Tag Archives: less
#433288 The New AI Tech Turning Heads in Video ...
A new technique using artificial intelligence to manipulate video content gives new meaning to the expression “talking head.”
An international team of researchers showcased the latest advancement in synthesizing facial expressions—including mouth, eyes, eyebrows, and even head position—in video at this month’s 2018 SIGGRAPH, a conference on innovations in computer graphics, animation, virtual reality, and other forms of digital wizardry.
The project is called Deep Video Portraits. It relies on a type of AI called generative adversarial networks (GANs) to modify a “target” actor based on the facial and head movement of a “source” actor. As the name implies, GANs pit two opposing neural networks against one another to create a realistic talking head, right down to the sneer or raised eyebrow.
In this case, the adversaries are actually working together: One neural network generates content, while the other rejects or approves each effort. The back-and-forth interplay between the two eventually produces a realistic result that can easily fool the human eye, including reproducing a static scene behind the head as it bobs back and forth.
The researchers say the technique can be used by the film industry for a variety of purposes, from editing facial expressions of actors for matching dubbed voices to repositioning an actor’s head in post-production. AI can not only produce highly realistic results, but much quicker ones compared to the manual processes used today, according to the researchers. You can read the full paper of their work here.
“Deep Video Portraits shows how such a visual effect could be created with less effort in the future,” said Christian Richardt, from the University of Bath’s motion capture research center CAMERA, in a press release. “With our approach, even the positioning of an actor’s head and their facial expression could be easily edited to change camera angles or subtly change the framing of a scene to tell the story better.”
AI Tech Different Than So-Called “Deepfakes”
The work is far from the first to employ AI to manipulate video and audio. At last year’s SIGGRAPH conference, researchers from the University of Washington showcased their work using algorithms that inserted audio recordings from a person in one instance into a separate video of the same person in a different context.
In this case, they “faked” a video using a speech from former President Barack Obama addressing a mass shooting incident during his presidency. The AI-doctored video injects the audio into an unrelated video of the president while also blending the facial and mouth movements, creating a pretty credible job of lip synching.
A previous paper by many of the same scientists on the Deep Video Portraits project detailed how they were first able to manipulate a video in real time of a talking head (in this case, actor and former California governor Arnold Schwarzenegger). The Face2Face system pulled off this bit of digital trickery using a depth-sensing camera that tracked the facial expressions of an Asian female source actor.
A less sophisticated method of swapping faces using a machine learning software dubbed FakeApp emerged earlier this year. Predictably, the tech—requiring numerous photos of the source actor in order to train the neural network—was used for more juvenile pursuits, such as injecting a person’s face onto a porn star.
The application gave rise to the term “deepfakes,” which is now used somewhat ubiquitously to describe all such instances of AI-manipulated video—much to the chagrin of some of the researchers involved in more legitimate uses.
Fighting AI-Created Video Forgeries
However, the researchers are keenly aware that their work—intended for benign uses such as in the film industry or even to correct gaze and head positions for more natural interactions through video teleconferencing—could be used for nefarious purposes. Fake news is the most obvious concern.
“With ever-improving video editing technology, we must also start being more critical about the video content we consume every day, especially if there is no proof of origin,” said Michael Zollhöfer, a visiting assistant professor at Stanford University and member of the Deep Video Portraits team, in the press release.
Toward that end, the research team is training the same adversarial neural networks to spot video forgeries. They also strongly recommend that developers clearly watermark videos that are edited through AI or otherwise, and denote clearly what part and element of the scene was modified.
To catch less ethical users, the US Department of Defense, through the Defense Advanced Research Projects Agency (DARPA), is supporting a program called Media Forensics. This latest DARPA challenge enlists researchers to develop technologies to automatically assess the integrity of an image or video, as part of an end-to-end media forensics platform.
The DARPA official in charge of the program, Matthew Turek, did tell MIT Technology Review that so far the program has “discovered subtle cues in current GAN-manipulated images and videos that allow us to detect the presence of alterations.” In one reported example, researchers have targeted eyes, which rarely blink in the case of “deepfakes” like those created by FakeApp, because the AI is trained on still pictures. That method would seem to be less effective to spot the sort of forgeries created by Deep Video Portraits, which appears to flawlessly match the entire facial and head movements between the source and target actors.
“We believe that the field of digital forensics should and will receive a lot more attention in the future to develop approaches that can automatically prove the authenticity of a video clip,” Zollhöfer said. “This will lead to ever-better approaches that can spot such modifications even if we humans might not be able to spot them with our own eyes.
Image Credit: Tancha / Shutterstock.com Continue reading
Posted in Human Robots
#433284 Tech Can Sustainably Feed Developing ...
In the next 30 years, virtually all net population growth will occur in urban regions of developing countries. At the same time, worldwide food production will become increasingly limited by the availability of land, water, and energy. These constraints will be further worsened by climate change and the expected addition of two billion people to today’s four billion now living in urban regions. Meanwhile, current urban food ecosystems in the developing world are inefficient and critically inadequate to meet the challenges of the future.
Combined, these trends could have catastrophic economic and political consequences. A new path forward for urban food ecosystems needs to be found. But what is that path?
New technologies, coupled with new business models and supportive government policies, can create more resilient urban food ecosystems in the coming decades. These tech-enabled systems can sustainably link rural, peri-urban (areas just outside cities), and urban producers and consumers, increase overall food production, and generate opportunities for new businesses and jobs (Figure 1).
Figure 1: The urban food value chain nodes from rural, peri-urban and urban producers
to servicing end customers in urban and peri-urban markets.
Here’s a glimpse of the changes technology may bring to the systems feeding cities in the future.
A technology-linked urban food ecosystem would create unprecedented opportunities for small farms to reach wider markets and progress from subsistence farming to commercially producing niche cash crops and animal protein, such as poultry, fish, pork, and insects.
Meanwhile, new opportunities within cities will appear with the creation of vertical farms and other controlled-environment agricultural systems as well as production of plant-based and 3D printed foods and cultured meat. Uberized facilitation of production and distribution of food will reduce bottlenecks and provide new business opportunities and jobs. Off-the-shelf precision agriculture technology will increasingly be the new norm, from smallholders to larger producers.
As part of Agricultural Revolution 4.0, all this will be integrated into the larger collaborative economy—connected by digital platforms, the cloud, and the Internet of Things and powered by artificial intelligence. It will more efficiently and effectively use resources and people to connect the nexus of food, water, energy, nutrition, and human health. It will also aid in the development of a circular economy that is designed to be restorative and regenerative, minimizing waste and maximizing recycling and reuse to build economic, natural, and social capital.
In short, technology will enable transformation of urban food ecosystems, from expanded production in cities to more efficient and inclusive distribution and closer connections with rural farmers. Here’s a closer look at seven tech-driven trends that will help feed tomorrow’s cities.
1. Worldwide Connectivity: Information, Learning, and Markets
Connectivity from simple cell phone SMS communication to internet-enabled smartphones and cloud services are providing platforms for the increasingly powerful technologies enabling development of a new agricultural revolution. Internet connections currently reach more than 4 billion people, about 55% of the global population. That number will grow fast in coming years.
These information and communications technologies connect food producers to consumers with just-in-time data, enhanced good agricultural practices, mobile money and credit, telecommunications, market information and merchandising, and greater transparency and traceability of goods and services throughout the value chain. Text messages on mobile devices have become the one-stop-shop for small farmers to place orders, gain technology information for best management practices, and access market information to increase profitability.
Hershey’s CocoaLink in Ghana, for example, uses text and voice messages with cocoa industry experts and small farm producers. Digital Green is a technology-enabled communication system in Asia and Africa to bring needed agricultural and management practices to small farmers in their own language by filming and recording successful farmers in their own communities. MFarm is a mobile app that connects Kenyan farmers with urban markets via text messaging.
2. Blockchain Technology: Greater Access to Basic Financial Services and Enhanced Food Safety
Gaining access to credit and executing financial transactions have been persistent constraints for small farm producers. Blockchain promises to help the unbanked access basic financial services.
The Gates Foundation has released an open source platform, Mojaloop, to allow software developers and banks and financial service providers to build secure digital payment platforms at scale. Mojaloop software uses more secure blockchain technology to enable urban food system players in the developing world to conduct business and trade. The free software reduces complexity and cost in building payment platforms to connect small farmers with customers, merchants, banks, and mobile money providers. Such digital financial services will allow small farm producers in the developing world to conduct business without a brick-and-mortar bank.
Blockchain is also important for traceability and transparency requirements to meet food regulatory and consumer requirement during the production, post-harvest, shipping, processing and distribution to consumers. Combining blockchain with RFID technologies also will enhance food safety.
3. Uberized Services: On-Demand Equipment, Storage, and More
Uberized services can advance development of the urban food ecosystem across the spectrum, from rural to peri-urban to urban food production and distribution. Whereas Uber and Airbnb enable sharing of rides and homes, the model can be extended in the developing world to include on-demand use of expensive equipment, such as farm machinery, or storage space.
This includes uberization of planting and harvesting equipment (Hello Tractor), transportation vehicles, refrigeration facilities for temporary storage of perishable product, and “cloud kitchens” (EasyAppetite in Nigeria, FoodCourt in Rwanda, and Swiggy and Zomto in India) that produce fresh meals to be delivered to urban customers, enabling young people with motorbikes and cell phones to become entrepreneurs or contractors delivering meals to urban customers.
Another uberized service is marketing and distributing “ugly food” or imperfect produce to reduce food waste. About a third of the world’s food goes to waste, often because of appearance; this is enough to feed two billion people. Such services supply consumers with cheaper, nutritious, tasty, healthy fruits and vegetables that would normally be discarded as culls due to imperfections in shape or size.
4. Technology for Producing Plant-Based Foods in Cities
We need to change diet choices through education and marketing and by developing tasty plant-based substitutes. This is not only critical for environmental sustainability, but also offers opportunities for new businesses and services. It turns out that current agricultural production systems for “red meat” have a far greater detrimental impact on the environment than automobiles.
There have been great advances in plant-based foods, like the Impossible Burger and Beyond Meat, that can satisfy the consumer’s experience and perception of meat. Rather than giving up the experience of eating red meat, technology is enabling marketable, attractive plant-based products that can potentially drastically reduce world per capita consumption of red meat.
5. Cellular Agriculture, Lab-Grown Meat, and 3D Printed Food
Lab-grown meat, literally meat grown from cultured cells, may radically change where and how protein and food is produced, including the cities where it is consumed. There is a wide range of innovative alternatives to traditional meats that can supplement the need for livestock, farms, and butchers. The history of innovation is about getting rid of the bottleneck in the system, and with meat, the bottleneck is the animal. Finless Foods is a new company trying to replicate fish fillets, for example, while Memphis meats is working on beef and poultry.
3D printing or additive manufacturing is a “general purpose technology” used for making, plastic toys, human tissues, aircraft parts, and buildings. 3D printing can also be used to convert alternative ingredients such as proteins from algae, beet leaves, or insects into tasty and healthy products that can be produced by small, inexpensive printers in home kitchens. The food can be customized for individual health needs as well as preferences. 3D printing can also contribute to the food ecosystem by making possible on-demand replacement parts—which are badly needed in the developing world for tractors, pumps, and other equipment. Catapult Design 3D prints tractor replacement parts as well as corn shellers, cart designs, prosthetic limbs, and rolling water barrels for the Indian market.
6. Alt Farming: Vertical Farms to Produce Food in Urban Centers
Urban food ecosystem production systems will rely not only on field-grown crops, but also on production of food within cities. There are a host of new, alternative production systems using “controlled environmental agriculture.” These include low-cost, protected poly hoop houses, greenhouses, roof-top and sack/container gardens, and vertical farming in buildings using artificial lighting. Vertical farms enable year-round production of selected crops, regardless of weather—which will be increasingly important in response to climate change—and without concern for deteriorating soil conditions that affect crop quality and productivity. AeroFarms claims 390 times more productivity per square foot than normal field production.
7. Biotechnology and Nanotechnology for Sustainable Intensification of Agriculture
CRISPR is a promising gene editing technology that can be used to enhance crop productivity while avoiding societal concerns about GMOs. CRISPR can accelerate traditional breeding and selection programs for developing new climate and disease-resistant, higher-yielding, nutritious crops and animals.
Plant-derived coating materials, developed with nanotechnology, can decrease waste, extend shelf-life and transportability of fruits and vegetables, and significantly reduce post-harvest crop loss in developing countries that lack adequate refrigeration. Nanotechnology is also used in polymers to coat seeds to increase their shelf-life and increase their germination success and production for niche, high-value crops.
Putting It All Together
The next generation “urban food industry” will be part of the larger collaborative economy that is connected by digital platforms, the cloud, and the Internet of Things. A tech-enabled urban food ecosystem integrated with new business models and smart agricultural policies offers the opportunity for sustainable intensification (doing more with less) of agriculture to feed a rapidly growing global urban population—while also creating viable economic opportunities for rural and peri-urban as well as urban producers and value-chain players.
Image Credit: Akarawut / Shutterstock.com Continue reading
Posted in Human Robots
#432893 These 4 Tech Trends Are Driving Us ...
From a first-principles perspective, the task of feeding eight billion people boils down to converting energy from the sun into chemical energy in our bodies.
Traditionally, solar energy is converted by photosynthesis into carbohydrates in plants (i.e., biomass), which are either eaten by the vegans amongst us, or fed to animals, for those with a carnivorous preference.
Today, the process of feeding humanity is extremely inefficient.
If we could radically reinvent what we eat, and how we create that food, what might you imagine that “future of food” would look like?
In this post we’ll cover:
Vertical farms
CRISPR engineered foods
The alt-protein revolution
Farmer 3.0
Let’s dive in.
Vertical Farming
Where we grow our food…
The average American meal travels over 1,500 miles from farm to table. Wine from France, beef from Texas, potatoes from Idaho.
Imagine instead growing all of your food in a 50-story tall vertical farm in downtown LA or off-shore on the Great Lakes where the travel distance is no longer 1,500 miles but 50 miles.
Delocalized farming will minimize travel costs at the same time that it maximizes freshness.
Perhaps more importantly, vertical farming also allows tomorrow’s farmer the ability to control the exact conditions of her plants year round.
Rather than allowing the vagaries of the weather and soil conditions to dictate crop quality and yield, we can now perfectly control the growing cycle.
LED lighting provides the crops with the maximum amount of light, at the perfect frequency, 24 hours a day, 7 days a week.
At the same time, sensors and robots provide the root system the exact pH and micronutrients required, while fine-tuning the temperature of the farm.
Such precision farming can generate yields that are 200% to 400% above normal.
Next let’s explore how we can precision-engineer the genetic properties of the plant itself.
CRISPR and Genetically Engineered Foods
What food do we grow?
A fundamental shift is occurring in our relationship with agriculture. We are going from evolution by natural selection (Darwinism) to evolution by human direction.
CRISPR (the cutting edge gene editing tool) is providing a pathway for plant breeding that is more predictable, faster and less expensive than traditional breeding methods.
Rather than our crops being subject to nature’s random, environmental whim, CRISPR unlocks our capability to modify our crops to match the available environment.
Further, using CRISPR we will be able to optimize the nutrient density of our crops, enhancing their value and volume.
CRISPR may also hold the key to eliminating common allergens from crops. As we identify the allergen gene in peanuts, for instance, we can use CRISPR to silence that gene, making the crops we raise safer for and more accessible to a rapidly growing population.
Yet another application is our ability to make plants resistant to infection or more resistant to drought or cold.
Helping to accelerate the impact of CRISPR, the USDA recently announced that genetically engineered crops will not be regulated—providing an opening for entrepreneurs to capitalize on the opportunities for optimization CRISPR enables.
CRISPR applications in agriculture are an opportunity to help a billion people and become a billionaire in the process.
Protecting crops against volatile environments, combating crop diseases and increasing nutrient values, CRISPR is a promising tool to help feed the world’s rising population.
The Alt-Protein/Lab-Grown Meat Revolution
Something like a third of the Earth’s arable land is used for raising livestock—a massive amount of land—and global demand for meat is predicted to double in the coming decade.
Today, we must grow an entire cow—all bones, skin, and internals included—to produce a steak.
Imagine if we could instead start with a single muscle stem cell and only grow the steak, without needing the rest of the cow? Think of it as cellular agriculture.
Imagine returning millions, perhaps billions, of acres of grazing land back to the wilderness? This is the promise of lab-grown meats.
Lab-grown meat can also be engineered (using technology like CRISPR) to be packed with nutrients and be the healthiest, most delicious protein possible.
We’re watching this technology develop in real time. Several startups across the globe are already working to bring artificial meats to the food industry.
JUST, Inc. (previously Hampton Creek) run by my friend Josh Tetrick, has been on a mission to build a food system where everyone can get and afford delicious, nutritious food. They started by exploring 300,000+ species of plants all around the world to see how they can make food better and now are investing heavily in stem-cell-grown meats.
Backed by Richard Branson and Bill Gates, Memphis Meats is working on ways to produce real meat from animal cells, rather than whole animals. So far, they have produced beef, chicken, and duck using cultured cells from living animals.
As with vertical farming, transitioning production of our majority protein source to a carefully cultivated environment allows for agriculture to optimize inputs (water, soil, energy, land footprint), nutrients and, importantly, taste.
Farmer 3.0
Vertical farming and cellular agriculture are reinventing how we think about our food supply chain and what food we produce.
The next question to answer is who will be producing the food?
Let’s look back at how farming evolved through history.
Farmers 0.0 (Neolithic Revolution, around 9000 BCE): The hunter-gatherer to agriculture transition gains momentum, and humans cultivated the ability to domesticate plants for food production.
Farmers 1.0 (until around the 19th century): Farmers spent all day in the field performing backbreaking labor, and agriculture accounted for most jobs.
Farmers 2.0 (mid-20th century, Green Revolution): From the invention of the first farm tractor in 1812 through today, transformative mechanical biochemical technologies (fertilizer) boosted yields and made the job of farming easier, driving the US farm job rate down to less than two percent today.
Farmers 3.0: In the near future, farmers will leverage exponential technologies (e.g., AI, networks, sensors, robotics, drones), CRISPR and genetic engineering, and new business models to solve the world’s greatest food challenges and efficiently feed the eight-billion-plus people on Earth.
An important driver of the Farmer 3.0 evolution is the delocalization of agriculture driven by vertical and urban farms. Vertical farms and urban agriculture are empowering a new breed of agriculture entrepreneurs.
Let’s take a look at an innovative incubator in Brooklyn, New York called Square Roots.
Ten farm-in-a-shipping-containers in a Brooklyn parking lot represent the first Square Roots campus. Each 8-foot x 8.5-foot x 20-foot shipping container contains an equivalent of 2 acres of produce and can yield more than 50 pounds of produce each week.
For 13 months, one cohort of next-generation food entrepreneurs takes part in a curriculum with foundations in farming, business, community and leadership.
The urban farming incubator raised a $5.4 million seed funding round in August 2017.
Training a new breed of entrepreneurs to apply exponential technology to growing food is essential to the future of farming.
One of our massive transformative purposes at the Abundance Group is to empower entrepreneurs to generate extraordinary wealth while creating a world of abundance. Vertical farms and cellular agriculture are key elements enabling the next generation of food and agriculture entrepreneurs.
Conclusion
Technology is driving food abundance.
We’re already seeing food become demonetized, as the graph below shows.
From 1960 to 2014, the percent of income spent on food in the U.S. fell from 19 percent to under 10 percent of total disposable income—a dramatic decrease over the 40 percent of household income spent on food in 1900.
The dropping percent of per-capita disposable income spent on food. Source: USDA, Economic Research Service, Food Expenditure Series
Ultimately, technology has enabled a massive variety of food at a significantly reduced cost and with fewer resources used for production.
We’re increasingly going to optimize and fortify the food supply chain to achieve more reliable, predictable, and nutritious ways to obtain basic sustenance.
And that means a world with abundant, nutritious, and inexpensive food for every man, woman, and child.
What an extraordinary time to be alive.
Join Me
Abundance-Digital Online Community: I’ve created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital.
Abundance-Digital is my ‘onramp’ for exponential entrepreneurs—those who want to get involved and play at a higher level. Click here to learn more.
Image Credit: Nejron Photo / Shutterstock.com Continue reading
Posted in Human Robots
#432880 Google’s Duplex Raises the Question: ...
By now, you’ve probably seen Google’s new Duplex software, which promises to call people on your behalf to book appointments for haircuts and the like. As yet, it only exists in demo form, but already it seems like Google has made a big stride towards capturing a market that plenty of companies have had their eye on for quite some time. This software is impressive, but it raises questions.
Many of you will be familiar with the stilted, robotic conversations you can have with early chatbots that are, essentially, glorified menus. Instead of pressing 1 to confirm or 2 to re-enter, some of these bots would allow for simple commands like “Yes” or “No,” replacing the buttons with limited ability to recognize a few words. Using them was often a far more frustrating experience than attempting to use a menu—there are few things more irritating than a robot saying, “Sorry, your response was not recognized.”
Google Duplex scheduling a hair salon appointment:
Google Duplex calling a restaurant:
Even getting the response recognized is hard enough. After all, there are countless different nuances and accents to baffle voice recognition software, and endless turns of phrase that amount to saying the same thing that can confound natural language processing (NLP), especially if you like your phrasing quirky.
You may think that standard customer-service type conversations all travel the same route, using similar words and phrasing. But when there are over 80,000 ways to order coffee, and making a mistake is frowned upon, even simple tasks require high accuracy over a huge dataset.
Advances in audio processing, neural networks, and NLP, as well as raw computing power, have meant that basic recognition of what someone is trying to say is less of an issue. Soundhound’s virtual assistant prides itself on being able to process complicated requests (perhaps needlessly complicated).
The deeper issue, as with all attempts to develop conversational machines, is one of understanding context. There are so many ways a conversation can go that attempting to construct a conversation two or three layers deep quickly runs into problems. Multiply the thousands of things people might say by the thousands they might say next, and the combinatorics of the challenge runs away from most chatbots, leaving them as either glorified menus, gimmicks, or rather bizarre to talk to.
Yet Google, who surely remembers from Glass the risk of premature debuts for technology, especially the kind that ask you to rethink how you interact with or trust in software, must have faith in Duplex to show it on the world stage. We know that startups like Semantic Machines and x.ai have received serious funding to perform very similar functions, using natural-language conversations to perform computing tasks, schedule meetings, book hotels, or purchase items.
It’s no great leap to imagine Google will soon do the same, bringing us closer to a world of onboard computing, where Lens labels the world around us and their assistant arranges it for us (all the while gathering more and more data it can convert into personalized ads). The early demos showed some clever tricks for keeping the conversation within a fairly narrow realm where the AI should be comfortable and competent, and the blog post that accompanied the release shows just how much effort has gone into the technology.
Yet given the privacy and ethics funk the tech industry finds itself in, and people’s general unease about AI, the main reaction to Duplex’s impressive demo was concern. The voice sounded too natural, bringing to mind Lyrebird and their warnings of deepfakes. You might trust “Do the Right Thing” Google with this technology, but it could usher in an era when automated robo-callers are far more convincing.
A more human-like voice may sound like a perfectly innocuous improvement, but the fact that the assistant interjects naturalistic “umm” and “mm-hm” responses to more perfectly mimic a human rubbed a lot of people the wrong way. This wasn’t just a voice assistant trying to sound less grinding and robotic; it was actively trying to deceive people into thinking they were talking to a human.
Google is running the risk of trying to get to conversational AI by going straight through the uncanny valley.
“Google’s experiments do appear to have been designed to deceive,” said Dr. Thomas King of the Oxford Internet Institute’s Digital Ethics Lab, according to Techcrunch. “Their main hypothesis was ‘can you distinguish this from a real person?’ In this case it’s unclear why their hypothesis was about deception and not the user experience… there should be some kind of mechanism there to let people know what it is they are speaking to.”
From Google’s perspective, being able to say “90 percent of callers can’t tell the difference between this and a human personal assistant” is an excellent marketing ploy, even though statistics about how many interactions are successful might be more relevant.
In fact, Duplex runs contrary to pretty much every major recommendation about ethics for the use of robotics or artificial intelligence, not to mention certain eavesdropping laws. Transparency is key to holding machines (and the people who design them) accountable, especially when it comes to decision-making.
Then there are the more subtle social issues. One prominent effect social media has had is to allow people to silo themselves; in echo chambers of like-minded individuals, it’s hard to see how other opinions exist. Technology exacerbates this by removing the evolutionary cues that go along with face-to-face interaction. Confronted with a pair of human eyes, people are more generous. Confronted with a Twitter avatar or a Facebook interface, people hurl abuse and criticism they’d never dream of using in a public setting.
Now that we can use technology to interact with ever fewer people, will it change us? Is it fair to offload the burden of dealing with a robot onto the poor human at the other end of the line, who might have to deal with dozens of such calls a day? Google has said that if the AI is in trouble, it will put you through to a human, which might help save receptionists from the hell of trying to explain a concept to dozens of dumbfounded AI assistants all day. But there’s always the risk that failures will be blamed on the person and not the machine.
As AI advances, could we end up treating the dwindling number of people in these “customer-facing” roles as the buggiest part of a fully automatic service? Will people start accusing each other of being robots on the phone, as well as on Twitter?
Google has provided plenty of reassurances about how the system will be used. They have said they will ensure that the system is identified, and it’s hardly difficult to resolve this problem; a slight change in the script from their demo would do it. For now, consumers will likely appreciate moves that make it clear whether the “intelligent agents” that make major decisions for us, that we interact with daily, and that hide behind social media avatars or phone numbers are real or artificial.
Image Credit: Besjunior / Shutterstock.com Continue reading
Posted in Human Robots