Use of AI in the fashion industry
nytimes.com
nytimes.com
When a human designs something, there's often intent involved; there are design constraints and social context involved. I don't expect statistical ML (which is good at interpolation) to cross these gaps without integration with symbolic ML (which is good at extrapolation).
Though maybe I'm biased since I work in a symbolic AI lab.
For every new design you see, there may be 100 or 1000 that were thrown away. All of those discarded designs cost money regardless of if they were used or not.
Pink being the color for a season is based not on rationality but on a decision made by the fashion industry at large (in a fuzzy matter)
Don't think of AI as the brand but as the designer (the actual person making the (ex.) pink color of the spring.
Nutella did it with packaging.
https://www.dezeen.com/2017/06/01/algorithm-seven-million-di...
A simple fix would just be to inline all the content, like all the little ol’ two-column responsive sites do. In light of that obvious solution, they put a modal on it and compromised their content.
Of course when the companies then implode because the technology can no way make up for the resulting skill drain, said managers will have moved on to a new position, having sold the layoffs/technology as evidence of their “superior business accumen.”
In the future (and even now) careers are going to be defined by how well you can form relationships (and therefore sell) i.e. the things that will be hardest for machines to do.
My understanding is spreadsheets didn't so much reduce accountant employment as change the job from determining the facts to predicting the future; more 'what-ifs.'
Even though we have calculators we still make kids learn basic math in school because it is necessary for doing the higher level work.
I suspect it would be the same here. Even more schooling to learn what the computer already knows, so that you can do novel work.
EDIT: Although I suppose that these professionals would need at least some practise of manual work too, to be able to monitor the machines' output.
And on the other hand, the average doctor's interpersonal skills will probably improve ?
But she also makes a good point — even if the computer is better, in today’s lawsuit happy America, it will be a long time before anyone will accept a result that wasn’t at least reviewed by a human.
A metric like that is a piece of data. So is anything a machine is going to produce. It's going to come in a different form, Oracle machines in some ways seem to be an actual thing these days, in that I have to ask myself why - why do all the words I search line up in this specific way? Why does that produce some thoughts I have? How do I know what I know? How can I test that?
I think humans can adapt to anything. I think we retain that flexibity as long as we are up for the challenge. That may seem like common sense or folk wisdom, but, there's probably good reasons stuff like that sticks around.
Saying to your radiologist friend that the computer is better and faster than she is flat out puts the entire security of her future - everything she has built into - on a coin toss. Of course she's going to react defensively. If you punch your hand into someone's chest and hold their heart out in front of them - yes, they will likely have difficulty thinking objectively.
People can adapt. It is often very challenging. But it's often also worth changing, if the question of progress versus stagnation is the thing at stake.
People who go into medicine want to save lives, so work with that foundation. Rather than who is going to get sued, direct the conversation towards how many more lives can be saved. It's the same argument as self driving cars. The problem is as we age, we think we have control over permanent stuff.
If we crash the car, that's our fault. If the car crashes the car, that's something we have no control over. But sometimes we might have a random seizure. We don't think about those probabilities when it comes to us driving the car versus the car driving the car, because we become accustomed to a context. But that's just an illusion until shit changes. I'd rather be aware of the easy and obvious changes in a conservative fashion, than totally ignorant to the hard ones until catastrophe I didn't see coming happens.
These are things that are core to people who don't understand computation, and they are core to ego - what makes the lives we live better than the lives we compare ourselves to? That's the lion inside of us, that doesn't give a shit who gets ripped to shreds (or simply can't afford to think about it). I know I am a good person because I have hurt less than all the others. But that's not true. I tell myself this, but is this a thing I can prove?
There are profound arguments to be made about why a machine can do a better calculation than a human does. It has access to more information. If people can't believe that, that's their own ego.
Create a job called computer science lawyer, make sure the judge understands computer science, explain the computation to a jury in a way that explains how the algorithm was designed, align that with present understanding of psychology. Checks and balances.
I was told by a surgeon that this happens because radiologists are generalists (looking for strong evidence of different types of issues all over the body) while surgeons are trained to know the specific issues that happen in few parts, even if they don't show up clearly in MRI/x-rays.
AI should be able to take data from all the specialists to make a better generalist than human-trained radiologists. Integrated AI system should immediately read an MRI/x-ray/ultrasound and spit out possible issues. I can imagine an x-ray or ultrasound video feed hooked to the cloud that shows in real-time possible diagnoses and highlights the areas of concern. Ultrasounds are safe and this could even be a consumer device. Just like 3D-ultrasounds and 23&Me are for 'entertainment' and not medical solutions, ultrasound-with-AI can be a good tool for at-home what-ifs. It could be a great prenatal monitoring device.
* I know a lot of surgeons personally. Didn't cause a trillion dollar insurance claim.
We live in a sad state of affairs in which this disclaimer is necessary. :(
Just curious, is there a way you can get this fixed? Or do you have to live with the pain?
In the meantime, I keep monitoring these studies on mesenchymal stem cells for disc regeneration, hoping one of them makes it to clinical trials :(
One cool thing I learned about is the existence of IONM: https://en.wikipedia.org/wiki/Intraoperative_neurophysiologi...
I felt pretty comfortable knowing that things would flash red and beep if anyone got close to my spine during the surgery.
Close friend of mine with multiple lumbar herniations swears by stretching regimen like frequent yoga. Maybe that can help in the meantime. Good luck!
Radiology requires a "theory of the body", so to speak. You can't just look at the image in isolation. You often need detailed knowledge of the patient's clinical situation, and some actual reasoning. My guess is that that's why the surgeons got it right in this case (they are more familiar with the complaints of the patient and with the "live" anatomy of that region).
This doesn't mean that radiology can't be automated. It just means that to be a good radiologist, you might need to be a general artificial intelligence, capable of graduating from medical school.
This is different from something like classifying moles into benign, malign and high risk. That's something that can be determined from the pixels of a picture (even by human dermatologists, through experience or by following certain simple algorithms), and has no relationship to the rest of the patient. This means that automating mole classification is kinda like automating chess. Automating radiology looks more like automating the command chain for WW2.
On the other hand, pathology (looking at tissue samples through the microscope) seems much easier to automate. It relies heavily on pattern recognition and IMO (I'm not a pathologist either, although I've spent time in a pathology lab) it's less dependent on the clinical data of the patient. It's almost as if the doctor were looking at the image and nothing else, and the kinds of pattern doctors are something that might be automated. This is of course a simplification, and sometimes clinical judgement is important even in pathology.
None of this means that medicine can't be automated. I'm just trying to convey some of the difficulties you might have in automating radiology, as opposed to other areas of medicine.
And in any case, my criterion for difficulty of automating is "does it seem to require a general artificial intelligence or not?". If you have a general artificial intelligence completely indistinguishable from a human, then all bets are off.
What is going to continue to happen is what is already happening now: Less work wasted on bullshit, more potentially interesting findings surfaced for humans to examine. Same type of thing I was working on 2011 (helping lawyers with discovery, edit: no I confused things. Back then I was helping companies scan internal communication for automatic skill mapping), only better.
I do not think our society which has recently (and ongoingly) had someone work in one job function (often at one company) for 30+ years is ready for the fast paced change of needing to change jobs every few years.
Look at the rate of displacement in tech of technologies and frameworks. Try being an Angular developer for 20 years... I think people in software have come to expect rapid change because its the nature of the game, but that rate of change is unreasonable to be endured by every industry everywhere.
The pace is not increasing. There have been radical changes, as much as in the last few hundred years.
Two "poster children" of technological advancements (AI and nuclear) are always behind the corner, but never here. Even if they were here, there would be no catastrophe, as much as there hadn't been with green energy, and transistors.
> Look at the rate of displacement in tech of technologies and frameworks. Try being an Angular developer for 20 years...
This is irrelevant; Angular or not, the software engineering market is evergreen, even with poorly skilled software engineers (I do know some).
This example is actually a counterargument to the thesis: displacement of technologies in this field did not lead to displacement of jobs.
We definitely do have real non-imaginary problems to focus on, but we shouldn't just ignore future problems. That's Hyperbolic discounting at its worst
Do you really think it's not worth thinking about the future and trying to predict problems that might occur, and preparing for them beforehand? Isn't not doing this one of the reasons we have real problems now? (Only some real problems, of course, others have nothing to do with this).
You're free to think about it if you like but don't be surprised if no one else shares your concern.
Unemployment is a prety bloody obvious problem that might occur if automation increases.
We also have historical data of jobs that have disappeared with various levels of success in retraining. This time there's legitimate and serious doubts that the employees affected by automation will be able to retrain at all, because several low-skill type of jobs that were retraining possibilities are also targeted by automation.
I completely agree!
The reason I think this is an issue with thinking about is:
1. Logic and common sense make a good argument for automation eventually replacing all jobs.
2. Most arguments against this amount to "historically this never happened even when people thought it would". This is a weak argument for several reasons (the period we're taking about is small, there's no reason to think history has to repeat itself here, etc).
3. Many smart people think this is a problem, including economists, including people from other fields.
If this doesn't make this problem worth thinking about, what does?
Meanwhile, we have real fucking problems right now:
1. Sky high housing prices. 2. Extreme wealth disparity. 3. Environmental degradation. 4. Cybersecurity failures everywhere, just as everything goes autonomous or otherwise cyberphysical. 5. Information operations threaten both democracy and the openness of the internet.
You can still make $100k a year editing English. The demand for talent is sky high, it's investments in education and society that will help us, not fretting over how AI will take away jobs long before we can do anything about it.
Wealth is moving around less because we don't need to spend (i.e. distribute) as much as we have in the past to generate more wealth. So, I think wealth disparity is a strong predictor for unemployment. I also think unemployment is the wrong word because it paints a false dichotomy. There's a not a huge lifestyle difference between making $20,000 a year and $0 a year (since the government steps in), compared to making $20,000 and $80,000 a year; and then $80,000 and $200,000.
One reason housing prices are so high right now is because people (mistakenly IMO) view houses as an investment. NO one wants to lose money on a sale. Another reason (for some areas) is probably because of the productivity gains. Since we need to distribute less to make more wealth, we've further centralized our economy into smaller pockets of land (i.e. cities).
So again, I think it's the same problem.
The only employers paying that much are old-school publishers that are a bit of a hold-out but will eventually give way. As a translator often doing full-length books, I have witnessed some big publishing names severely slashing the amount they pay for editing (by doing things like outsourcing the job to India), and they don’t worry about any drop in quality because it is felt that in a web-heavy world, the public no longer cares too much.
It is depressing as fuck for me as a translator, because I put a lot of effort into my translations and I wish they would get the same level of love at the next stage of the publishing process, but this is the trend of the future.
Also, I feel lucky to still have work as a translator because many clients today are running the text through Google Translate and then just paying a native speaker to clean up the text for less money than they would have to pay a translator. Obviously that is not common in the mainstream publishing world, but it is increasingly happening with the marketing materials and technical manuals that are a translator’s daily bread and butter. “AI” is already hitting businesses based on human language hard.
As for translation quality; I care. Others do too. though you're right that many don't. In the long run quality wins though.
And I don't agree that it's pure speculation - we do see how many jobs(in full or in part) could be, and may be on their way to being automated.
On the other hand, we rarely hear reasonable speculations on what would be the jobs that would replace them.
Considering the creativity of the human mind (and of various authors), and our love for speculation, that's somewhat worrying.
The burden of proof is not on the trend continuing, but on it slowing down for any reason.
Nobody can predict those numbers; any number about unemployment is essentially made up. And fallacious as well, according to the lump of labour fallacy.
In the meanwhile, the industrial revolution (of whom automation is part of), in its 200+ years, hasn't caused any death of political/economic/social systems.
This move towards automating thinking will not follow the same trend.
Communism was a direct response to the wealth inequality of the industrial revolution. That was one of the most disruptive political/economic/social upheavals of all time.
Hasn't it? It completely killed off mercantilism and mostly killed off monarchism.
Advances in politics made monarchies less relevant, not industrialization by itself, with France, the US and later Russia being the key examples. The US and Russia industrialized later than France and still-monarchies like the UK, Belgium, Denmark etc. Industrial giant Germany lost its king by losing a World War: despite industry, not because of it.
It not only killed off most pre-capitalist systems, it also mostly killed off the original system named “capitalism” (mostly in favor of modern mixed economies.) It also both spurred and then killed off Leninist Communism.
For example, can Siri or Alexa delete an specific phone number from a contact? Like "ok Google, delete home number from X" is not possible right now.
Honestly I see more and more bullshit work created every day. Go back 2 centuries and I doubt anyone was doing much bullshit work at all.
With the human you can have a conversation that will hopefully avoid similar confusion in the future which eases the frustration for many. How long before machines allow us to do the same? My bet is months, a year or two at the outside. After all, we already have conversational interactions. Building on those and tying an intent interpretation to a clarifying correction provides high information training data. There's already a swath of old, well understood ML techniques -- mean subtraction, singular value decomposition, boosting, etc. -- aimed at differentiating information from data. Instantaneous classification of responses as errors followed by information on a better response? That sounds like training gold.
I think the three most popular voice assistants (Siri, Google & Alexa) do for the most part get the basic commands right and even some complex ones.
The struggle I think with using voice assistants for me is the human interaction. When I am in a social setting or walking outside on the street I can't see people using it. When I am alone or maybe with a significant other I can see it being used a lot. I rarely see people actually using Siri on a train or when they are out and about.
Besides, the article, which is very poor and click-baity, starts with a factoid (algorithms designing shirts) and then steers into something completely different - big data.
> Why do the media keep running stories saying suits are back? Because PR firms tell them to. One of the most surprising things I discovered during my brief business career was the existence of the PR industry, lurking like a huge, quiet submarine beneath the news. Of the stories you read in traditional media that aren't about politics, crimes, or disasters, more than half probably come from PR firms.
> I know because I spent years hunting such "press hits." Our startup spent its entire marketing budget on PR: at a time when we were assembling our own computers to save money, we were paying a PR firm $16,000 a month. And they were worth it. PR is the news equivalent of search engine optimization; instead of buying ads, which readers ignore, you get yourself inserted directly into the stories.
Sounds like a long winded way of describing a GAN.