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#436252 After AI, Fashion and Shopping Will ...

AI and broadband are eating retail for breakfast. In the first half of 2019, we’ve seen 19 retailer bankruptcies. And the retail apocalypse is only accelerating.

What’s coming next is astounding. Why drive when you can speak? Revenue from products purchased via voice commands is expected to quadruple from today’s US$2 billion to US$8 billion by 2023.

Virtual reality, augmented reality, and 3D printing are converging with artificial intelligence, drones, and 5G to transform shopping on every dimension. And as a result, shopping is becoming dematerialized, demonetized, democratized, and delocalized… a top-to-bottom transformation of the retail world.

Welcome to Part 1 of our series on the future of retail, a deep-dive into AI and its far-reaching implications.

Let’s dive in.

A Day in the Life of 2029
Welcome to April 21, 2029, a sunny day in Dallas. You’ve got a fundraising luncheon tomorrow, but nothing to wear. The last thing you want to do is spend the day at the mall.

No sweat. Your body image data is still current, as you were scanned only a week ago. Put on your VR headset and have a conversation with your AI. “It’s time to buy a dress for tomorrow’s event” is all you have to say. In a moment, you’re teleported to a virtual clothing store. Zero travel time. No freeway traffic, parking hassles, or angry hordes wielding baby strollers.

Instead, you’ve entered your own personal clothing store. Everything is in your exact size…. And I mean everything. The store has access to nearly every designer and style on the planet. Ask your AI to show you what’s hot in Shanghai, and presto—instant fashion show. Every model strutting down the runway looks exactly like you, only dressed in Shanghai’s latest.

When you’re done selecting an outfit, your AI pays the bill. And as your new clothes are being 3D printed at a warehouse—before speeding your way via drone delivery—a digital version has been added to your personal inventory for use at future virtual events.

The cost? Thanks to an era of no middlemen, less than half of what you pay in stores today. Yet this future is not all that far off…

Digital Assistants
Let’s begin with the basics: the act of turning desire into purchase.

Most of us navigate shopping malls or online marketplaces alone, hoping to stumble across the right item and fit. But if you’re lucky enough to employ a personal assistant, you have the luxury of describing what you want to someone who knows you well enough to buy that exact right thing most of the time.

For most of us who don’t, enter the digital assistant.

Right now, the four horsemen of the retail apocalypse are waging war for our wallets. Amazon’s Alexa, Google’s Now, Apple’s Siri, and Alibaba’s Tmall Genie are going head-to-head in a battle to become the platform du jour for voice-activated, AI-assisted commerce.

For baby boomers who grew up watching Captain Kirk talk to the Enterprise’s computer on Star Trek, digital assistants seem a little like science fiction. But for millennials, it’s just the next logical step in a world that is auto-magical.

And as those millennials enter their consumer prime, revenue from products purchased via voice-driven commands is projected to leap from today’s US$2 billion to US$8 billion by 2023.

We are already seeing a major change in purchasing habits. On average, consumers using Amazon Echo spent more than standard Amazon Prime customers: US$1,700 versus US$1,300.

And as far as an AI fashion advisor goes, those too are here, courtesy of both Alibaba and Amazon. During its annual Singles’ Day (November 11) shopping festival, Alibaba’s FashionAI concept store uses deep learning to make suggestions based on advice from human fashion experts and store inventory, driving a significant portion of the day’s US$25 billion in sales.

Similarly, Amazon’s shopping algorithm makes personalized clothing recommendations based on user preferences and social media behavior.

Customer Service
But AI is disrupting more than just personalized fashion and e-commerce. Its next big break will take place in the customer service arena.

According to a recent Zendesk study, good customer service increases the possibility of a purchase by 42 percent, while bad customer service translates into a 52 percent chance of losing that sale forever. This means more than half of us will stop shopping at a store due to a single disappointing customer service interaction. These are significant financial stakes. They’re also problems perfectly suited for an AI solution.

During the 2018 Google I/O conference, CEO Sundar Pichai demoed the Google Duplex, their next generation digital assistant. Pichai played the audience a series of pre-recorded phone calls made by Google Duplex. The first call made a reservation at a restaurant, the second one booked a haircut appointment, amusing the audience with a long “hmmm” mid-call.

In neither case did the person on the other end of the phone have any idea they were talking to an AI. The system’s success speaks to how seamlessly AI can blend into our retail lives and how convenient it will continue to make them. The same technology Pichai demonstrated that can make phone calls for consumers can also answer phones for retailers—a development that’s unfolding in two different ways:

(1) Customer service coaches: First, for organizations interested in keeping humans involved, there’s Beyond Verbal, a Tel Aviv-based startup that has built an AI customer service coach. Simply by analyzing customer voice intonation, the system can tell whether the person on the phone is about to blow a gasket, is genuinely excited, or anything in between.

Based on research of over 70,000 subjects in more than 30 languages, Beyond Verbal’s app can detect 400 different markers of human moods, attitudes, and personality traits. Already it’s been integrated in call centers to help human sales agents understand and react to customer emotions, making those calls more pleasant, and also more profitable.

For example, by analyzing word choice and vocal style, Beyond Verbal’s system can tell what kind of shopper the person on the line actually is. If they’re an early adopter, the AI alerts the sales agent to offer them the latest and greatest. If they’re more conservative, it suggests items more tried-and-true.

(2) Replacing customer service agents: Second, companies like New Zealand’s Soul Machines are working to replace human customer service agents altogether. Powered by IBM’s Watson, Soul Machines builds lifelike customer service avatars designed for empathy, making them one of many helping to pioneer the field of emotionally intelligent computing.

With their technology, 40 percent of all customer service interactions are now resolved with a high degree of satisfaction, no human intervention needed. And because the system is built using neural nets, it’s continuously learning from every interaction—meaning that percentage will continue to improve.

The number of these interactions continues to grow as well. Software manufacturer Autodesk now includes a Soul Machine avatar named AVA (Autodesk Virtual Assistant) in all of its new offerings. She lives in a small window on the screen, ready to soothe tempers, troubleshoot problems, and forever banish those long tech support hold times.

For Daimler Financial Services, Soul Machines built an avatar named Sarah, who helps customers with arguably three of modernity’s most annoying tasks: financing, leasing, and insuring a car.

This isn’t just about AI—it’s about AI converging with additional exponentials. Add networks and sensors to the story and it raises the scale of disruption, upping the FQ—the frictionless quotient—in our frictionless shopping adventure.

Final Thoughts
AI makes retail cheaper, faster, and more efficient, touching everything from customer service to product delivery. It also redefines the shopping experience, making it frictionless and—once we allow AI to make purchases for us—ultimately invisible.

Prepare for a future in which shopping is dematerialized, demonetized, democratized, and delocalized—otherwise known as “the end of malls.”

Of course, if you wait a few more years, you’ll be able to take an autonomous flying taxi to Westfield’s Destination 2028—so perhaps today’s converging exponentials are not so much spelling the end of malls but rather the beginning of an experience economy far smarter, more immersive, and whimsically imaginative than today’s shopping centers.

Either way, it’s a top-to-bottom transformation of the retail world.

Over the coming blog series, we will continue our discussion of the future of retail. Stay tuned to learn new implications for your business and how to future-proof your company in an age of smart, ultra-efficient, experiential retail.

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If you’d like to learn more and consider joining our 2020 membership, apply here.

(2) Abundance-Digital Online Community: I’ve also created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is Singularity University’s ‘onramp’ for exponential entrepreneurs — those who want to get involved and play at a higher level. Click here to learn more.

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This article originally appeared on diamandis.com. Read the original article here.

Image Credit: Image by Pexels from Pixabay Continue reading

Posted in Human Robots

#436218 An AI Debated Its Own Potential for Good ...

Artificial intelligence is going to overhaul the way we live and work. But will the changes it brings be for the better? As the technology slowly develops (let’s remember that right now, we’re still very much in the narrow AI space and nowhere near an artificial general intelligence), whether it will end up doing us more harm than good is a question at the top of everyone’s mind.

What kind of response might we get if we posed this question to an AI itself?

Last week at the Cambridge Union in England, IBM did just that. Its Project Debater (an AI that narrowly lost a debate to human debating champion Harish Natarajan in February) gave the opening arguments in a debate about the promise and peril of artificial intelligence.

Critical thinking, linking different lines of thought, and anticipating counter-arguments are all valuable debating skills that humans can practice and refine. While these skills are tougher for an AI to get good at since they often require deeper contextual understanding, AI does have a major edge over humans in absorbing and analyzing information. In the February debate, Project Debater used IBM’s cloud computing infrastructure to read hundreds of millions of documents and extract relevant details to construct an argument.

This time around, Debater looked through 1,100 arguments for or against AI. The arguments were submitted to IBM by the public during the week prior to the debate, through a website set up for that purpose. Of the 1,100 submissions, the AI classified 570 as anti-AI, or of the opinion that the technology will bring more harm to humanity than good. 511 arguments were found to be pro-AI, and the rest were irrelevant to the topic at hand.

Debater grouped the arguments into five themes; the technology’s ability to take over dangerous or monotonous jobs was a pro-AI theme, and on the flip side was its potential to perpetuate the biases of its creators. “AI companies still have too little expertise on how to properly assess datasets and filter out bias,” the tall black box that houses Project Debater said. “AI will take human bias and will fixate it for generations.”
After Project Debater kicked off the debate by giving opening arguments for both sides, two teams of people took over, elaborating on its points and coming up with their own counter-arguments.

In the end, an audience poll voted in favor of the pro-AI side, but just barely; 51.2 percent of voters felt convinced that AI can help us more than it can hurt us.

The software’s natural language processing was able to identify racist, obscene, or otherwise inappropriate comments and weed them out as being irrelevant to the debate. But it also repeated the same arguments multiple times, and mixed up a statement about bias as being pro-AI rather than anti-AI.

IBM has been working on Project Debater for over six years, and though it aims to iron out small glitches like these, the system’s goal isn’t to ultimately outwit and defeat humans. On the contrary, the AI is meant to support our decision-making by taking in and processing huge amounts of information in a nuanced way, more quickly than we ever could.

IBM engineer Noam Slonim envisions Project Debater’s tech being used, for example, by a government seeking citizens’ feedback about a new policy. “This technology can help to establish an interesting and effective communication channel between the decision maker and the people that are going to be impacted by the decision,” he said.

As for the question of whether AI will do more good or harm, perhaps Sylvie Delacroix put it best. A professor of law and ethics at the University of Birmingham who argued on the pro-AI side of the debate, she pointed out that the impact AI will have depends on the way we design it, saying “AI is only as good as the data it has been fed.”

She’s right; rather than asking what sort of impact AI will have on humanity, we should start by asking what sort of impact we want it to have. The people working on AI—not AIs themselves—are ultimately responsible for how much good or harm will be done.

Image Credit: IBM Project Debater at Cambridge Union Society, photo courtesy of IBM Research Continue reading

Posted in Human Robots

#436207 This Week’s Awesome Tech Stories From ...

COMPUTING
A Giant Superfast AI Chip Is Being Used to Find Better Cancer Drugs
Karen Hao | MIT Technology Review
“Thus far, Cerebras’s computer has checked all the boxes. Thanks to its chip size—it is larger than an iPad and has 1.2 trillion transistors for making calculations—it isn’t necessary to hook multiple smaller processors together, which can slow down model training. In testing, it has already shrunk the training time of models from weeks to hours.”

MEDICINE
Humans Put Into Suspended Animation for First Time
Ian Sample | The Guardian
“The process involves rapidly cooling the brain to less than 10C by replacing the patient’s blood with ice-cold saline solution. Typically the solution is pumped directly into the aorta, the main artery that carries blood away from the heart to the rest of the body.”

DRONES
This Transforming Drone Can Be Fired Straight Out of a Cannon
James Vincent | The Verge
“Drones are incredibly useful machines in the air, but getting them up and flying can be tricky, especially in crowded, windy, or emergency scenarios when speed is a factor. But a group of researchers from Caltech university and NASA’s Jet Propulsion Laboratory have come up with an elegant and oh-so-fun solution: fire the damn thing out of a cannon.”

ROBOTICS
Alphabet’s Dream of an ‘Everyday Robot’ Is Just Out of Reach
Tom Simonite | Wired
“Sorting trash was chosen as a convenient challenge to test the project’s approach to creating more capable robots. It’s using artificial intelligence software developed in collaboration with Google to make robots that learn complex tasks through on-the-job experience. The hope is to make robots less reliant on human coding for their skills, and capable of adapting quickly to complex new tasks and environments.”

ENVIRONMENT
The Electric Car Revolution May Take a Lot Longer Than Expected
James Temple | MIT Technology Review
“A new report from the MIT Energy Initiative warns that EVs may never reach the same sticker price so long as they rely on lithium-ion batteries, the energy storage technology that powers most of today’s consumer electronics. In fact, it’s likely to take another decade just to eliminate the difference in the lifetime costs between the vehicle categories, which factors in the higher fuel and maintenance expenses of standard cars and trucks.”

SPACE
How Two Intruders From Interstellar Space Are Upending Astronomy
Alexandra Witze | Nature
“From the tallest peak in Hawaii to a high plateau in the Andes, some of the biggest telescopes on Earth will point towards a faint smudge of light over the next few weeks. …What they’re looking for is a rare visitor that is about to make its closest approach to the Sun. After that, they have just months to grab as much information as they can from the object before it disappears forever into the blackness of space.”

Image Credit: Simone Hutsch / Unsplash Continue reading

Posted in Human Robots

#436202 Trump CTO Addresses AI, Facial ...

Michael Kratsios, the Chief Technology Officer of the United States, took the stage at Stanford University last week to field questions from Stanford’s Eileen Donahoe and attendees at the 2019 Fall Conference of the Institute for Human-Centered Artificial Intelligence (HAI).

Kratsios, the fourth to hold the U.S. CTO position since its creation by President Barack Obama in 2009, was confirmed in August as President Donald Trump’s first CTO. Before joining the Trump administration, he was chief of staff at investment firm Thiel Capital and chief financial officer of hedge fund Clarium Capital. Donahoe is Executive Director of Stanford’s Global Digital Policy Incubator and served as the first U.S. Ambassador to the United Nations Human Rights Council during the Obama Administration.

The conversation jumped around, hitting on both accomplishments and controversies. Kratsios touted the administration’s success in fixing policy around the use of drones, its memorandum on STEM education, and an increase in funding for basic research in AI—though the magnitude of that increase wasn’t specified. He pointed out that the Trump administration’s AI policy has been a continuation of the policies of the Obama administration, and will continue to build on that foundation. As proof of this, he pointed to Trump’s signing of the American AI Initiative earlier this year. That executive order, Kratsios said, was intended to bring various government agencies together to coordinate their AI efforts and to push the idea that AI is a tool for the American worker. The AI Initiative, he noted, also took into consideration that AI will cause job displacement, and asked private companies to pledge to retrain workers.

The administration, he said, is also looking to remove barriers to AI innovation. In service of that goal, the government will, in the next month or so, release a regulatory guidance memo instructing government agencies about “how they should think about AI technologies,” said Kratsios.

U.S. vs China in AI

A few of the exchanges between Kratsios and Donahoe hit on current hot topics, starting with the tension between the U.S. and China.

Donahoe:

“You talk a lot about unique U.S. ecosystem. In which aspect of AI is the U.S. dominant, and where is China challenging us in dominance?

Kratsios:

“They are challenging us on machine vision. They have more data to work with, given that they have surveillance data.”

Donahoe:

“To what extent would you say the quantity of data collected and available will be a determining factor in AI dominance?”

Kratsios:

“It makes a big difference in the short term. But we do research on how we get over these data humps. There is a future where you don’t need as much data, a lot of federal grants are going to [research in] how you can train models using less data.”

Donahoe turned the conversation to a different tension—that between innovation and values.

Donahoe:

“A lot of conversation yesterday was about the tension between innovation and values, and how do you hold those things together and lead in both realms.”

Kratsios:

“We recognized that the U.S. hadn’t signed on to principles around developing AI. In May, we signed [the Organization for Economic Cooperation and Development Principles on Artificial Intelligence], coming together with other Western democracies to say that these are values that we hold dear.

[Meanwhile,] we have adversaries around the world using AI to surveil people, to suppress human rights. That is why American leadership is so critical: We want to come out with the next great product. And we want our values to underpin the use cases.”

A member of the audience pushed further:

“Maintaining U.S. leadership in AI might have costs in terms of individuals and society. What costs should individuals and society bear to maintain leadership?”

Kratsios:

“I don’t view the world that way. Our companies big and small do not hesitate to talk about the values that underpin their technology. [That is] markedly different from the way our adversaries think. The alternatives are so dire [that we] need to push efforts to bake the values that we hold dear into this technology.”

Facial recognition

And then the conversation turned to the use of AI for facial recognition, an application which (at least for police and other government agencies) was recently banned in San Francisco.

Donahoe:

“Some private sector companies have called for government regulation of facial recognition, and there already are some instances of local governments regulating it. Do you expect federal regulation of facial recognition anytime soon? If not, what ought the parameters be?”

Kratsios:

“A patchwork of regulation of technology is not beneficial for the country. We want to avoid that. Facial recognition has important roles—for example, finding lost or displaced children. There are use cases, but they need to be underpinned by values.”

A member of the audience followed up on that topic, referring to some data presented earlier at the HAI conference on bias in AI:

“Frequently the example of finding missing children is given as the example of why we should not restrict use of facial recognition. But we saw Joy Buolamwini’s presentation on bias in data. I would like to hear your thoughts about how government thinks we should use facial recognition, knowing about this bias.”

Kratsios:

“Fairness, accountability, and robustness are things we want to bake into any technology—not just facial recognition—as we build rules governing use cases.”

Immigration and innovation

A member of the audience brought up the issue of immigration:

“One major pillar of innovation is immigration, does your office advocate for it?”

Kratsios:

“Our office pushes for best and brightest people from around the world to come to work here and study here. There are a few efforts we have made to move towards a more merit-based immigration system, without congressional action. [For example, in] the H1-B visa system, you go through two lotteries. We switched the order of them in order to get more people with advanced degrees through.”

The government’s tech infrastructure

Donahoe brought the conversation around to the tech infrastructure of the government itself:

“We talk about the shiny object, AI, but the 80 percent is the unsexy stuff, at federal and state levels. We don’t have a modern digital infrastructure to enable all the services—like a research cloud. How do we create this digital infrastructure?”

Kratsios:

“I couldn’t agree more; the least partisan issue in Washington is about modernizing IT infrastructure. We spend like $85 billion a year on IT at the federal level, we can certainly do a better job of using those dollars.” Continue reading

Posted in Human Robots

#436190 What Is the Uncanny Valley?

Have you ever encountered a lifelike humanoid robot or a realistic computer-generated face that seem a bit off or unsettling, though you can’t quite explain why?

Take for instance AVA, one of the “digital humans” created by New Zealand tech startup Soul Machines as an on-screen avatar for Autodesk. Watching a lifelike digital being such as AVA can be both fascinating and disconcerting. AVA expresses empathy through her demeanor and movements: slightly raised brows, a tilt of the head, a nod.

By meticulously rendering every lash and line in its avatars, Soul Machines aimed to create a digital human that is virtually undistinguishable from a real one. But to many, rather than looking natural, AVA actually looks creepy. There’s something about it being almost human but not quite that can make people uneasy.

Like AVA, many other ultra-realistic avatars, androids, and animated characters appear stuck in a disturbing in-between world: They are so lifelike and yet they are not “right.” This void of strangeness is known as the uncanny valley.

Uncanny Valley: Definition and History
The uncanny valley is a concept first introduced in the 1970s by Masahiro Mori, then a professor at the Tokyo Institute of Technology. The term describes Mori’s observation that as robots appear more humanlike, they become more appealing—but only up to a certain point. Upon reaching the uncanny valley, our affinity descends into a feeling of strangeness, a sense of unease, and a tendency to be scared or freaked out.

Image: Masahiro Mori

The uncanny valley as depicted in Masahiro Mori’s original graph: As a robot’s human likeness [horizontal axis] increases, our affinity towards the robot [vertical axis] increases too, but only up to a certain point. For some lifelike robots, our response to them plunges, and they appear repulsive or creepy. That’s the uncanny valley.

In his seminal essay for Japanese journal Energy, Mori wrote:

I have noticed that, in climbing toward the goal of making robots appear human, our affinity for them increases until we come to a valley, which I call the uncanny valley.

Later in the essay, Mori describes the uncanny valley by using an example—the first prosthetic hands:

One might say that the prosthetic hand has achieved a degree of resemblance to the human form, perhaps on a par with false teeth. However, when we realize the hand, which at first site looked real, is in fact artificial, we experience an eerie sensation. For example, we could be startled during a handshake by its limp boneless grip together with its texture and coldness. When this happens, we lose our sense of affinity, and the hand becomes uncanny.

In an interview with IEEE Spectrum, Mori explained how he came up with the idea for the uncanny valley:

“Since I was a child, I have never liked looking at wax figures. They looked somewhat creepy to me. At that time, electronic prosthetic hands were being developed, and they triggered in me the same kind of sensation. These experiences had made me start thinking about robots in general, which led me to write that essay. The uncanny valley was my intuition. It was one of my ideas.”

Uncanny Valley Examples
To better illustrate how the uncanny valley works, here are some examples of the phenomenon. Prepare to be freaked out.

1. Telenoid

Photo: Hiroshi Ishiguro/Osaka University/ATR

Taking the top spot in the “creepiest” rankings of IEEE Spectrum’s Robots Guide, Telenoid is a robotic communication device designed by Japanese roboticist Hiroshi Ishiguro. Its bald head, lifeless face, and lack of limbs make it seem more alien than human.

2. Diego-san

Photo: Andrew Oh/Javier Movellan/Calit2

Engineers and roboticists at the University of California San Diego’s Machine Perception Lab developed this robot baby to help parents better communicate with their infants. At 1.2 meters (4 feet) tall and weighing 30 kilograms (66 pounds), Diego-san is a big baby—bigger than an average 1-year-old child.

“Even though the facial expression is sophisticated and intuitive in this infant robot, I still perceive a false smile when I’m expecting the baby to appear happy,” says Angela Tinwell, a senior lecturer at the University of Bolton in the U.K. and author of The Uncanny Valley in Games and Animation. “This, along with a lack of detail in the eyes and forehead, can make the baby appear vacant and creepy, so I would want to avoid those ‘dead eyes’ rather than interacting with Diego-san.”

​3. Geminoid HI

Photo: Osaka University/ATR/Kokoro

Another one of Ishiguro’s creations, Geminoid HI is his android replica. He even took hair from his own scalp to put onto his robot twin. Ishiguro says he created Geminoid HI to better understand what it means to be human.

4. Sophia

Photo: Mikhail Tereshchenko/TASS/Getty Images

Designed by David Hanson of Hanson Robotics, Sophia is one of the most famous humanoid robots. Like Soul Machines’ AVA, Sophia displays a range of emotional expressions and is equipped with natural language processing capabilities.

5. Anthropomorphized felines

The uncanny valley doesn’t only happen with robots that adopt a human form. The 2019 live-action versions of the animated film The Lion King and the musical Cats brought the uncanny valley to the forefront of pop culture. To some fans, the photorealistic computer animations of talking lions and singing cats that mimic human movements were just creepy.

Are you feeling that eerie sensation yet?

Uncanny Valley: Science or Pseudoscience?
Despite our continued fascination with the uncanny valley, its validity as a scientific concept is highly debated. The uncanny valley wasn’t actually proposed as a scientific concept, yet has often been criticized in that light.

Mori himself said in his IEEE Spectrum interview that he didn’t explore the concept from a rigorous scientific perspective but as more of a guideline for robot designers:

Pointing out the existence of the uncanny valley was more of a piece of advice from me to people who design robots rather than a scientific statement.

Karl MacDorman, an associate professor of human-computer interaction at Indiana University who has long studied the uncanny valley, interprets the classic graph not as expressing Mori’s theory but as a heuristic for learning the concept and organizing observations.

“I believe his theory is instead expressed by his examples, which show that a mismatch in the human likeness of appearance and touch or appearance and motion can elicit a feeling of eeriness,” MacDorman says. “In my own experiments, I have consistently reproduced this effect within and across sense modalities. For example, a mismatch in the human realism of the features of a face heightens eeriness; a robot with a human voice or a human with a robotic voice is eerie.”

How to Avoid the Uncanny Valley
Unless you intend to create creepy characters or evoke a feeling of unease, you can follow certain design principles to avoid the uncanny valley. “The effect can be reduced by not creating robots or computer-animated characters that combine features on different sides of a boundary—for example, human and nonhuman, living and nonliving, or real and artificial,” MacDorman says.

To make a robot or avatar more realistic and move it beyond the valley, Tinwell says to ensure that a character’s facial expressions match its emotive tones of speech, and that its body movements are responsive and reflect its hypothetical emotional state. Special attention must also be paid to facial elements such as the forehead, eyes, and mouth, which depict the complexities of emotion and thought. “The mouth must be modeled and animated correctly so the character doesn’t appear aggressive or portray a ‘false smile’ when they should be genuinely happy,” she says.

For Christoph Bartneck, an associate professor at the University of Canterbury in New Zealand, the goal is not to avoid the uncanny valley, but to avoid bad character animations or behaviors, stressing the importance of matching the appearance of a robot with its ability. “We’re trained to spot even the slightest divergence from ‘normal’ human movements or behavior,” he says. “Hence, we often fail in creating highly realistic, humanlike characters.”

But he warns that the uncanny valley appears to be more of an uncanny cliff. “We find the likability to increase and then crash once robots become humanlike,” he says. “But we have never observed them ever coming out of the valley. You fall off and that’s it.” Continue reading

Posted in Human Robots