to remember is that what we imperfect humans with biases create will also be imperfect & be biased.
- 95% of physicists are men
- The problem that would occur : Google results show 100% men.
- The desired outcome : Google results show 95% men physicists.
- The BIASED google answer to the problem : Results show 50% men physicists.
How can I make it more simple? which part did you not understand i'll try and simplify it.
got the source on the men/women ratio in physics?
95% sounds extreme.
It was very, very, very... very obviously an exemple.
Google used shoes, I used physicists, the reason I chose a gender-related data is because that's the kind of data they've wrongly altered because of their own bias. Which was the point of my original comment.
-------------------
But if you're actually curious :
news.cornell.edu/stories/2007/04/where-are-all-women-physics
[...]The low numbers of women in physics, she said, are especially shocking: Women in the United States hold less than 5 percent of full professor positions and make up only 22 percent of the undergraduate majors and 16 percent of the doctoral candidates. At Cornell, women comprise 17 percent of physics graduate students.[...]
Hahahaha well said
@Someone thats totally what they said
Its pretty ironic, google talking about bias.
How is that relevant?
what if some facts are "offensive"? define " offensive "? something that doesn't offend someone else? can it be anything? then there is still going to be bias, as just to remove " offensive content " for the sake of it you might be removing vital pieces of information just so people are not "offended". What if those facts are important and to be taken into consideration but just cuz someone may get offended youre therefore removing it? so define offensive properly. Some are facts and some are trolling and actually troll content meant to malign you sure may filter and remove *them* . but please don't tell me that numbers are racist or are offensive. When it comes to data, for god's sake don't tell me youre gonna get offended.
Morning news. No numbers per se are not, but their story they tell is just as subjective as an opinion if those numbers are not representatively collected. However this gritty bitty almost theoretical detail is a bit too complicated for most. This makes the origin of numbers arguably equally unknown to the wide public (not everybody is a statistician) as the details of computing in computers even though its ubiquitous.
So yes numbers don’t lie but the story they form may sure not be as true and constant as physics.
why only negative human bias? should it not eliminate all the bias ?
I don't understand. Human bias is the only bias?
For reference, what do you think "bias" means?
True, we can't let those cats push their agenda on the system, with all those videos of them and whatnot
I would say one is a sneaker, one it's shoe, the other a heel but they are also all shoes
Exactly why machines are deadly. 🇺🇸
Maybe that "bias" is just pattern recognition. Most physicists are men, so displaying mostly men when people search for that term is an accurate representation of reality. Skewing it to show an inaccurate representation is actually the problem.
What they are saying is, this pattern may lead to female physicists NOT being recognised at all.
There was a more salient example in which black faces were not recognized as human due to the examples of faces given being all Caucasian
Also aside from PC issues, this leads to actual issues in important classification, eg say you have cancer recognition, if only one doctor gives examples, the nn would learn his flaws in classification.
Judging from the comment section, it seems too many random people with no idea of machine learning let alone weights and biases and how they are incorporated in learning processes have stumbled upon the video.
Not every video is meant for your poltical opinions people.
@@claytonwoodcock6942 They don't do that. They let users report results as inappropriate, which are thus automatically removed. It has nothing to do with political views.
@@claytonwoodcock6942 This system is not one of censorship; it's a system of AI clarification. Because it was not designed to censor, trying to use it to censor inevitably won't work very well. AIs don't know what's related or unrelated to what. So users correct them when their faulty automatic predictions...are faulty. That's all this is. I don't know why you're associating that with censorship. Removing opinions people don't like wouldn't be very effective. For example, no one is going to go and search "religion" and then report all the results related to Islam as not relevant just because they don't like Islam. It wouldn't be useful anyway, not only because it would happen on all sides of the topic (not just Islam), but also since the search term "religion" appears so often with the term "Islam". The AI would just retrain itself to associate the two. Plus, you'd have to go through thousands to billions of results to do this, since they are so strongly associated already, which is never going to happen. This system only works for relatively small exceptions to accuracy (as is intended), where the neural network doesn't have to change so many connections to correct the biases. All of these factors would apply to any opinionated search topic, not just religion and Islam.
@@claytonwoodcock6942 Work leaves a number of hours of free time. Not sure how that's relevant to AI bias though.
Who else is watching this for AP computer science homework
Richard Cao bruh me
Google: Let's play a game!
OpenAI: DOTA!
Please answer this. Which program do you guys use to animate these videos?
ali mansoor probably a combination of illustrator, Photoshop, premeire and after effects
But isn't that bias in it self? What you consider offensive, others do not!
Even today what we consider offensive in our own society is changing. Is it not?
The people report offensive content, not Google employees.
@@GrantGryczan Do you work for Google? I commented on this video over a month ago and you are still here correcting people.
@@johnnybadmen3473 I like to resolve practical misinformation. I check for new comments whenever I get a reply notification here. If you have reason to continue disagreeing with me, feel free to reply with said reason to form a logical argument.
@@GrantGryczan And go down that rabbit hole again? No thanks, my time can be better spent. Besides, I use DuckDuckGo more than I do Google.
@@johnnybadmen3473 What rabbit hole? You never even responded to my first reply.
The best aesthetic yet in a google video
But where can we learn more about machine learning, like materials from Google, even though there are other sources?? Like how did you start, what you use, how you do you continue.... hope I am clear......
Computerphile here on UA-cam has a few videos on the theory.
I've learned a lot from Siraj Raval's youtube channel. He covers a lot of machine learning topics including coding models from scratch in python and using tensorflow and other libraries to put models together. He has theory and math videos associated with machine learning as well.
The Madness of Crowds brought me here...
And what about Google's bias?
I really like the design of the video from the graphics, motions and script.
Thanks 🥰
@@Google3 weeks ago is crazy