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Shirt Without Stripes

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Re: Shirt Without Stripes

#431

Post by nitwit005 »

jedberg wrote: post #390
bartread wrote: post #221

Earlier quoted context omitted.

I couldn't quite believe your comment when I read it so I did a Google image search for "person" and the results weren't a lot better than you'd suggested. Mostly white men, a few white women, a very few black women, a handful of Asians, and multiple instances of Terry Crews. The net result of that Google search, combined with the "Shirt Without Stripes" repo, leaves me even more unimpressed with the capabilities of…

If you really want to be disappointed, search for [doctor] and [nurse]. Unless things have really changed, [doctor] will be mostly white men and [nurse] will be mostly white and Filipino women. But don't blame the AI. The AI has no morality. It simply reflects and amplifies the morality of the data it was given. And in this case the data is the entirety of human knowledge that Google knows about. So really you can't…

Those look almost entirely like stock photos or part of advertisements. It's probably just reflecting the biases of what photos other businesses like, which get the label of "doctor" or "nurse".

Any sort of image search is going to tend to be biased toward stock photos, because those images are well labeled, and often created to match things people search for.

Re: Shirt Without Stripes

#432

Post by iconjack »

Alex3917 wrote: post #212
rgovostes wrote: post #23

The point that the author is making, in a very understated way, is that all three companies have PR websites that breathlessly describe their advanced AI capabilities, yet they cannot understand a very simple query that young children can.

At least this is relatively innocuous. Until recently if you did a Google Image Search for "person" or "people", it only showed white men.

Google American Inventors and you'll get 95% black men.

Re: Shirt Without Stripes

#433

Post by ori_b »

seiferteric wrote: post #137

I have noticed in the past few years google results have become noticeable worse for similar reasons. Google used to _surprise_ me with how good it was able to understand what I was really looking for even when I put in vague terms. I remember being shocked on several occasions when putting in half remembered sentences, lyrics, expressions from something I had heard years ago and it being the first! result. I almost…

Google has gotten worse for me BECAUSE of the stuff you're talking about: It used to search everything and find the words that I cared about.

Today, it will silently guess at what I want, and rewrite the query. If they have indexed pages that contain the words I put in, but don't meet their freshness/recency/goodness criteria, they will return OTHER pages with content that contains vaguely related words. "Oh, he couldn't have meant that, it's from 6 months ago, and it's niche!"

They'll even show this off by bolding the words I didn't want to search for.

So, if I'm looking for something that isn't popular -- duckduckgo it is. It doesn't do this kind of rewriting, so my queries still work.

Re: Shirt Without Stripes

#434

Post by waltpad »

rhizome wrote: post #356
albertzeyer wrote: post #243

Why should it not be possible to solve this with statistical methods? The model just needs to be able to understand the important meaning of "no" in here, in the context of the whole sentence. I would guess that most modern NNs from the NLP area (Transformer or LSTM) would be able to correctly differentiate the meaning. The problem is, I think there is no fancy NN (yet) behind Google search, and the other web searche…

> The model just needs to be able to understand the important meaning of "no" in here, in the context of the whole sentence It's easy to say, isn't it? Unfortunately, sticking the word "just" in there doesn't affect the difficulty. I do it all the time, too. That said, "meaning" is not statistical.

> That said, "meaning" is not statistical.

Are you sure of that? After all, we don't have all the same interpretation for every word in the dictionary. Ask a hundred person in the street - well perhaps not these days - the meaning of the word "meaning", how many different explanations will you get? And will you be able to reduce them all to the same "fundamental" meaning?

Re: Shirt Without Stripes

#435

Post by rurp »

natefox wrote: post #168
davesque wrote: post #89

Earlier quoted context omitted.

Maybe you mean, "Please don't imagine a pink elephant." Imagining a non-pink elephant seems pretty easy.

Along these lines, I once heard somewhere that people do not process the word 'dont'. As a coach, I've had to shift my vocabulary to focus on the 'do's rather than the 'dont's Eg: If you're doing a sport where leaning forward is bad, avoid telling yourself 'dont lean forward' as your mind only hears 'lean forward', therefore reinforcing the thing you're trying to avoid. Alternatively, tell yourself 'lean back' or 'st…

Interestingly I've found this same approach from good coaches across completely different niche sports. I imagine this phenomenon has been discovered a number of times by various smart people. It certainly wasn't intuitive to me, but since learning to use affirmative advice in real-time sport situations, my advice got noticeably more effective.

Re: Shirt Without Stripes

#436

Post by pbhjpbhj »

bartread wrote: post #221
Alex3917 wrote: post #212

Earlier quoted context omitted.

At least this is relatively innocuous. Until recently if you did a Google Image Search for "person" or "people", it only showed white men.

I couldn't quite believe your comment when I read it so I did a Google image search for "person" and the results weren't a lot better than you'd suggested. Mostly white men, a few white women, a very few black women, a handful of Asians, and multiple instances of Terry Crews. The net result of that Google search, combined with the "Shirt Without Stripes" repo, leaves me even more unimpressed with the capabilities of…

4 of my top 7 images (the top line) are Greta Thunberg in a search for "person". First viewport is 11 men, 11 women, 1 stick person, of which there are 4 Thunbergs, 4 Trumps, 2 Crews. People seem to be if they got major "person" awards like "most powerful person" or "person of the year".

There's not much diversity, assuming Terry Crews is from USA, then all the first viewport full of images are Western people; except Ms Thunberg they're all from USA AFAICT [I'm in UK].

The first non-Western person would be a Polish dude called Andrzej Person (the second Person called Person in my list after a USA dancer/actress), then Xi Jinping a few lines down. The population in my UK city is such that about 5/30 of my kids primary and secondary school, respectively, classmates have recent Asian (Indian/Pakistani) heritage. So, relative to our population, there are more black people, far fewer Indian-subcontinent no obviously local people.

Interesting for me is there are no boys. I see girls, men and women of various ages but no boys. 7 viewports down there's an anonymous boy in an image for "national short person day". The only other boys in the top 10 pages are [sexual and violent] crime victims.

The adjectives with thumbnails across the top are interesting too - beautiful, fake, anime, attractive, kawaii are women; short, skinny, obese, big [a hugely obese person on a scooter], cute, business are men.

Re: Shirt Without Stripes

#437

Post by albertzeyer »

alberth wrote: post #409
DenisM wrote: post #197

This problem is known as "attribution" - you have a "no" or "without" in the sentence, but you don't know where it belongs. One could (and one does) argue that the problem cannot be solved with statistical methods (ML), especially not in any domain where accuracy is required, such as medical recored analysis: "no evidence of cancer" and "evidence of no cancer" are very different things. Zooming out, the language fiel…

The # 1 google result for “Shirt without stripes” is this very own HN post https://www.google.com/search?q=%22Shirt+without+Stripes%22&

I guess, even in the original results, the problem is not really that Google search was not understanding the meaning of the search term (which is possible with today's models). Rather, it was a bit confused about what you are really searching for here. Maybe a comparison of shirts with and without stripes? The search query was just unusual, and it is not too unreasonable to guess that the query was not meant literally. At least this is a valid possibility, that the query was not meant literally. So it is reasonable to just return some results which might be related to the query, which will also be shirts with stripes.

If you argue this is bad behavior: Maybe we need a web query which really only takes the query literally. Putting the query in quotes will not quite have this effect for Google. Maybe some other syntax?

Re: Shirt Without Stripes

#438

Post by waltpad »

glup wrote: post #397
DenisM wrote: post #197

This problem is known as "attribution" - you have a "no" or "without" in the sentence, but you don't know where it belongs. One could (and one does) argue that the problem cannot be solved with statistical methods (ML), especially not in any domain where accuracy is required, such as medical recored analysis: "no evidence of cancer" and "evidence of no cancer" are very different things. Zooming out, the language fiel…

As a postdoc in computational linguistics, my go-to example for talks is asking Siri not to show me the weather.

Has any of these talks been published?

Re: Shirt Without Stripes

#440

Post by [deleted] »

joshspankit wrote: post #426
pbhjpbhj wrote: post #417

Earlier quoted context omitted.

As someone else said you don't know that's wrong for what Amazon are optimising. If they find people [with your background profile] who buy shirts are susceptible to buying sweatpants, they might also find that if the seed you with "sweatpants" as an idea up front that the repeated presentation of sweatpants in "people who bought X also bought Y" sections is more effective. That's the sort of thing I'd expect Amazon…

Tbh, I feel like the underpinning “problem” is that more and more these marketplaces are optimizing for what they want to sell, and seeming to ignore blatant requests. I’m an odd one that I already know specifically what I want to buy before I search for it, but I’m certainly not the only one (and I think everyone has done that at least once).

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