Tag Archives: computer

#435687 Humanoid Robots Teach Coping Skills to ...

Posted on September 16, 2019 by Android

Photo: Rob Felt

IEEE Senior Member Ayanna Howard with one of the interactive androids that help children with autism improve their social and emotional engagement.

THE INSTITUTEChildren with autism spectrum disorder can have a difficult time expressing their emotions and can be highly sensitive to sound, sight, and touch. That sometimes restricts their participation in everyday activities, leaving them socially isolated. Occupational therapists can help them cope better, but the time they’re able to spend is limited and the sessions tend to be expensive.

Roboticist Ayanna Howard, an IEEE senior member, has been using interactive androids to guide children with autism on ways to socially and emotionally engage with others—as a supplement to therapy. Howard is chair of the School of Interactive Computing and director of the Human-Automation Systems Lab at Georgia Tech. She helped found Zyrobotics, a Georgia Tech VentureLab startup that is working on AI and robotics technologies to engage children with special needs. Last year Forbes named Howard, Zyrobotics’ chief technology officer, one of the Top 50 U.S. Women in Tech.

In a recent study, Howard and other researchers explored how robots might help children navigate sensory experiences. The experiment involved 18 participants between the ages of 4 and 12; five had autism, and the rest were meeting typical developmental milestones. Two humanoid robots were programmed to express boredom, excitement, nervousness, and 17 other emotional states. As children explored stations set up for hearing, seeing, smelling, tasting, and touching, the robots modeled what the socially acceptable responses should be.

“If a child’s expression is one of happiness or joy, the robot will have a corresponding response of encouragement,” Howard says. “If there are aspects of frustration or sadness, the robot will provide input to try again.” The study suggested that many children with autism exhibit stronger levels of engagement when the robots interact with them at such sensory stations.

It is one of many robotics projects Howard has tackled. She has designed robots for researching glaciers, and she is working on assistive robots for the home, as well as an exoskeleton that can help children who have motor disabilities.

Howard spoke about her work during the Ethics in AI: Impacts of (Anti?) Social Robotics panel session held in May at the IEEE Vision, Innovation, and Challenges Summit in San Diego. You can watch the session on IEEE.tv.

The next IEEE Vision, Innovation, and Challenges Summit and Honors Ceremony will be held on 15 May 2020 at the JW Marriott Parq Vancouver hotel, in Vancouver.

In this interview with The Institute, Howard talks about how she got involved with assistive technologies, the need for a more diverse workforce, and ways IEEE has benefited her career.

FOCUS ON ACCESSIBILITY
Howard was inspired to work on technology that can improve accessibility in 2008 while teaching high school students at a summer camp devoted to science, technology, engineering, and math.

“A young lady with a visual impairment attended camp. The robot programming tools being used at the camp weren’t accessible to her,” Howard says. “As an engineer, I want to fix problems when I see them, so we ended up designing tools to enable access to programming tools that could be used in STEM education.

“That was my starting motivation, and this theme of accessibility has expanded to become a main focus of my research. One of the things about this world of accessibility is that when you start interacting with kids and parents, you discover another world out there of assistive technologies and how robotics can be used for good in education as well as therapy.”

DIVERSITY OF THOUGHT
The Institute asked Howard why it’s important to have a more diverse STEM workforce and what could be done to increase the number of women and others from underrepresented groups.

“The makeup of the current engineering workforce isn’t necessarily representative of the world, which is composed of different races, cultures, ages, disabilities, and socio-economic backgrounds,” Howard says. “We’re creating products used by people around the globe, so we have to ensure they’re being designed for a diverse population. As IEEE members, we also need to engage with people who aren’t engineers, and we don’t do that enough.”

Educational institutions are doing a better job of increasing diversity in areas such as gender, she says, adding that more work is needed because the enrollment numbers still aren’t representative of the population and the gains don’t necessarily carry through after graduation.

“There has been an increase in the number of underrepresented minorities and females going into engineering and computer science,” she says, “but data has shown that their numbers are not sustained in the workforce.”

ROLE MODEL
Because there are more underrepresented groups on today’s college campuses that can form a community, the lack of engineering role models—although a concern on campuses—is more extreme for preuniversity students, Howard says.

“Depending on where you go to school, you may not know what an engineer does or even consider engineering as an option,” she says, “so there’s still a big disconnect there.”

Howard has been involved for many years in math- and science-mentoring programs for at-risk high school girls. She tells them to find what they’re passionate about and combine it with math and science to create something. She also advises them not to let anyone tell them that they can’t.

Howard’s father is an engineer. She says he never encouraged or discouraged her to become one, but when she broke something, he would show her how to fix it and talk her through the process. Along the way, he taught her a logical way of thinking she says all engineers have.

“When I would try to explain something, he would quiz me and tell me to ‘think more logically,’” she says.

Howard earned a bachelor’s degree in engineering from Brown University, in Providence, R.I., then she received both a master’s and doctorate degree in electrical engineering from the University of Southern California. Before joining the faculty of Georgia Tech in 2005, she worked at NASA’s Jet Propulsion Laboratory at the California Institute of Technology for more than a decade as a senior robotics researcher and deputy manager in the Office of the Chief Scientist.

ACTIVE VOLUNTEER
Howard’s father was also an IEEE member, but that’s not why she joined the organization. She says she signed up when she was a student because, “that was something that you just did. Plus, my student membership fee was subsidized.”

She kept the membership as a grad student because of the discounted rates members receive on conferences.

Those conferences have had an impact on her career. “They allow you to understand what the state of the art is,” she says. “Back then you received a printed conference proceeding and reading through it was brutal, but by attending it in person, you got a 15-minute snippet about the research.”

Howard is an active volunteer with the IEEE Robotics and Automation and the IEEE Systems, Man, and Cybernetics societies, holding many positions and serving on several committees. She is also featured in the IEEE Impact Creators campaign. These members were selected because they inspire others to innovate for a better tomorrow.

“I value IEEE for its community,” she says. “One of the nice things about IEEE is that it’s international.” Continue reading →

Posted in Human Robots

#435683 How High Fives Help Us Get in Touch With ...

Posted on September 16, 2019 by Android

The human sense of touch is so naturally ingrained in our everyday lives that we often don’t notice its presence. Even so, touch is a crucial sensing ability that helps people to understand the world and connect with others. As the market for robots grows, and as robots become more ingrained into our environments, people will expect robots to participate in a wide variety of social touch interactions. At Oregon State University’s Collaborative Robotics and Intelligent Systems (CoRIS) Institute, I research how to equip everyday robots with better social-physical interaction skills—from playful high-fives to challenging physical therapy routines.

Some commercial robots already possess certain physical interaction skills. For example, the videoconferencing feature of mobile telepresence robots can keep far-away family members connected with one another. These robots can also roam distant spaces and bump into people, chairs, and other remote objects. And my Roomba occasionally tickles my toes before turning to vacuum a different area of the room. As a human being, I naturally interpret this (and other Roomba behaviors) as social, even if they were not intended as such. At the same time, for both of these systems, social perceptions of the robots’ physical interaction behaviors are not well understood, and these social touch-like interactions cannot be controlled in nuanced ways.

Before joining CoRIS early this year, I was a postdoc at the University of Southern California’s Interaction Lab, and prior to that, I completed my doctoral work at the GRASP Laboratory’s Haptics Group at the University of Pennsylvania. My dissertation focused on improving the general understanding of how robot control and planning strategies influence perceptions of social touch interactions. As part of that research, I conducted a study of human-robot hand-to-hand contact, focusing on an interaction somewhere between a high five and a hand-clapping game. I decided to study this particular interaction because people often high five, and they will likely expect robots in everyday spaces to high five as well!

I conducted a study of human-robot hand-to-hand contact, focusing on an interaction somewhere between a high five and a hand-clapping game. I decided to study this particular interaction because people often high five, and they will likely expect robots to high five as well!

The implications of motion and planning on the social touch experience in these interactions is also crucial—think about a disappointingly wimpy (or triumphantly amazing) high five that you’ve experienced in the past. This great or terrible high-fiving experience could be fleeting, but it could also influence who you interact with, who you’re friends with, and even how you perceive the character or personalities of those around you. This type of perception, judgement, and response could extend to personal robots, too!

An investigation like this requires a mixture of more traditional robotics research (e.g., understanding how to move and control a robot arm, developing models of the desired robot motion) along with techniques from design and psychology (e.g., performing interviews with research participants, using best practices from experimental methods in perception). Enabling robots with social touch abilities also comes with many challenges, and even skilled humans can have trouble anticipating what another person is about to do. Think about trying to make satisfying hand contact during a high five—you might know the classic adage “watch the elbow,” but if you’re like me, even this may not always work.

I conducted a research study involving eight different types of human-robot hand contact, with different combinations of the following: interactions with a facially reactive or non-reactive robot, a physically reactive or non-reactive planning strategy, and a lower or higher robot arm stiffness. My robotic system could become facially reactive by changing its facial expression in response to hand contact, or physically reactive by updating its plan of where to move next after sensing hand contact. The stiffness of the robot could be adjusted by changing a variable that controlled how quickly the robot’s motors tried to pull its arm to the desired position. I knew from previous research that fine differences in touch interactions can have a big impact on perceived robot character. For example, if a robot grips an object too tightly or for too long while handing an object to a person, it might be perceived as greedy, possessive, or perhaps even Sméagol-like. A robot that lets go too soon might appear careless or sloppy.

In the example cases of robot grip, it’s clear that understanding people’s perceptions of robot characteristics and personality can help roboticists choose the right robot design based on the proposed operating environment of the robot. I likewise wanted to learn how the facial expressions, physical reactions, and stiffness of a hand-clapping robot would influence human perceptions of robot pleasantness, energeticness, dominance, and safety. Understanding this relationship can help roboticists to equip robots with personalities appropriate for the task at hand. For example, a robot assisting people in a grocery store may need to be designed with a high level of pleasantness and only moderate energy, while a maximally effective robot for comedy roast battles may need high degrees of energy and dominance above all else.

After many a late night at the GRASP Lab clapping hands with a big red robot, I was ready to conduct the study. Twenty participants visited the lab to clap hands with our Baxter Research Robot and help me begin to understand how characteristics of this humanoid robot’s social touch influenced its pleasantness, energeticness, dominance, and apparent safety. Baxter interacted with participants using a custom 3D-printed hand that was inlaid with silicone inserts.

The study showed that a facially reactive robot seemed more pleasant and energetic. A physically reactive robot seemed less pleasant, energetic, and dominant for this particular study design and interaction. I thought contact with a stiffer robot would seem harder (and therefore more dominant and less safe), but counter to my expectations, a stiffer-armed robot seemed safer and less dominant to participants. This may be because the stiffer robot was more precise in following its pre-programmed trajectory, therefore seeming more predictable and less free-spirited.

Safety ratings of the robot were generally high, and several participants commented positively on the robot’s facial expressions. Some participants attributed inventive (and non-existent) intelligences to the robot—I used neither computer vision nor the Baxter robot’s cameras in this study, but more than one participant complimented me on how well the robot tracked their hand position. While interacting with the robot, participants displayed happy facial expressions more than any other analyzed type of expression.

Photo: Naomi Fitter

Participants were asked to clap hands with Baxter and describe how they perceived the robot in terms of its pleasantness, energeticness, dominance, and apparent safety.

Circling back to the idea of how people might interpret even rudimentary and practical robot behaviors as social, these results show that this type of social perception isn’t just true for my lovable (but sometimes dopey) Roomba, but also for collaborative industrial robots, and generally, any robot capable of physical human-robot interaction. In designing the motion of Baxter, the adjustment of a single number in the equation that controls joint stiffness can flip the robot from seeming safe and docile to brash and commanding. These implications are sometimes predictable, but often unexpected.

The results of this particular study give us a partial guide to manipulating the emotional experience of robot users by adjusting aspects of robot control and planning, but future work is needed to fully understand the design space of social touch. Will materials play a major role? How about personalized machine learning? Do results generalize over all robot arms, or even a specialized subset like collaborative industrial robot arms? I’m planning to continue answering these questions, and when I finally solve human-robot social touch, I’ll high five all my robots to celebrate.

Naomi Fitter is an assistant professor in the Collaborative Robotics and Intelligent Systems (CoRIS) Institute at Oregon State University, where her Social Haptics, Assistive Robotics, and Embodiment (SHARE) research group aims to equip robots with the ability to engage and empower people in interactions from playful high-fives to challenging physical therapy routines. She completed her doctoral work in the GRASP Laboratory’s Haptics Group and was a postdoctoral scholar in the University of Southern California’s Interaction Lab from 2017 to 2018. Naomi’s not-so-secret pastime is performing stand-up and improv comedy. Continue reading →

Posted in Human Robots

#435674 MIT Future of Work Report: We ...

Posted on September 16, 2019 by Android

Robots aren’t going to take everyone’s jobs, but technology has already reshaped the world of work in ways that are creating clear winners and losers. And it will continue to do so without intervention, says the first report of MIT’s Task Force on the Work of the Future.

The supergroup of MIT academics was set up by MIT President Rafael Reif in early 2018 to investigate how emerging technologies will impact employment and devise strategies to steer developments in a positive direction. And the headline finding from their first publication is that it’s not the quantity of jobs we should be worried about, but the quality.

Widespread press reports of a looming “employment apocalypse” brought on by AI and automation are probably wide of the mark, according to the authors. Shrinking workforces as developed countries age and outstanding limitations in what machines can do mean we’re unlikely to have a shortage of jobs.

But while unemployment is historically low, recent decades have seen a polarization of the workforce as the number of both high- and low-skilled jobs have grown at the expense of the middle-skilled ones, driving growing income inequality and depriving the non-college-educated of viable careers.

This is at least partly attributable to the growth of digital technology and automation, the report notes, which are rendering obsolete many middle-skilled jobs based around routine work like assembly lines and administrative support.

That leaves workers to either pursue high-skilled jobs that require deep knowledge and creativity, or settle for low-paid jobs that rely on skills—like manual dexterity or interpersonal communication—that are still beyond machines, but generic to most humans and therefore not valued by employers. And the growth of emerging technology like AI and robotics is only likely to exacerbate the problem.

This isn’t the first report to note this trend. The World Bank’s 2016 World Development Report noted how technology is causing a “hollowing out” of labor markets. But the MIT report goes further in saying that the cause isn’t simply technology, but the institutions and policies we’ve built around it.

The motivation for introducing new technology is broadly assumed to be to increase productivity, but the authors note a rarely-acknowledged fact: “Not all innovations that raise productivity displace workers, and not all innovations that displace workers substantially raise productivity.”

Examples of the former include computer-aided design software that makes engineers and architects more productive, while examples of the latter include self-service checkouts and automated customer support that replace human workers, often at the expense of a worse customer experience.

While the report notes that companies have increasingly adopted the language of technology augmenting labor, in reality this has only really benefited high-skilled workers. For lower-skilled jobs the motivation is primarily labor cost savings, which highlights the other major force shaping technology’s impact on employment: shareholder capitalism.

The authors note that up until the 1980s, increasing productivity resulted in wage growth across the economic spectrum, but since then average wage growth has failed to keep pace and gains have dramatically skewed towards the top earners.

The report shies away from directly linking this trend to the birth of Reaganomics (something others have been happy to do), but it notes that American veneration of the shareholder as the primary stakeholder in a business and tax policies that incentivize investment in capital rather than labor have exacerbated the negative impacts technology can have on employment.

That means the current focus on re-skilling workers to thrive in the new economy is a necessary, but not sufficient, solution to the disruptive impact technology is having on work, the authors say.

Alongside significant investment in education, fiscal policies need to be re-balanced away from subsidizing investment in physical capital and towards boosting investment in human capital, the authors write, and workers need to have a greater say in corporate decision-making.

The authors point to other developed economies where productivity growth, income growth, and equality haven’t become so disconnected thanks to investments in worker skills, social safety nets, and incentives to invest in human capital. Whether such a radical reshaping of US economic policy is achievable in today’s political climate remains to be seen, but the authors conclude with a call to arms.

“The failure of the US labor market to deliver broadly shared prosperity despite rising productivity is not an inevitable byproduct of current technologies or free markets,” they write. “We can and should do better.”

Image Credit: Simon Abrams / Unsplash/a> Continue reading →

Posted in Human Robots

#435662 Video Friday: This 3D-Printed ...

Posted on September 15, 2019 by Android

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):

ICRES 2019 – July 29-30, 2019 – London, U.K.
DARPA SubT Tunnel Circuit – August 15-22, 2019 – Pittsburgh, Pa., USA
IEEE Africon 2019 – September 25-27, 2019 – Accra, Ghana
ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam
Ro-Man 2019 – October 14-18, 2019 – New Delhi, India
Humanoids 2019 – October 15-17, 2019 – Toronto, Canada
Let us know if you have suggestions for next week, and enjoy today’s videos.

We’re used to seeing bristle bots about the size of a toothbrush head (which is not a coincidence), but Georgia Tech has downsized them, with some interesting benefits.

Researchers have created a new type of tiny 3D-printed robot that moves by harnessing vibration from piezoelectric actuators, ultrasound sources or even tiny speakers. Swarms of these “micro-bristle-bots” might work together to sense environmental changes, move materials – or perhaps one day repair injuries inside the human body.

The prototype robots respond to different vibration frequencies depending on their configurations, allowing researchers to control individual bots by adjusting the vibration. Approximately two millimeters long – about the size of the world’s smallest ant – the bots can cover four times their own length in a second despite the physical limitations of their small size.

“We are working to make the technology robust, and we have a lot of potential applications in mind,” said Azadeh Ansari, an assistant professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. “We are working at the intersection of mechanics, electronics, biology and physics. It’s a very rich area and there’s a lot of room for multidisciplinary concepts.”

[ Georgia Tech ]

Most consumer drones are “multi-copters,” meaning that they have a series of rotors or propellers that allow them to hover like helicopters. But having rotors severely limits their energy efficiency, which means that they can’t easily carry heavy payloads or fly for long periods of time. To get the best of both worlds, drone designers have tried to develop “hybrid” fixed-wing drones that can fly as efficiently as airplanes, while still taking off and landing vertically like multi-copters.

These drones are extremely hard to control because of the complexity of dealing with their flight dynamics, but a team from MIT CSAIL aims to make the customization process easier, with a new system that allows users to design drones of different sizes and shapes that can nimbly switch between hovering and gliding – all by using a single controller.

In future work, the team plans to try to further increase the drone’s maneuverability by improving its design. The model doesn’t yet fully take into account complex aerodynamic effects between the propeller’s airflow and the wings. And lastly, their method trained the copter with “yaw velocity” set at zero, which means that it cannot currently perform sharp turns.

[ Paper ] via [ MIT ]

We’re not quite at the point where we can 3D print entire robots, but UCSD is getting us closer.

The UC San Diego researchers’ insight was twofold. They turned to a commercially available printer for the job, (the Stratasys Objet350 Connex3—a workhorse in many robotics labs). In addition, they realized one of the materials used by the 3D printer is made of carbon particles that can conduct power to sensors when connected to a power source. So roboticists used the black resin to manufacture complex sensors embedded within robotic parts made of clear polymer. They designed and manufactured several prototypes, including a gripper.

When stretched, the sensors failed at approximately the same strain as human skin. But the polymers the 3D printer uses are not designed to conduct electricity, so their performance is not optimal. The 3D printed robots also require a lot of post-processing before they can be functional, including careful washing to clean up impurities and drying.

However, researchers remain optimistic that in the future, materials will improve and make 3D printed robots equipped with embedded sensors much easier to manufacture.

[ UCSD ]

Congrats to Team Homer from the University of Koblenz-Landau, who won the RoboCup@Home world championship in Sydney!

[ Team Homer ]

When you’ve got a robot with both wheels and legs, motion planning is complicated. IIT has developed a new planner for CENTAURO that takes advantage of the different ways that the robot is able to get past obstacles.

[ Centauro ]

Thanks Dimitrios!

If you constrain a problem tightly enough, you can solve it even with a relatively simple robot. Here’s an example of an experimental breakfast robot named “Loraine” that can cook eggs, bacon, and potatoes using what looks to be zero sensing at all, just moving to different positions and actuating its gripper.

There’s likely to be enough human work required in the prep here to make the value that the robot adds questionable at best, but it’s a good example of how you can make a relatively complex task robot-compatible as long as you set it up in just the right way.

[ Connected Robotics ] via [ RobotStart ]

It’s been a while since we’ve seen a ball bot, and I’m not sure that I’ve ever seen one with a manipulator on it.

[ ETH Zurich RSL ]

Soft Robotics’ new mini fingers are able to pick up taco shells without shattering them, which as far as I can tell is 100 percent impossible for humans to do.

[ Soft Robotics ]

Yes, Starship’s wheeled robots can climb curbs, and indeed they have a pretty neat way of doing it.

[ Starship ]

Last year we posted a long interview with Christoph Bartneck about his research into robots and racism, and here’s a nice video summary of the work.

[ Christoph Bartneck ]

Canada’s contribution to the Lunar Gateway will be a smart robotic system which includes a next-generation robotic arm known as Canadarm3, as well as equipment, and specialized tools. Using cutting-edge software and advances in artificial intelligence, this highly-autonomous system will be able to maintain, repair and inspect the Gateway, capture visiting vehicles, relocate Gateway modules, help astronauts during spacewalks, and enable science both in lunar orbit and on the surface of the Moon.

[ CSA ]

An interesting demo of how Misty can integrate sound localization with other services.

[ Misty Robotics ]

The third and last period of H2020 AEROARMS project has brought the final developments in industrial inspection and maintenance tasks, such as the crawler retrieval and deployment (DLR) or the industrial validation in stages like a refinery or a cement factory.

[ Aeroarms ]

The Guardian S remote visual inspection and surveillance robot navigates a disaster training site to demonstrate its advanced maneuverability, long-range wireless communications and extended run times.

[ Sarcos ]

This appears to be a cake frosting robot and I wish I had like 3 more hours of this to share:

Also here is a robot that picks fried chicken using a curiously successful technique:

[ Kazumichi Moriyama ]

This isn’t strictly robots, but professor Hiroshi Ishii, associate director of the MIT Media Lab, gave a fascinating SIGCHI Lifetime Achievement Talk that’s absolutely worth your time.

[ Tangible Media Group ] Continue reading →

Posted in Human Robots

#435656 Will AI Be Fashion Forward—or a ...

Posted on September 15, 2019 by Android

The narrative that often accompanies most stories about artificial intelligence these days is how machines will disrupt any number of industries, from healthcare to transportation. It makes sense. After all, technology already drives many of the innovations in these sectors of the economy.

But sneakers and the red carpet? The definitively low-tech fashion industry would seem to be one of the last to turn over its creative direction to data scientists and machine learning algorithms.

However, big brands, e-commerce giants, and numerous startups are betting that AI can ingest data and spit out Chanel. Maybe it’s not surprising, given that fashion is partly about buzz and trends—and there’s nothing more buzzy and trendy in the world of tech today than AI.

In its annual survey of the $3 trillion fashion industry, consulting firm McKinsey predicted that while AI didn’t hit a “critical mass” in 2018, it would increasingly influence the business of everything from design to manufacturing.

“Fashion as an industry really has been so slow to understand its potential roles interwoven with technology. And, to be perfectly honest, the technology doesn’t take fashion seriously.” This comment comes from Zowie Broach, head of fashion at London’s Royal College of Arts, who as a self-described “old fashioned” designer has embraced the disruptive nature of technology—with some caveats.

Co-founder in the late 1990s of the avant-garde fashion label Boudicca, Broach has always seen tech as a tool for designers, even setting up a website for the company circa 1998, way before an online presence became, well, fashionable.

Broach told Singularity Hub that while she is generally optimistic about the future of technology in fashion—the designer has avidly been consuming old sci-fi novels over the last few years—there are still a lot of difficult questions to answer about the interface of algorithms, art, and apparel.

For instance, can AI do what the great designers of the past have done? Fashion was “about designing, it was about a narrative, it was about meaning, it was about expression,” according to Broach.

AI that designs products based on data gleaned from human behavior can potentially tap into the Pavlovian response in consumers in order to make money, Broach noted. But is that channeling creativity, or just digitally dabbling in basic human brain chemistry?

She is concerned about people retaining control of the process, whether we’re talking about their data or their designs. But being empowered with the insights machines could provide into, for example, the geographical nuances of fashion between Dubai, Moscow, and Toronto is thrilling.

“What is it that we want the future to be from a fashion, an identity, and design perspective?” she asked.

Off on the Right Foot
Silicon Valley and some of the biggest brands in the industry offer a few answers about where AI and fashion are headed (though not at the sort of depths that address Broach’s broader questions of aesthetics and ethics).

Take what is arguably the biggest brand in fashion, at least by market cap but probably not by the measure of appearances on Oscar night: Nike. The $100 billion shoe company just gobbled up an AI startup called Celect to bolster its data analytics and optimize its inventory. In other words, Nike hopes it will be able to figure out what’s hot and what’s not in a particular location to stock its stores more efficiently.

The company is going even further with Nike Fit, a foot-scanning platform using a smartphone camera that applies AI techniques from fields like computer vision and machine learning to find the best fit for each person’s foot. The algorithms then identify and recommend the appropriately sized and shaped shoe in different styles.

No doubt the next step will be to 3D print personalized and on-demand sneakers at any store.

San Francisco-based startup ThirdLove is trying to bring a similar approach to bra sizes. Its 20-member data team, Fortune reported, has developed the Fit Finder quiz that uses machine learning algorithms to help pick just the right garment for every body type.

Data scientists are also a big part of the team at Stitch Fix, a former San Francisco startup that went public in 2017 and today sports a market cap of more than $2 billion. The online “personal styling” company uses hundreds of algorithms to not only make recommendations to customers, but to help design new styles and even manage the subscription-based supply chain.

Future of Fashion
E-commerce giant Amazon has thrown its own considerable resources into developing AI applications for retail fashion—with mixed results.

One notable attempt involved a “styling assistant” that came with the company’s Echo Look camera that helped people catalog and manage their wardrobes, evening helping pick out each day’s attire. The company more recently revisited the direct consumer side of AI with an app called StyleSnap, which matches clothes and accessories uploaded to the site with the retailer’s vast inventory and recommends similar styles.

Behind the curtains, Amazon is going even further. A team of researchers in Israel have developed algorithms that can deduce whether a particular look is stylish based on a few labeled images. Another group at the company’s San Francisco research center was working on tech that could generate new designs of items based on images of a particular style the algorithms trained on.

“I will say that the accumulation of many new technologies across the industry could manifest in a highly specialized style assistant, far better than the examples we’ve seen today. However, the most likely thing is that the least sexy of the machine learning work will become the most impactful, and the public may never hear about it.”

That prediction is from an online interview with Leanne Luce, a fashion technology blogger and product manager at Google who recently wrote a book called, succinctly enough, Artificial Intelligence and Fashion.

Data Meets Design
Academics are also sticking their beakers into AI and fashion. Researchers at the University of California, San Diego, and Adobe Research have previously demonstrated that neural networks, a type of AI designed to mimic some aspects of the human brain, can be trained to generate (i.e., design) new product images to match a buyer’s preference, much like the team at Amazon.

Meanwhile, scientists at Hong Kong Polytechnic University are working with China’s answer to Amazon, Alibaba, on developing a FashionAI Dataset to help machines better understand fashion. The effort will focus on how algorithms approach certain building blocks of design, what are called “key points” such as neckline and waistline, and “fashion attributes” like collar types and skirt styles.

The man largely behind the university’s research team is Calvin Wong, a professor and associate head of Hong Kong Polytechnic University’s Institute of Textiles and Clothing. His group has also developed an “intelligent fabric defect detection system” called WiseEye for quality control, reducing the chance of producing substandard fabric by 90 percent.

Wong and company also recently inked an agreement with RCA to establish an AI-powered design laboratory, though the details of that venture have yet to be worked out, according to Broach.

One hope is that such collaborations will not just get at the technological challenges of using machines in creative endeavors like fashion, but will also address the more personal relationships humans have with their machines.

“I think who we are, and how we use AI in fashion, as our identity, is not a superficial skin. It’s very, very important for how we define our future,” Broach said.

Image Credit: Inspirationfeed / Unsplash Continue reading →

Posted in Human Robots