“We’re in a diversity crisis”: cofounder of Black in AI on what’s poisoning algorithms in our lives

“We’re in a diversity crisis”: cofounder of Black in AI on what’s poisoning algorithms in our lives

Artificial intelligence is an increasingly seamless part of our everyday lives, present in everything from web searches to social media to home assistants like Alexa. I had a tiny mailing list before that where I literally would add any black person I saw in this field into the mailing list and be like, ‘Hi, I’m Timnit. The reason diversity is really important in AI, not just in data sets but also in researchers, is that you need people who just have this social sense of how things are. We are in a diversity crisis for AI. In addition to having technical conversations, conversations about law, conversations about ethics, we need to have conversations about diversity in AI. We need all sorts of diversity in AI. And this needs to be treated as something that’s extremely urgent. One is to diversify your data set and to have many different annotations of your data set, like race and gender and age. But even after you do this, you are bound to have some sort of bias in your data set. Something I’m really passionate about and I’m working on right now is to figure out how to encourage companies to give more information to users or even researchers. So that when I’m a startup and I’m just taking your off-the-shelf data set or off-the-shelf model and incorporating it into whatever I’m doing, at least I have some knowledge of what kinds of pitfalls there may be. Right now we’re in a place almost like the Wild West, where we don’t really have many standards [about] where we put out data sets. And then there are just some things you probably shouldn’t be using machine learning for right now, and we don’t have a clear guideline for what those things are. We should say that if you’re going to use machine learning for this particular task, the accuracy of your model should be at least X, and it should be fair in this particular respect. AI is just now starting to be baked into the mainstream, into a product everywhere, so we’re at a precipice where we really need some sort of conversation around standardization and usage. At the time we started this project, there was very little work being done to try to analyze culture using images. But we know that online, most of our data is in the form of images. There are places in the world where the infrastructure is not there and the resources are not there to send people door to door and gather [census] data, [but where] having an understanding of the different types of populations that live in your country would be very helpful. Because if I’m going to be continuing to do this line of work, I really need to have a better understanding of the potentially negative repercussions. So my line of work there was really what led me to want to spend some time in the fairness community to understand where the pitfalls could be. What issues are you hoping to address with this first Fairness and Transparency conference? She also cofounded the Black in AI event at the Neural Information Processing Systems (NIPS) conference in 2017 and was on the steering committee for the first Fairness and Transparency conference in February. This is really the first conference that is addressing the issues of fairness, accountability, ethics, and transparency in AI. There have been workshops at other conferences, and mostly there have been workshops at either natural-­language-processing-based conferences or machine-learning-based conferences. It’s really important to have the stand-alone conference because it needs to be worked on by people from many disciplines who talk to each other. There are issues of transparency; there are issues of how the laws should be updated. If you’re going to talk about bias in health care, you want to talk to [health-care professionals] about where the potential biases could be, and then you can think about how to have a machine-learning-based solution. I love the research that I work on. I love the field. She spoke with MIT Technology Review about how bias gets into AI systems and how diversity can counteract it. How does the lack of diversity distort artificial intelligence and specifically computer vision? When I started Black in AI, I started it with a couple of my friends. I had a tiny mailing list before that where I literally would add any black person I saw in this field into the mailing list and be like, “Hi, I’m Timnit. Let’s be friends.” What really just made it accelerate was [in 2016] when I went to NIPS and someone was saying there were an estimated 8,500 people. At the same time, I also saw a lot of rhetoric about diversity and how a lot of companies think it’s important. I was like, “We have to do something now.” I want to give a call to action to people who believe diversity is important. Because it is an emergency, and we have to do something about it now. There is a bias to what kinds of problems we think are important, what kinds of research we think are important, and where we think AI should go. If we don’t have diversity in our set of researchers, we are not going to address problems that are faced by the majority of people in the world. When problems don’t affect us, we don’t think they’re that important, and we might not even know what these problems are, because we’re not interacting with the people who are experiencing them. “When I started Black in AI, I started it with a couple of my friends.

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SimPaisa Raises Rs. 25 Million in Seed Funding from Sarmayacar

SimPaisa Raises Rs. 25 Million in Seed Funding from Sarmayacar

We can now focus on our core products and believe that the kind of experience and network new investors bring will help our business grow faster and expand across the MEENA region,” said Yassir Pasha, Co-Founder and Managing Director of SimPaisa.SimPaisa is already working with multiple international and local merchants and is engaging major players like Gaana, Hangama, Sony Liv and Adolf Games. SimPaisa is the only payment system in Pakistan to offer this service.Due to the lack of trust in online credit card payments, SimPaisa allows users to enjoy the benefits of premium services without the necessary risks involved. For merchants, SimPaisa allows for applications to be monetized, tapping into the 140 million plus SIM subscriber market.ALSO READProCheck Raises $250,000 in Seed Funding from SarmayacarThe capital raised will be used to further invest in SimPaisa, expand the merchant network and scale the operations to other countries. As part of the financing, Bernhard Klemen, Partner at Sarmayacar, will join PublishEx’s Board of Directors.“The mobile payment solutions offered by SimPaisa gives 110 million potential customers a more convenient, secure and fast way to pay for and access digital offerings, in particular media, gaming and insurance related products. For its telecommunication partners, SimPaisa significantly enhances their service portfolio while allowing for higher revenues, so it is a win-win-win proposition with solid traction and attractive growth potential,” said Bernhard Klemen.“We wanted to bring in a simple secure payment mechanism that didn’t require the customer to have a credit card, bank account or a third party mobile wallet which would need to be constantly topped up. Through our existing teleco relationships we will now be able to offer 11 international markets to our merchants,” said Salim Karim, Co-Founder and CEO of SimPaisa.ALSO READMusic Streaming Service Patari Raises $200,000 Seed Investment“Ideas are easy but implementation in the local environment is hard; however, the startup environment in Pakistan is improving drastically every year. It is difficult and time consuming to raise smart capital in the region but we are excited to realize the synergies and the potential coming with this investment.

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Asia’s rocketing ambition

Asia’s rocketing ambition

China’s lunar missions have prompted Japan and India to step up their own space exploration. (WorldPost illustration) This is the weekend roundup of The WorldPost, of which Nathan Gardels is the editor in chief.  In his 2011 book, “Civilization: The West and the Rest,” historian Niall Ferguson credits a series of “killer apps” for enabling the West to take off in the 15th century and remain dominant for the next 500 years while the rest of the world stalled. China’s technological dominance weighs on the Asian strategic balance, and both India and Japan are clearly feeling the pressure.” Chandran Nair notes how a new sustainable practice implemented by China is setting off a global competition in waste recycling. “Beijing decided to halt imports of plastic waste in January, which had a knock-on effect on the rest of the world, since China has been a major outlet for recycling trash. These government decisions, in turn, prompted several major multinational companies from Coca-Cola to Walmart to pledge in Davos last month to reduce their use of plastics. Drawing on the compelling card of global competition, Nair proposes that the Chinese e-commerce giant Alibaba lead the way in regulating the use of plastics in packaged deliveries, thus pressuring the other global giant, Amazon, to follow suit. In domestic policy, China’s “Internet plus” policy — a long-range plan to link cyber and physical infrastructure through high-tech innovation and the “Internet of things” — runs up against what might be called the “Internet minus” policy of censorship, which impedes a pragmatic approach to addressing its challenges through seeking truth from fact. To the extent China tries to extend control over inflows of information — including by seeking to curtail critical content in scholarly journals from the West that circulate in Chinese academia — or tries ham-handedly to promote its own narrative in the Western media, it is hurting its own cause.  As Thomas Kellogg writes, such an effort has already been saddled with a pejorative moniker — “sharp power.” Yet, there is an important distinction between China and Russia’s efforts to manipulate public opinion. Russia is trying to sow division and discord in the Western body politic to undermine the democratic discourse; China is clumsily trying to control its own image in the West. In that book, Ferguson recounts how competition among the nations and city-states of Europe over exploring trade routes to the New World and later, over exploiting the cutting-edge discoveries of the Newtonian scientific revolution, propelled them all forward. As Chinese President Xi Jinping’s signature foreign policy vision, it is massive in all dimensions, aiming to bind Beijing with the rest of the world through more than $1 trillion of new infrastructure, scores of trade agreements and countless other connections,” he writes from Tashkurgan, a Chinese town on the Pakistan border. “But there is a fundamental tension between the connectivity China says it seeks and the control it is unwilling to give up,” says Hillman, referring to the massive presence of anti-terror security forces and imposing police outposts across Xinjiang’s predominantly Muslim Uyghur towns and cities. “Even as China claims to be championing globalization and broadening ties, it is clamping down in critical borderlands that Belt and Road routes would pass through, potentially crippling its own projects,” concludes Hillman. One clear lesson of history is that the growing dominance of a major power like China will generate challengers in kind, both those driven to compete as well as those determined to resist. The Middle Kingdom’s efforts to make its mark in every realm — from outer space to artificial intelligence and sustainable environmental practices — incites others in its neighborhood, and indeed in America and Europe as well, to do likewise. Rajeswari Pillai Rajagopalan describes how geopolitical anxieties in Asia have prompted the governments of India and Japan to join together in a new project to land on the moon. “The recent launch of the SpaceX rocket Falcon Heavy is a good illustration of the entry of efficient and innovative private players into an arena long considered the preserve of national governments,” she writes from New Delhi. “But this does not mean that national competition in outer space is disappearing. China’s growing space prowess is leading to a space race with India and Japan, which are beginning to pool their resources to better match Beijing.” She goes on to say: “Both are acutely aware of what China has accomplished, with four moon missions between 2007 and 2014 alone.

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STANK LOVE, BEAR WIG, and other sayings from AI-generated … – Popular Science

STANK LOVE, BEAR WIG, and other sayings from AI-generated … – Popular Science

The list, Shane comments, was “pitifully small.” (For comparison, Apple says they used “over a billion images” when creating the neural networks that power its Face ID security system on the iPhone X.) To compensate for the small list size, she took a number of steps. The first was to ensure that the neural network didn’t just directly repeat words it saw in the list she gave it. She needed to “thwart its ability to memorize the data,” she says. So, Shane explains, she intentionally hobbled aspects of the AI system by knocking out “parts of the neural network at random.” Using that strategy, she made the artificial intelligence system devise “really general rules” when producing new candy heart slogans. To make the original dataset bigger, she added back into it some of the AI-generated slogans the system first came up with, like STANK LOVE. That ended up creating many bear-themed slogans, including TIME BEAR, which would be an excellent title for a film about a time-traveling ursine, and HOME BEAR, which kind of sounds like an Apple product. The bear theme is probably because the expanded dataset included BEAR HUG, MY BEAR, BEAR WIG, and TEAM BEAR. “The more data it has, the more it’s going to be consistently interesting,” Shane says. But with artificial intelligence taking on even bigger roles in our lives, the stakes are higher when we’re not just talking about candy hearts. And recent research reported in The New York Times showed that facial recognition systems were better at correctly identifying the gender of images of white males; one probable cause for errors like these is if the data set used in the first place overrepresented white men. But when using artificial intelligence in a fun, lighthearted way, as Shane is, the creative results will also be best with a lot of data. For the candy hearts, the original input was scant, and she had to sort through the output to find the good ones. She’s had more luck with bigger datasets for other projects, like giving a neural network thousands of real bird names and asking it to come up with new, made-up avian names based on that original data. (Cape Babbler was one believable result.) Besides candy hearts and bird species, Shane has also trained neural networks to come up with new names for craft beers (want a sip of some Dang River?), metal bands (what does music from Death from the Trend sound like?), and delightfully, My Little Pony names, producing Pony names like Dark Candy (which also sounds like a Valentine’s Day snack). More specifically, a machine learning system called a neural network deserves our thanks for these bizarre expressions, as does a human—a research scientist, Janelle Shane, who works at an optics research and design company in Colorado. And while it’s easy to laugh at AI-created Valentine’s Day messages like LOVE 2000 HOGSYEA, her research also illustrates an important issue in artificial intelligence: why good data, and lots of it, matters for developing AI. But first, here’s how, and why, Shane used the neural network to create messages like LOOK BIG. She began, she says, by wondering what she “could train the neural network on that would showcase its weird, kind of endearing ability to try and fail to guess at what humans find attractive.” She eventually hit on candy hearts.

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AI is helping seismologists detect earthquakes they’d otherwise miss … – The Verge

AI is helping seismologists detect earthquakes they’d otherwise miss … – The Verge

And for seismographs, it means cancelling out the normal geological rumblings of the Earth (what’s known as “ambient seismic noise”) to spot the earthquakes that might be very small or far away. To make this happen, Perol and his colleagues trained a convolutional neural network to recognize background noise, feeding it data from seismically quiet areas, like pre-fracking era Oklahoma and the geological dead-zone of Wisconsin. (The state has only really had one significant earthquake, and that was in 1947.) As with all neural networks, the software examines this input and learns to pick out common patterns. Once it knows what ambient rumblings sound like, it can remove these from the data, leaving behind the tiny earthquakes that had previously been hidden — like sea shells revealed by a retreating tide. As a bonus, the neural network is even able to identify the rough whereabouts of individual quakes by matching the patterns they created with historical data where a tremor’s location was known. This could be done by looking for patterns in the data; for example, finding times when a number of small earthquakes have happened in quick succession, triggering a bigger, potentially damaging quake. The idea of using AI to predict — not just detect — earthquakes is an exciting one, but it’s not something that the whole seismologist community is confident about. (You can watch the video below for more info.) In Oklahoma at least, prediction isn’t as pressing as detection. Before 2009, the state had roughly two quakes of magnitude three and above each year. (Magnitude three is when things shake on the shelf, but before houses start getting damaged.) In 2015, this tally rocketed to more than 900, though it’s calmed since, falling to 304 last year. This sudden increase is thought to be caused by the disposal of wastewater by the state’s booming fracking industry, and it’s caught seismologists off-guard. The solution proposed by Perol and his colleagues from Harvard University’s engineering and earth sciences departments is to use artificial intelligence to amplify the sensitivity of the state’s earthquake detectors, otherwise known as seismographs. In a paper published today in the journal Science Advances, they show how effective this technique is — capable of detecting 17 times more earthquakes than older methods in a fraction of the time.

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Human/AI hybrids and gene editing are going to change mankind in a big way

Modern medicine and rapidly advancing technology have seen us greatly evolve from the early days of hunter-gatherers, and now the same factors are working toward seeing the introduction of “superhumans” into our society. At least this is the belief of renowned futurist Ian Pearson, who said something needs to be done before Artificial Intelligence becomes “billions of times” smarter than mankind. “The fact is that AI can go further than humans, it could be billions of times smarter than humans at this point,” he said. “So we really do need to make sure that we have some means of keeping up. The way to protect against that is to link that AI to your brain so you have the same IQ … as the computer.” At the same World Government Summit the year prior, Elon Musk also suggested humans and AI need to merge. “Over time, I think we will probably see a closer merger of biological intelligence and digital intelligence,” Musk said in February 2017. “It’s mostly about the bandwidth, the speed of the connection between your brain and the digital version of yourself, particularly output.” Since the comments, Musk has even founded a company called Neuralink, which has been designed to make this a reality. During his speech, Pearson said he agreed with Musk’s comments and commended the work being done by Neuralink. “I don’t actually think it’s safe, just like Elon Musk … to develop these superhuman computers until we have a direct link to the human brain,” he said. SUPERHUMAN WORKERS Whether it is self-driving taxis or service and hospitality robots, one of the biggest concerns of AI is the risk it will pose to the human workforce. During his address at the summit, Sebastian Thurn said he envisioned a future where humans and AI would merge, turning people into “superhuman workers”. “AI is a tool and what AI can do really, really well is getting rid of repetitive work,” he said, reported CNBC. “So, if you are a worker, say a medical doctor or a lawyer who spends day in and day out doing the same thing, then having AI look over your shoulder and learn those skills from you will make you a superhuman, a more powerful person. “Now, that means that some jobs will go away, very repetitive work, of course. Allowing humans to become masters of their DNA is something that can be achieved using a gene editing technique known as CRISPR — a simple yet powerful tool used to easily alter DNA sequences and modify gene function. “These instruments, like CRISPR, are allowing us to, in real-time, edit life on a grand scale,” Enriquez said, according to Futurism. “We are rewriting the sentences of life to our purposes.” He said these techniques will soon see us living in a world of “unrandom selection.” “Instead of letting nature select what lives here, I’m going to select what lives here,” he said. “Science used to be about discovery, now it is about creation.” The academic said more than being able to create athletes from birth, the technology would greatly increase the amount of lives that could be saved on a daily basis. “You can make the world’s flu vaccine in a week instead of a year. With the likes of Elon Musk and NASA working toward getting humans to colonize Mars, he said gene editing will play a vital role in this. “Why would anyone want to do this,” Enriquez asked. “Because, at heart, we are explorers. We have to take control of our own evolution if we want to even think about getting somewhere else.” HUMAN/AI HYBRIDS Editing our genomes to thrive in extreme environments will be useless if we can’t figure out a way for humans and artificial intelligence to merge.

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China’s military could soon rival American power ‘across almost every domain’: Top US Admiral

China’s military could soon rival American power ‘across almost every domain’: Top US Admiral

Agencies | Feb 15, 2018, 10:54 ISTAdmiral Harry Harris warned lawmakers they must be wary of Beijing's investments in traditional assets as well as its development of hypersonic missiles and artificial intelligenceHe said the OBOR initiativeIt is a concerted, strategic endeavour by China to gain a foothold and displace the US and its allies in the Indo-Pacific regionThe People's Liberation Army (Reuters photo) WASHINGTON: China's military might is growing at such a pace that it could soon rival American power "across almost every domain," a top US military official said Wednesday. Admiral Harry Harris, who heads up the military's enormous Pacific Command (PACOM), warned lawmakers they must be wary of Beijing's investments in traditional assets as well as its development of a new wave of technologies such as hypersonic missiles and artificial intelligence. Touted as Chinese President Xi Jinping's ambitious project, the One Belt One Road initiative focuses on improving connectivity and cooperation among Asian countries, Africa, China and Europe. "Key advancements include fielding significant improvements in missile systems, developing fifth-generation fighter aircraft capabilities, and growing the size and capability of the Chinese navy to include their first overseas base in the port of Djibouti." He added: "If the US does not keep pace, PACOM will struggle to compete with the People's Liberation Army on future battlefields." The admiral stressed that China's One Belt One Road (OBOR) initiative is not as benign as it is made out to be and, in fact, all global chokepoints are currently under pressure from it. "One Belt One Road is much more than just an economic engine that China is undertaking. It is a concerted, strategic endeavour by China to gain a foothold and displace the United States and our allies and partners in the Indo-Pacific region," he said. One needs to look at the bases and places where China is putting its emphasis to see the realisation of this, he said. "They are in a position today to influence the shipping routes in the Strait of Hormuz, in the Gulf of Aden, the Red Sea which means the Suez Canal, and also in our hemisphere in the Panama Canal," he said. "Also, finally in the Strait of Malacca, all those global chokepoints are under pressure from China's One Belt One Road initiative," Harris said.

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Arterys Receives First FDA Clearance for Broad Oncology Imaging Suite with Deep Learning

Arterys Receives First FDA Clearance for Broad Oncology Imaging Suite with Deep Learning

The new oncology software complements Arterys' existing web-based offering, and helps clinicians measure and track tumors or potential cancers, and easily apply radiological standards. The company's goal is to reduce variability and subjectivity in the clinical diagnoses, and alleviate the enormous workloads radiologists face. With this new technology, radiologists can now easily confirm, evaluate, quantify, and report on the absence or presence of lung nodules and liver lesions along with their key characteristics using a simple web browser. The company plans additional deep learning workflows for solid tumors in other organs. "The evaluation of primary and metastatic disease in the lung and liver are among the most valuable contributions of radiologists to the care of patients with cancer," said radiologist and Arterys co-founder Albert Hsiao, M.D., Ph.D. "We desperately need more efficient technology to automatically track lung and liver lesions to further improve diagnosis, assess response to treatment, and automate reporting with standardized terminology including Lung-RADS and LI-RADS. The Oncology Lung AI and Liver AI products are designed to maximize efficiency and accuracy of the radiologist read and will power next-generation radiology interpretation." Oncology AI runs on the Arterys MICA (Medical Imaging Cloud AI) platform, which is easier to deploy than on-premise imaging systems and complies with patient data privacy and security requirements in 27 countries, including the US, Canada, all of Europe, Australia, and New Zealand. The software uses deep learning to automate the segmentation of lung nodules and liver lesions, with accuracy equal to segmentations performed manually by experienced clinicians. "Cancer is one of the leading causes of morbidity and mortality worldwide, with about 14 million new cases in 2012, and about 8.8 million deaths in 2015, according to the World Health Organization," said Arterys CEO Fabien Beckers, Ph.D. "A core Arterys mission is to help the medical community identify cancer earlier, so that patients can receive optimal treatment and improved prognosis. FDA clearance of our Oncology AI suite will help clinicians to quickly measure and track tumors over time. Additionally, our software enables seamless collaboration for clinicians, so second opinions can be easily gathered from within the hospital, or from outside experts." About Arterys: Arterys was founded in 2011 to facilitate the global advancement of healthcare and enable data driven medicine by leveraging cloud computation and artificial intelligence. MICA enables use and interaction with deep learning algorithms in real-time, augmenting the clinician and expediting image interpretation.

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MIT Neural Network Processor Cuts Power Consumption by 95 Percent

MIT Neural Network Processor Cuts Power Consumption by 95 Percent

Neural network processing and AI workloads are both hot topics these days, driving multiple companies to announce their own custom silicon designs or to plug their own hardware as a top-end solution for these workloads. But one problem with neural networks is that they tend to be extremely power intensive, and not necessarily suited to mobile devices or the kind of low-power “smart” speakers that have recently become so popular.MIT is claiming to have developed a neural network processor that addresses these problems, with an overall power reduction of up to 95 percent. Those values then have to be stored, and each input to a node has to be independently calculated.What MIT has done is create a chip that more closely mimics the human brain. By storing all of its weights as either 1 or -1, the system can be implemented as a simple set of switches, while only losing 2-3 percent of accuracy compared with the vastly more expensive neural nets.Not bad for an approach that can reduce power consumption up to 95 percent. Instead of being forced to rely on cloud connectivity to drive AI (and using power to keep the modem active), SoCs could incorporate these processors and perform local calculations.“The general processor model is that there is a memory in some part of the chip, and there is a processor in another part of the chip, and you move the data back and forth between them when you do these computations,” said Avishek Biswas, an MIT graduate student in electrical engineering and computer science, who led the new chip’s development:Since these machine-learning algorithms need so many computations, this transferring back and forth of data is the dominant portion of the energy consumption. Our approach was, can we implement this dot-product functionality inside the memory so that you don’t need to transfer this data back and forth?A typical neural network is organized into layers. Weight, in this context, refers to how much of an impact computations performed in one node will have on the calculations performed in the nodes it connects to. Nodes receiving input from multiple nodes above it multiply the inputs they receive by the weight of each input. If the dot product is above a certain threshold, it gets sent along to nodes farther down the chain.

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How Artificial Intelligence Is Changing The Future Of Beauty

How Artificial Intelligence Is Changing The Future Of Beauty

More and more companies are embracing the individuality of their customers, creating products designed specifically for each of them. “This database encompasses more than 8 million consumer reviews about skincare products, more than 100,000 beauty products that are on the market and 20,000 beauty ingredients and more than 4,000 scientific articles or peer-reviewed journal articles about skin and about ingredients,” Zhao explained, noting that the database allows for transparency about suppliers, ingredient origins and efficacy. Bots continuously scrape the data in the database and, through machine learning, are able to make connections between different product categories, ingredients and review ratings. Zhao explained that Yuan would use semantic searches to pick out different key words ― acne, wrinkles, etc. ― and then make sense of the ingredients and how they affect those skin concerns for different people. On the user experience end, consumers just fill out a short quiz (developed by a dermatologist) that asks for things like age, skin type, skin goals, ethnicity and geographic location. “A machine is not able to know what feels good, what feels moisturizing, what percentage of oil is good for cold weather,” she said. “All of those require an expert’s inclination,” Zhao said. Another brand taking the tech-heavy approach to personalized skin care is Curology, an app-meets-medical-practice-meets-subscription-service that uses digital technology as a supplement to human interaction. Curology offers personalized skin care solutions aimed specifically at those dealing with acne. Similar to Proven, Curology’s process for consumers begins with a questionnaire that asks for details like skin type and skin goals as well as medical history. Then users are matched with a medical professional who will design the custom formula to target unique skin care needs. “Technology is super critical to what we do in a lot of ways,” Lortscher said, adding that the aim for Curology’s technology was to make it easy for both the patient and doctor to connect with each other. The idea came to him, he said, while he was practicing in New Mexico and his patients were driving one or two hours to see him. “What we don’t do with technology is use any sort of automation or algorithm to prescribe things to our patients,” Lortscher said. “Ultimately you need human judgment in there. Brands like Glossier and Milk have garnered impressive cult followings, thanks to their social media-friendly packaging and refreshing approach to beauty. Customers enter in their hair type, hair structure, hair goals and other preferences, and that information is filtered through an algorithm that “transforms all of those inputs into very precise outputs of ingredient combinations,” CEO and co-founder Zahir Dossa said. In Dossa’s opinion, it’s the fact that consumers are getting a product made specifically for them based on statistics and data, as opposed to a stylist’s potential personal or professional biases. In addition, consumers have the ability to provide feedback and tweak their formulas to their liking, he added. Of course, Proven, Curology and FoB aren’t the first companies to incorporate advanced technologies, with or without human aspects, into their business models in order to provide consumers with truly customized products. “Not only is it using technology to improve little aspects of things, it’s actually using technology to fundamentally change the products that each and every single person gets and ideally would be able to do so on a very individual level.”  But, by and large, most brands seem to be all about finding the next trendy ingredient, featuring it in their products and convincing us that their formula is better than the others on the market. We’re all unique, with different skin types or hair types, and have different goals for what we want to achieve. Most beauty brands aren’t selling products tailored to individual consumers. Instead, they’re selling a brand, a luxury, a lifestyle or some product that will magically work on every skin type and solve every skin problem.

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