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The emergence of AI in Fashion – good or bad?
With fast tech adoption and integration, the $3T global fashion industry has begun to intertwine the physical realm with a new digital world.
From fashionable wearable tech accessories to connected jackets, there are multiple digital applications that the fashion industry is adopting.
But from all the digital realm, AI has the highest potential to bring some of the most revolutionary types of innovation to the 21st-century fashion industry.
At The Right Time, For The Right Price
By augmenting the mobile e-commerce side of things, AI has enhanced the quality of search results, through automatic image processing and better recommendations.
Mobile-based AI apps are improving year by year, driven by significant investments from e-commerce giants such Walmart, Amazon, and Alibaba, allowing buyers to find the right garments and accessories, at the right time, and for the right price.
AI Can Predict Trends And Styles
Another landscape of the fashion industry that the AI sees fast adoption is the domain of fashion styles and future trend prediction.
Previously led by fashion designers, trend spotters, artists, VIPs, and influencers, the trend prediction side of fashion is slowly taken over by data scientists.
With the help of science such as prediction algorithms, the AI can draw inspiration from the world of art to uncover new insights and even redefine the core structures of fashion design, according to social constructs and cultural backgrounds.
Also, the adoption of AI in fashion can provide unlimited personalisation and customisation, according to the wearer’s biometrics, previous experiences, purchases and even social background.
The AI can automatically create iterations based on the digital facet of the buyer (social media presence, likes, dislikes, engagements, preferences, etc) and design clothes that haven’t been designed yet, specially designed according to each consumers’ demands.
Potential Issues With AI In Fashion
There have been various technology integrations into the fashion sphere, especially in the last decade.
Wearables, smart materials, connected sensors, and yet, most arguments against tech in fashion come from the idea of the low demand for such integrations.
Equally, when it comes to the use of AI, voices are arguing that relying on algorithms to predict future trends and design new fashion garments could only be detrimental and counterproductive.
According to these voices, technology can only take us so far.
And, that’s where the criticisms about AI in fashion begins.
To them, only humans can be creative, while the human-made algorithms can only be programmed to perform specific jobs.
And surely that is the case if the AI is seen as another tech tool in the hand of the designers of fashion.
However, this is an issue of perception as if the AI is no longer just a tool in the hands of the fashion designers but a salient, independent-thinker, globally-connected to all fashion, art, design, history, and cultural databases.
The AI is an autonomous entity, a modern fashion designer that can learn, improve, create, and even bring new ideas to the market.
So given the choice, human-made fashion or AI-made fashion, which one would you choose?
AI Fashion Design – New Era Of Creativity?
Truth be told, ‘robots’ are coming.
But rather than nudging out the need for humans, artificial intelligence might stand to enhance the creative process.
Or so the experts say.
The implication of AI on design is a major theme of the 21st century, with experts from many fields discussing AI’s entanglements with fashion, design, media, art, and beyond.
Body Shaped Clothing
Entrepreneur Camilla Olson was in town to promote her fashion-tech software solution Savitude, which uses AI to recommend clothing based on a shopper’s shape and proportions.
Before Savitude, Olson founded two predictive modeling companies and designed an eponymous fashion label, both of which informed her insights into solving fashion’s fit issues.
“People with mathematical appreciation will look for perfection and ‘overkill’ in the fit problem. But, if you have expertise [in fashion], you know where to draw the line in product design. You have a gut feeling of what the market needs,” said Olson.
Olson’s perspective reflects the growing tension between humans and machines.
As science gets smarter and is able to make recommendations on what is most likely to sell, traditional approaches are facing irrelevance.
Humans’ Take A ‘Defensive’ Role
Fashion designer Gretchen Jones, who is the former fashion director of womenswear at Pendelton Woolen Mills, found that her role as a designer had become more ‘defensive’ than proactive.
“I was fighting against big data that would often negate the creative design directions,” Jones said. “I was speaking through my gut and they had paperwork that could prove another black mock turtleneck was the thing that sold. But rarely can a customer tell you what they want that hasn’t been created yet, and that was stifling my ideation.”
Jones’s solution was to pursue a master’s degree in fashion at the University of Arts London, where she researched the role of data in the fashion business.
What she found was surprising: she learned that data analytics can be valuable in empowering the creative process if the business side invites the creative side to participate.
AI Creativity Is Illogical And Abstract
“It’s not just guys in suits or Mark Zuckerberglooking-like dudes,” Jones says. “We need to disrupt data; it’s a tool, but not the only thing.”
Human creativity isn’t algorithmic, it is illogical and abstract.
Yet, we can use AI to overcome the limitations of our minds.
Designers, she said, are wise to acknowledge that customers feel that aesthetic choices are an extension of their identities and that a designer is designing for them, rather than creating a vision that is delivered to the customer.
In this way, Jones found that data could help designers understand the emotional connections that customers have with a brand.
Jones added that leaning too heavily on either the creative or the business side, whether that’s expecting a miracle by appointing Raf Simons as the chief creative officer of Calvin Klein, or former Starbucks executive Adam Brotman as president and chief experience officer at J. Crew — will not save fashion.
“Dictatorial creativity is a failure,” she says.
The Age Of AI Influencers?
Actor and entrepreneur Brooklyn Decker, who co-founded the digital wardrobe app Finery with Whitney Casey, think that artificial intelligence will take over the role of the fashion influencer, using the computer-generated “influencer” @lilmiquela (who has 1.1 Mil Instagram followers) as an example.
“This person can be anywhere and fit any size, and appeal to any audience, all based on the data [the brand] layers on top,” says Casey.
“And, if the content is interesting enough, I don’t think she becomes [advertising cartoon] ‘Tony the Tiger,” completes Decker.
But experts suggest that in certain cases, it is possible for an algorithm to mimic human intuition.
Jenna Niven, the creative director at advertising agency R/GA, explained that “the gut” is the brain’s organic algorithm.
Because a person’s knowledge base is limited to one worldview, humans can lean on AI to enhance creative capabilities by creating associations between huge amounts of data.
The increase in the number of possible designs leads to more creativity, as designers see more possibilities and inspiration.
“I don’t think human creativity is algorithmic. Creativity is ingrained, over time, in an elusive thought process that happens deep in the sub-conscious. The rest is illogical and abstract, but we can use AI to overcome the limitations of our mind,” Niven thinks.
At a conceptual level, fashion designers could look to AI to generate designs, in a way similar to what Google did with DeepDream, which used computer vision to alter images.
Taking Advantage Before The Curve
“AI is taking all possible combinations and release them as inspiration. Funnily enough, fashion is one of the few industries that is taking advantage of AI before the curve,” concludes Niven.
Although algorithms aren’t generally creating new garments, they are being used to educate designers about what is needed in the market at companies such as True & Co., RocksBox, Rent the Runway, and Amazon.
Stitch Fix uses data to both inform designs for its in-house labels and to scale the capacity of its 3,400 stylists, who lean on AI to curate an assortment of product recommendations.
Eric Colson, who is the chief algorithms officer at Stitch Fix, firmly believes that human designers are still very much the curators of fashion, but that machines can expand the number of possibilities that a human designer can consider.
“The increase in the number of possible designs leads to more creativity, as designers see more possibilities and inspiration,” Colson says. “Because apparel is both personal and emotional, a design has to strike a chord with a fashion designer before it goes into production.”
He also thinks that machines can estimate the probability of a design’s success, although it’s still difficult to predict which totally new concepts will succeed.
In other words, predicting the popularity of “the cold shoulder” is “revolutionary,” but tweaking that concept with elements such as back and side cutouts is “evolutionary.”
AI Fashion Design – The Problem of ‘Too Much’
“Machines can capture elements of style and allow us to manipulate them further. Imagine saying, ‘Take that skirt by Theory, but add a Kate Spade touch.’ Deep learning algorithms can, in theory, do such things,” Colson said. “It’s able to learn what makes Kate Spade, Kate Spade. Once they learn it, they can apply it to anything.”
Finally, Niven, of R/GA, had some encouraging news for (human) designers worried about proving their worth: “If you look at something that is mass-produced, it ends up losing value,” she says.
“So if we are constantly producing garments out of an AI machine, the garments produced by AI are going to be devalued, and hence the value of a garment produced by a human is actually going to increase.”
Is The World Ready For AI Designers?
Can you imagine a salient AI fashion designer?
As futuristic as it might sound, this is happening as you read this.
Three years ago, when Amazon Echo’s algorithm was introduced to the market, with its ability to advise you on the outfits you wear, many envisioned a future of AI fashion styles.
The era of AI algorithms turned fashion stylists didn’t last long.
AI Turned Influencer
Well, AI fashion stylists didn’t go away but instead transformed into a more human-like form, such as Miquela, the virtual influencer.
As such, nowadays, it has become reasonable to expect not just advice from AI and other virtual entities, but new garments created by algorithms presented as AI designer fashion.
‘There nature of [AI] classes in active development and used at the moment is enormous. Sadly, it seems the fashion industry is the last one to adopt AI,’ says the Founder and CEO of ‘Save Your Wardrobe’, Hasna Kourda.
“The industry is still doubtful about the role of ‘digital’ in fashion as a whole, not just the AI designer fashion,” continued Kourda.
The AI Designer Fashion – A Passing Trend Or Takeover?
However, if the trends we see keep going, in a not so far future, the only humans involved in the process of fashion making will be the software developers.
AI designer fashion garments created by algorithms listening to commands from stylistic algorithms and carried by ‘autonomous’ drones, also driven by algorithms.
So, what’s left for humans?
AI Creates Unexpected Material Breakthroughs
Few recognise the vast implications of materials science.
For example, according to Omkaram Nalamasu, CTO of ‘Applied Materials’, to build a 2020 smartphone in the 1980s it would cost about $110 million.
Also, it would require almost 200 kilowatts of energy, compared to 2kW per year today.
Finally, the device would be 14 meters tall. That’s the power of materials advances.
Materials science has democratised everything, from smartphones to fashion.
It has brought portable technology to the pockets of over 3.5 billion people and has dressed the entire world without depleting its resources.
Materials science stands at the centre of several breakthroughs across multiple industries: energy, future cities, transit, fashion, and medicine.
And at the forefront of Covid-19, materials scientists are forging ahead.
Working with biomaterials, nanotechnology, and other novel materials to accelerate sustainable solutions.
As the name suggests, materials science is the branch devoted to the discovery and development of new materials.
It’s an outgrowth of both physics and chemistry, using the periodic table as its grocery store and the laws of physics as its cookbook.
And today, we are in the middle of a materials science revolution.
In this article, we’ll unpack the most critical materials advancements happening now.
Let’s dive in.
The Materials Genome Initiative
In June 2011 at Carnegie Mellon University, President Obama announced the Materials Genome Initiative, a nationwide effort to use AI and open source to double the pace of innovation in materials science.
Obama felt this acceleration was critical to the US’s global competitiveness and held the key to solving significant challenges in clean energy, national security, and human welfare.
And, it worked.
The initiative used AI to map hundreds of millions of different possible combinations of elements, such as hydrogen, boron, lithium, carbon, and many more.
The initiative created an enormous database that lets scientists play a kind of improv-jazz with the periodic table.
This new map of the physical world lets scientists combine elements faster than ever before and is helping them create all sorts of novel components and materials.
And an array of new fabrication tools are further amplifying this process, allowing us to work at altogether new scales and sizes, including the atomic scale, where we’re now building materials, one atom at a time.
Biggest Materials Science Breakthroughs
The AI has helped create the ‘metamaterials’ used in carbon fibre composites for lighter-weight vehicles.
AI advanced alloys are found in durable jet engines and even in human implantables.
With the help of AI, we also see breakthroughs in energy storage and quantum computing.
In robotics, new materials are helping us create the artificial muscles needed for humanoid, soft robots—think Westworld in your world.
Let’s unpack some of the leading materials science breakthroughs of the past decade.
Nanotechnology is the outer edge of materials science, the point where matter manipulation gets nano-small.
That’s a million times smaller than an ant, 8,000 times smaller than a red blood cell, and 2.5 times smaller than a strand of DNA.
Nanobots are machines that can be directed to produce more of themselves or more of whatever else you’d like.
And because this takes place at an atomic scale, these ‘nanobots’ can pull apart any material: soil, water, or air, atom by atom.
Then, it can use these now raw materials to construct just about anything.
Progress has been surprisingly swift in the nano-world, with a bevvy of nano-products now on the market.
Never want to fold clothes again?
Nanoscale additives to fabrics help them resist wrinkling and staining. Don’t do windows? Not a problem!
Nano-films make windows self-cleaning, anti-reflective, and capable of conducting electricity.
Want to add solar to your house? We’ve got nano-coatings that capture the sun’s energy.
Nanomaterials make lighter automobiles, aeroplanes, baseball bats, helmets, bicycles, luggage, power tools—the list goes on.
Researchers at Harvard built a nanoscale 3D printer capable of producing miniature batteries less than one millimetre wide.
And if you don’t like those bulky VR goggles, researchers are now using nanotech to create smart contact lenses with a resolution six times greater than that of today’s smartphones.
Right now, in medicine, drug delivery nanobots are proving especially useful in fighting cancer.
Computing is a stranger story, as a bioengineer at Harvard recently stored 700 terabytes of data in a single gram of DNA.
On the environmental front, scientists can take carbon dioxide from the atmosphere and convert it into super-strong carbon nanofibers for use in manufacturing.
If we can do this at scale—powered by solar—a system one-tenth the size of the Sahara Desert could reduce CO2 in the atmosphere to pre-industrial levels in about a decade.
Thanks to AI, the applications are endless and are coming fast.
Moreover, over the next decade, the AI’s impact is about to reach unseen heights, on all industries.
Next Level Batteries
The lithium-ion battery, which today powers everything from our smartphones to our autonomous cars, was conceived in the 1970s.
It couldn’t make it to market until the 1990s and didn’t begin to reach maturity until the past few years.
An exponential technology, these batteries have been dropping in price for three decades.
The price has been plummeting 90 per cent between 1990 and 2010, and 80 per cent since.
Concurrently, they’ve seen an eleven-fold increase in capacity.
But producing enough batteries to meet demand has been an ongoing problem.
But, with the help of AI Tesla has stepped up to the challenge as the company’s Gigafactory in Nevada churns out 20 gigawatts of energy storage per year.
Tesla is now marking the first time-ever lithium-ion batteries at an industrial scale.
Musk predicts 100 Gigafactories could store the energy needs of the entire globe.
Other companies are moving quickly to integrate this technology as well.
For example, Renault is building a home energy storage based on their Zoe batteries.
Then, BMW’s 500 i3 battery packs are being integrated into the UK’s national energy grid.
And, Toyota, Nissan, and Audi have all announced similar AI pilot projects.
Right now, lithium-ion batteries play a significant role in renewable energy storage by bringing down solar and wind energy prices to compete with those of coal and gasoline.
Derived from the graphite core found in everyday pencils, graphene is a sheet of carbon just one atom thick.
It is nearly weightless, but 200 times stronger than steel.
Conducting electricity and dissipating heat faster than any other known substance, this super-material has transformative applications.
Graphene enables sensors, high-performance transistors, and even gel that helps cell brains to communicate in the spinal cord.
Many flexible device screens, drug delivery systems, 3D printers, solar panels, and protective fabric use graphene.
As manufacturing costs decrease, this material has the power to accelerate the advancements of all kinds.
Right now, the “conversion efficiency” of the average solar panel – a measure of how much-captured sunlight can be turned into electricity – hovers around 16 per cent.
That is the cost of roughly $3 per watt.
Perovskite, a light-sensitive crystal and one of our newer new materials, has the potential to get that up to 66 per cent, which would double what silicon panels can muster.
Perovskite’s ingredients are widely available and inexpensive to combine. What do all these factors add up to? Affordable solar energy for everyone.
With the help of artificial intelligence and quantum computing over the next decade, the discovery of new materials will accelerate exponentially.
And with these discoveries, customised materials will grow commonplace.
Future knee implants will be personalised to meet the exact needs of each body, both in terms of structure and composition.
Though invisible to the naked eye, nanoscale materials will integrate into our everyday lives, seamlessly improving medicine, energy, smartphones, and more.
Ultimately, the path to demonetisation and democratisation of advanced technologies starts with re-designing materials, an invisible enabler and catalyst.
As such, our future depends a lot on the next generation of materials we are going to create.
Does The AI Creator Owns AI’s Design Rights?
With creative AI emerging, art creation doesn’t seem to be unique to humans, not anymore.
Creativity is one of the few traits that make humans different from other species.
We alone can make music and art that speak to our experiences or illuminate truths about our world.
But suddenly, humans’ artistic abilities have some competition—and from a decidedly non-human source; Artificial Intelligence.
Emergence Of Creative AI
Over the last couple of years, there have been some remarkable examples of art produced by deep learning algorithms.
McKinsey estimates creative AI will annually generate a value of $3.5 to $5.8 trillion across various sectors.
They have challenged the notion of an elusive definition of creativity.
They have put into perspective how professionals can use artificial intelligence to enhance their abilities and produce beyond the known boundaries.
But here, creativity is the result of code written by a programmer.
It is indeed designed using a format given by a software engineer, featuring private and public datasets.
Yet, creativity is more than matter and code.
So, the question is how do we assign ownership of creative AI-generated content?
In particular, who has the ownership of an AI’s creative artwork, beyond the programmed algorithm?
Bear in mind, to be considered creative art, the programmed algorithm has to use pre-existing forms of art, as sources of inspiration.
Who Would Own Creative AI?
In 2018, a portrait that was christened Edmond de Belamy was made in a French art collective called Obvious.
It took a database with 15,000 portraits from the 1300s to the 1900s, to train a deep learning algorithm to produce a ‘unique’ portrait.
The painting sold for $432,500 in a New York auction.
Similarly, another creative AI program called Aiva, trained on thousands of classical compositions, has released musical albums whose pieces are now being used by ad agencies and movies from all over the world.
Yes, the datasets used by these two algorithms were different.
Still, behind both AIs, there was a programmer who converted the brush lines and strokes and the musical notes into lines of code.
There was a data scientist or engineer who fitted and ‘curated’ the datasets to be used by their digital model.
There could also have been user-based input, and the output may be biased towards individual styles or unintentionally infringe on similar pieces of art.
This shows that there are many collaborators with distinct roles in producing creative AI content.
The problem occurs not only in video, painting or music. Fashion is increasingly created by AIs and it’s important to discuss who owns creative and proprietary interests.
Creative AI Ownership Guideline
A perspective article published in Nature Machine Intelligence by Jason K. Eshraghian in March looks into how creative AI ‘artists’ and collaborators involved should assess their ownership.
“It started by laying out some guiding principles that are only applicable for as long as creative AI does not have legal parenthood, similar to the way humans and corporations are accorded.”
Before looking at how collaborators can protect their interests, it’s useful to understand the basic requirements of copyright law.
“The artwork in question must be an original work of authorship fixed in a tangible medium.”
Given this principle, the author asked whether it’s possible for creative AI to exercise creativity, skill, or any other indicator of originality.
The answer is still straightforward—no—or at least not yet.
Currently, AI’s range of creativity doesn’t exceed the standard used by the US Copyright Office, which states that:
“Copyright law protects the “fruits of intellectual labour founded in the creative powers of the mind.”
Due to the current limitations of narrow creative AI, it must have some form of initial input that helps develop its ability to create.
At the moment, creative AI is just a tool used to produce creative work in a similar way to a video camera used to record content.
Video producers don’t need to comprehend the inner workings of their cameras; as long as their content shows creativity and originality, they have a proprietary claim over their creations.
The same concept applies to programmers developing a neural network.
As long as the dataset they use as input yields an original and creative result, it will be protected by copyright law.
They don’t need to understand the high-level mathematics, which in this case are often black-box algorithms whose output it’s impossible to analyse.
Algorithms As ‘Creatives’ That Own Copyrights?
The author pointed to the recent patent case of Warner-Lambert Co Ltd versus Generics where Lord Briggs, Justice of the Supreme Court of the UK, determined that:
“The court is well versed in identifying the governing mind of a corporation and, when the need arises, will no doubt be able to do the same for robots.”
In the meantime, Dr Eshraghian suggests four guiding principles to allow artists who collaborate with creative AI, to protect themselves:
Programmers need to document their process through online code repositories like GitHub or BitBucket.
Data engineers should document and catalogue their datasets and processes used to curate their models.
In cases where user data is utilised, the engineer should “catalogue all runs of the program” to distinguish the data selection process.
Finally, the output should avoid infringing on others’ content through methods like reverse image searches and version control.
It could, in some ways, be interpreted as a way of determining whether user-based input has a right to claim the copyright too.
AI-generated artwork is still a very new concept, and the ambiguous copyright laws around it give a lot of flexibility to creative AI artists and programmers worldwide.
The guiding principles Eshraghian lays out will hopefully shed some light on the legislation we’ll eventually need for this kind of art, and start a meaningful conversation between all the stakeholders involved.
Farewell Human Karl Lagerfeld, Welcome AI ‘Karl Lagerfeld’
The times we live in! ‘DeepVogue’, a ‘deep learning’ AI design created by Shenlan Technology has managed to take the 2nd place at the China International Fashion Design.
The Era Of AI Design – Is AI The Future?
Its often-charismatic enthusiasts have always hyped the future of Artificial Intelligence.
But now, it seems that the hype has become real. Media pundits, technologists and the broader public no longer argue if the rise of artificial intelligence is inevitable or not. AI is here.
Companies with mass data fed into AI systems such as Google, Facebook, Badoo, Alibaba, and many others, make daily headlines with technological successes that were SCI-FI movies a decade ago.
Nowadays, we ask an AI assistant on the smartphone for recommendations personalised to our interests. We ride around in cars driven by AI algorithms, and trust AI to find better ways of curing genetical diseases. The world has changed, and AI is a big part of why.
Most experts talk about the AI ‘revolution’ in glowing terms. The latest advancements in computer technology are now seen as advances in humanity; better standards of living, instant access to knowledge, improved hearing and vision – not only for the impaired, cheaper manufacturing of goods, and even better recommendations from Amazon, and Netflix.
Artificial Intelligence is progress, but technological progress cuts both ways. That is why, despite the excitement around artificial intelligence, there is a growing cautionary voice about its potential downside.
The Era Of AI Design – Early Warnings
Back in 2000, Bill Joy, former CTO of Sun Microsystems, wrote ‘Why the Future Doesn’t Need Us’, putting together one of the most famous apocalyptic rants about the threat of AI to humanity.
Sadly, Bill’s message was drowned out by the closer and more tangible problems, such as the attacks of 9/11. Almost two decades later, his anxiety over robots taking over humanity made possible by rapid advances in AI, has become more current than ever.
Three years later, ‘The Artificial Intelligence Revolution: Will Artificial Intelligence Serve Us or Replace Us?’ was launched by Louis Del Monte, a former IBM researcher. In the book, Del Monte expresses his concern that AI is happening so fast that humanity won’t be able to cope with the changes.
A year later, ‘Superintelligence: Paths, Dangers, Strategies’, a bestseller penned by Nick Bostrom, warned us again of the potentiality of AI spelling the end of humanity.
William Barrat, a National Geographic writer and filmmaker, also joined the fray in a full-apocalyptic mode in ‘Our Final Invention: Artificial Intelligence and the End of the Human Era’, worrying over the AI’s influence in the societal construct.
The Era Of AI Design – Can We Coexist?
According to Bostrom, ‘AI could become an existential threat to humanity’. A threat that’s eclipsing previous (and ongoing) concerns about climate change, accelerated pollution, wars, or even nuclear disasters.
Luminaries like Bill Gates and Stephen Hawking have also revealed potential problems that could arise with the emergence of Artificial Intelligence.
Moreover, the founder of Tesla and SpaceX, Elon Musk, has often insisted in the past that humans will be reduced to “pets” by the next super AI if we don’t take action now. Musk has donated $10 million to the ‘Future of Life Institute’, in a bid to help to find a way to coexist peacefully.
However, most of those concerns were focused on the so-called crossover point in the affairs of man and machine. At the point where the AI passes human intelligence and creativity, and humans cease to be the most powerful beings on the planet.
The Era Of AI Design – AI Creativity
Yes, creativity. In November 2014 the article ‘Artificial Intelligence as a Threat’ was published by The New York Times in the Fashion and Style section. As an omen of what’s coming, the author was suggesting the idea that machines are the future creators.
An idea supported by Andrew McAfee and Erik Brynjolfsson of MIT’s Centre for Digital Business and the Sloan School of Management. According to their claims, AI will soon begin assuming roles that were once the sole purview of humans.
Their book, ‘The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies’ reads: “From manufacturing to customisation and arts, AI will change the landscape of the new world.”
But not everybody sees AI the same. In ‘Who Owns the Future?’ Jaron Lanier, a pioneer of virtual-reality software, expresses a profound doubt regarding the coming of a super AI.
Lanier’s views align with Nicholas Carr’s, a former Harvard Business Review editor and writer of a 2007 article, ‘Is Google Making Us Stupid?’, in their belief that AI is a misnomer as ‘true intelligence’ comes only from human minds.
The Era Of AI Design – Welcome Deep Vogue
Fast forward to 2019 and today’s news. A creative algorithm designed by Shenlan Technology has managed to take the second place, after the winners Valentina Cosenza and Giada Petrolini, at the China International Fashion Design. Creativity?
DeepVogue was the only ‘non-human designer’ among 16 teams from all over the world. The ‘machine’ defeated Iris van Wees, a graduate of Amsterdam Fashion Institute, and many other human designers, before a panel of 50 judges, thanks to – let’s be honest – some absolutely magnificent creations.
DeepVogue AI design not only won the runner-up prize but also the ‘People’s Choice Award.’
The Era Of AI Design – What’s China Got To Do With It?
Back in 2017, the ‘Next Generation Artificial Intelligence Development Plan’ was launched by the government, seeking to make China a world leader in AI innovation by 2030.
Nowadays, led by Baidu, Alibaba, and Tencent, at least another 15 Chinese AI companies are worth over 1 billion USD while almost 85 per cent of Chinese companies are testing some forms of AI.
The data shows a level of adoption and implementation considerable higher than the US, in second place with a modest 51 per cent.
China dominates the global AI industry. The country ranks number one for the quantity of AI funding, research papers, and granted patents and with over 2,000 AI companies already operating.
The Era Of AI Design – What’s Next?
Thanks to ‘DeepVogue’, it has become evident that algorithms can create original fashion designs. Once again, I expect the news to reignite speculations on AI design and its potential impact on creative jobs this time.
Nevertheless, I feel that an interesting paradox has emerged: As our technological innovation has become the crowning enlightenment of humanity, it seems that the fast-changing narrative of the contemporary world leaves no room for us, humans.
Or simply put, our creativity is directing us out of existence.
Machines Takeover – The salient AI fashion designer is here.
Fashion design is a form of art; drawing flavour, colour, and composition not only from the styles it creates and the materials it uses but also from the craftsmanship and the tools of the designer.
In their artistic ways, old-generation designers are still using sketches and mood boards.
But, as everything changes, grows and evolves in fashion, maybe now fast than ever with the help of technology, designer’s tools are progressing as well.
At the same time, an emerging generation of ‘hybrid’ fashion designers is rising.
No longer working with sketches, printed pictures, and physical designs, these modern creators employ digital forms conceptualised with the help of computers, inspired by social media and more recently, co-created with artificial intelligence.
A true statement to the change that’s happening is Stitch Fix. A fashion startup with a team of data scientist working with AI to predict which clothes their buyers want to wear.
“The AI identifies fashion styles that customers prefer and would like to buy but aren’t designed or available yet”, says Stitch Fix CAO, Eric Colson.
Moreover, the fusion of fashion with AI changes not only the tools of the fashion designers but also gives birth to new C-level positions in the fashion industry.
New jobs such as the position of Chief Algorithm Officer, or Chief AI Designer have emerged overnight.
Forecasting Market Demand
However, it is not that simple. According to Colson, Stitch Fix’s AI experts are using a triad of algorithms to construct the company’s AI-fashion designer.
The first algorithm identifies and then recommends bits of apparel that could be used as templates for the new garment.
The second algorithm recommends three distinct attributes that have been shown to augment the original style and the third algorithm factors in the so-called ‘randomness factor’, designed to make the final style more interesting and appealing to the buyers.
Combined, these three algorithms are able to process almost 30 trillion possible combinations of styles. However, the final selection of styles comprises of only nine outlines from which the human gets to choose.
“Our proprietary AI can analyse, identify, and generate unique fashion designs and styles that are in high demand by the consumers of fashion and yet, are missing from the market,” said Colson.
AI In The The Socio-Cultural Context
Nevertheless, while most of the bulk work is done by the AI, human designers are still required to assess and improve the AI’s proposals into garments that people would want to buy and wear.
“We are [not yet] at the stage where the AI is solely responsible for the entire process, added Daragh Sibley, Data Science Manager at Stitch Fix.
That is because, while from a mathematical point of view the AI is able to identify and construct the perfect fashion garment, the machine is still lacking the ability to assess historical and social contexts and understand how and when such contexts make fashion creations relevant or complete disasters.
So what does the rise of AI mean for the future of fashion?
From Colson’s attempt to decipher the construct of fashion from an algorithmic point of view, the ‘infiltration’ of AI in the fashion industry is becoming increasingly harder to ignore.
We see the use of AI in the fashion industry under different shapes and forms: AI in fashion as style assistants as it is the case of ‘The Look’, an Amazon creation that has a deep understanding of fashion styles.
AI in pattern recognition. AI in trend spotting. AI in social media ‘reading’, pointing to the inevitability of seeing one day, independent AI fashion designers at work.
Inspired By The History Of The World
A new era of previously unseen styles, colors, and patterns, made with the most innovative and sustainable materials is coming.
Fashion is shifting from human designs, according to one’s unique cultural background, education, and experience, to AI fashion designs, constructed on the creations of all previous designers, biotechnology and material understanding, and inspired by this earth’s history, art, and fashion.
AI-Designed Clothes Available In Stores
Korea’s first AI-designed clothes are now available in stores. Handsome, a South Korean fashion company has just released its new line of fashion apparel designed with the help of artificial intelligence.
On the steps of 8 by YOOX
It is the second endeavor of this type, following the launch of 8, another AI-powered fashion label that belongs to the YOOX group, and the use of AI in fashion design by Stitch Fix.
SJYP fashion label, – Steve Jung & Yoni Pai – has resulted from the collaboration of Handsome, an associate of Hyundai DSG, and Designovel, a startup specialized in creating artificial intelligence for fashion.
The SJYP’s first product is a hoodie called the ‘Dino Hood Tee’, and it is hailed as Korea’s first AI-designed fashion garment to hit the stores.
Designovel’s ‘Style AI’ has ‘made’ its custom-designed by drawing inspiration from over 330,000 pictures, characters, and logos, provided by Handsome, via the convolutional neural network.
Beyond Pattern Recognition
CNN is an image processing technology that recognizes, categorizes, and process patterns for the development of new fashion styles and designs.
The final design features the image of a dinosaur embedded with the brand’s logo and Lego blocks.
“We began this collaboration to see if it was possible to create AI-fashion designs for real-world use,” said a spokesman from Handsome.
The hoodie costs $215 and is already available via SJYP stores and Hyundai’s Department Stores nationwide, online, and offline.
Handsome is now looking forward to expanding the use of algorithmically-designed clothes and implement AI capabilities in other phases of fashion such as customer data by granting the AI access to the latest trends and styles in real-time.
“We are looking at integrating AI technology into other aspects of our fashion business, such as personalised designs and outfits according to the data collected and social media recommendations from our consumers”, said the spokesman of Handsome.
Uniqlo Launches AI Personal Assistant
Uniqlo Launches AI Personal Assistant Empowered By Google Technology – The Japanese retailer, Uniqlo has launched Uniqlo IQ, a new Uniqlo mobile assistant that gives customers personalized recommendations by the use of Artificial Intelligence and voice recognition techniques.
To improve the online shopping experience for its fashion customers, Uniqlo has developed a new AI-empowered personal assistant using the same technology that has been used in Google Assistant by Inamoto & Co.
After testing the technology in both the American and Japanese markets, Uniqlo IQ is now ready to be used by its customer via its own app, Line, or through Google Assistant.
The app helps the users to find clothes, see the product rankings, use advanced searching services, find fashion items that are featured in magazines, or even recommends products according to each customer’s daily horoscope.
Moreover, Uniqlo IQ allows customers to buy the chosen product within the app or direct them to the nearest store for a try on.
Founding partner of Inamoto & Co, Rei Inamoto has told TheDrum that the deeper movement of retailers into the digital realm is not only making shopping “portable and perpetual.”
But, it also makes online shopping more enjoyable by allowing the customers to have more personalized shopping experiences.
The Fashion Industry Awaits Its ‘Uber’
Fashion Industry Still Awaits Its ‘Uber’ – Where’s The Disruptive Innovation?
I hear every day about another new invention that is ‘for sure’ going to disrupt the fashion landscape.
In most cases, it is either a new innovative technology such as graphene-based textiles, able to gather the wearer’s body electricity, new 3D printing techniques that output cotton-like materials, immersive e-commerce platforms running on augmented and mixed reality, or some sort of style-matching artificial intelligence-powered fashion assistant apps.
The truth is, disruptive innovation starts when a product, a market, or an industry is replaced.
Disruption is by definition destructive.
To change for the better, it has to disrupt before it creates.
Disruptive innovation has to disrupt jobs, businesses, industries.
See the disruption caused by Uber and Airbnb, for example. Many jobs were lost, but many more jobs were created.
The Industry Is Ripe
For that, while pushing for market changes, technological innovation alone does not have the power to disrupt.
Any technology needs people. It needs consumers, to adopt and use it en-masse.
To date, all technological innovations in the fashion industry did not disrupt but instead enhanced it.
To disrupt the fashion industry, we need products, markets, and services unseen before.
The global fashion market is a multi-trillion business with massive potential for disruption.
The fast adoption of sustainable, innovative materials, the use of augmented reality and artificial intelligence in fashion designs, style predictions, and retail, shows that the landscape is ripe for disruptive innovation.
Not Knowing What To Disrupt?
The industry of apparel and accessories sees constant changes as it is in its nature to be fashionable, to remain trendy.
However, let’s not confuse style and fashion changes with disruptive innovation.
By redesigning a jacket, you are not disrupting an industry.
By bestowing garments with smart sensors and wearable technology, you are not disrupting but rather improve the garment.
You are not creating a “new fashtech industry that will run in parallel with the ‘traditional’ fashion industry”, but rather participate in the augmentation of the overall apparel industry and the evolution of the global fashion landscape.
Thus, you become an active participant in the process of maintaining its fashionable nature by keeping up with the times and consumers’ demands.
You help it grow; you enhance it.
According to Statista, the global fashion market is expected to reach $3.4 trillion by 2020. Just like food, everybody needs clothes; it is something that we all need every day.
The question is, what will you do to disrupt the fashion industry?
Moreover, what do you intend to disrupt? Products? Services?
The Uber Of Fashion
As the Internet-based fashion commerce is growing, its share of the market against the classic retail stores, consumers’ expectations are also changing.
This is your chance to rethink what the future fashion store will look like.
Online? Offline? Channel convergence? Mixed reality? What about the tactile feedback?
Also, around the world, more fashion consumers are asking for smarter use of resources and reduction in the emission of pollutants, requiring companies to create more sustainable products, from environmentally-friendly materials.
Is your startup designing a new type of sustainable material that replaces cotton, leather, and plastic while retaining their physical properties?
Only then, you’re on the cusp of disruptive innovation.
However, while the required technology is already here, the fashion industry is still waiting for that disruptive innovation to reshape it.
Do we go for renting, subscription boxes or wait to see if cheap 3D printing technologies mark a boom in crowdsourced fashion?
Is your startup the next Uber for the fashion industry?