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Imagine trying to read War and Peace one letter at a time. The thought alone feels excruciating. But in many ways, this painful idea holds parallels to how human-machine interfaces (HMI) force us to interact with and process data today.
Designed back in the 1970s at Xerox PARC and later refined during the 1980s by Apple, today’s HMI was originally conceived during fundamentally different times, and specifically, before people and machines were generating so much data. Fast forward to 2019, when humans are estimated to produce 44 zettabytes of data—equal to two stacks of books from here to Pluto—and we are still using the same HMI from the 1970s.
These dated interfaces are not equipped to handle today’s exponential rise in data, which has been ushered in by the rapid dematerialization of many physical products into computers and software.
Breakthroughs in perceptual and cognitive computing, especially machine learning algorithms, are enabling technology to process vast volumes of data, and in doing so, they are dramatically amplifying our brain’s abilities. Yet even with these powerful technologies that at times make us feel superhuman, the interfaces are still crippled with poor ergonomics.
Many interfaces are still designed around the concept that human interaction with technology is secondary, not instantaneous. This means that any time someone uses technology, they are inevitably multitasking, because they must simultaneously perform a task and operate the technology.
If our aim, however, is to create technology that truly extends and amplifies our mental abilities so that we can offload important tasks, the technology that helps us must not also overwhelm us in the process. We must reimagine interfaces to work in coherence with how our minds function in the world so that our brains and these tools can work together seamlessly.
Most technology is designed to serve either the mind or the body. It is a problematic divide, because our brains use our entire body to process the world around us. Said differently, our minds and bodies do not operate distinctly. Our minds are embodied.
Studies using MRI scans have shown that when a person feels an emotion in their gut, blood actually moves to that area of the body. The body and the mind are linked in this way, sharing information back and forth continuously.
Current technology presents data to the brain differently from how the brain processes data. Our brains, for example, use sensory data to continually encode and decipher patterns within the neocortex. Our brains do not create a linguistic label for each item, which is how the majority of machine learning systems operate, nor do our brains have an image associated with each of these labels.
Our bodies move information through us instantaneously, in a sense “computing” at the speed of thought. What if our technology could do the same?
Using Cognitive Ergonomics to Design Better Interfaces
Well-designed physical tools, as philosopher Martin Heidegger once meditated on while using the metaphor of a hammer, seem to disappear into the “hand.” They are designed to amplify a human ability and not get in the way during the process.
The aim of physical ergonomics is to understand the mechanical movement of the human body and then adapt a physical system to amplify the human output in accordance. By understanding the movement of the body, physical ergonomics enables ergonomically sound physical affordances—or conditions—so that the mechanical movement of the body and the mechanical movement of the machine can work together harmoniously.
Cognitive ergonomics applied to HMI design uses this same idea of amplifying output, but rather than focusing on physical output, the focus is on mental output. By understanding the raw materials the brain uses to comprehend information and form an output, cognitive ergonomics allows technologists and designers to create technological affordances so that the brain can work seamlessly with interfaces and remove the interruption costs of our current devices. In doing so, the technology itself “disappears,” and a person’s interaction with technology becomes fluid and primary.
By leveraging cognitive ergonomics in HMI design, we can create a generation of interfaces that can process and present data the same way humans process real-world information, meaning through fully-sensory interfaces.
Several brain-machine interfaces are already on the path to achieving this. AlterEgo, a wearable device developed by MIT researchers, uses electrodes to detect and understand nonverbal prompts, which enables the device to read the user’s mind and act as an extension of the user’s cognition.
Another notable example is the BrainGate neural device, created by researchers at Stanford University. Just two months ago, a study was released showing that this brain implant system allowed paralyzed patients to navigate an Android tablet with their thoughts alone.
These are two extraordinary examples of what is possible for the future of HMI, but there is still a long way to go to bring cognitive ergonomics front and center in interface design.
Disruptive Innovation Happens When You Step Outside Your Existing Users
Most of today’s interfaces are designed by a narrow population, made up predominantly of white, non-disabled men who are prolific in the use of technology (you may recall The New York Times viral article from 2016, Artificial Intelligence’s White Guy Problem). If you ask this population if there is a problem with today’s HMIs, most will say no, and this is because the technology has been designed to serve them.
This lack of diversity means a limited perspective is being brought to interface design, which is problematic if we want HMI to evolve and work seamlessly with the brain. To use cognitive ergonomics in interface design, we must first gain a more holistic understanding of how people with different abilities understand the world and how they interact with technology.
Underserved groups, such as people with physical disabilities, operate on what Clayton Christensen coined in The Innovator’s Dilemma as the fringe segment of a market. Developing solutions that cater to fringe groups can in fact disrupt the larger market by opening a downward, much larger market.
Learning From Underserved Populations
When technology fails to serve a group of people, that group must adapt the technology to meet their needs.
The workarounds created are often ingenious, specifically because they have not been arrived at by preferences, but out of necessity that has forced disadvantaged users to approach the technology from a very different vantage point.
When a designer or technologist begins learning from this new viewpoint and understanding challenges through a different lens, they can bring new perspectives to design—perspectives that otherwise can go unseen.
Designers and technologists can also learn from people with physical disabilities who interact with the world by leveraging other senses that help them compensate for one they may lack. For example, some blind people use echolocation to detect objects in their environments.
The BrainPort device developed by Wicab is an incredible example of technology leveraging one human sense to serve or compliment another. The BrainPort device captures environmental information with a wearable video camera and converts this data into soft electrical stimulation sequences that are sent to a device on the user’s tongue—the most sensitive touch receptor in the body. The user learns how to interpret the patterns felt on their tongue, and in doing so, become able to “see” with their tongue.
Key to the future of HMI design is learning how different user groups navigate the world through senses beyond sight. To make cognitive ergonomics work, we must understand how to leverage the senses so we’re not always solely relying on our visual or verbal interactions.
Radical Inclusion for the Future of HMI
Bringing radical inclusion into HMI design is about gaining a broader lens on technology design at large, so that technology can serve everyone better.
Interestingly, cognitive ergonomics and radical inclusion go hand in hand. We can’t design our interfaces with cognitive ergonomics without bringing radical inclusion into the picture, and we also will not arrive at radical inclusion in technology so long as cognitive ergonomics are not considered.
This new mindset is the only way to usher in an era of technology design that amplifies the collective human ability to create a more inclusive future for all.
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Development across the entire information technology landscape certainly didn’t slow down this year. From CRISPR babies, to the rapid decline of the crypto markets, to a new robot on Mars, and discovery of subatomic particles that could change modern physics as we know it, there was no shortage of headline-grabbing breakthroughs and discoveries.
As 2018 comes to a close, we can pause and reflect on some of the biggest technology breakthroughs and scientific discoveries that occurred this year.
I reached out to a few Singularity University speakers and faculty across the various technology domains we cover asking what they thought the biggest breakthrough was in their area of expertise. The question posed was:
“What, in your opinion, was the biggest development in your area of focus this year? Or, what was the breakthrough you were most surprised by in 2018?”
I can share that for me, hands down, the most surprising development I came across in 2018 was learning that a publicly-traded company that was briefly valued at over $1 billion, and has over 12,000 employees and contractors spread around the world, has no physical office space and the entire business is run and operated from inside an online virtual world. This is Ready Player One stuff happening now.
For the rest, here’s what our experts had to say.
Dr. Tiffany Vora | Faculty Director and Vice Chair, Digital Biology and Medicine, Singularity University
“That’s easy: CRISPR babies. I knew it was technically possible, and I’ve spent two years predicting it would happen first in China. I knew it was just a matter of time but I failed to predict the lack of oversight, the dubious consent process, the paucity of publicly-available data, and the targeting of a disease that we already know how to prevent and treat and that the children were at low risk of anyway.
I’m not convinced that this counts as a technical breakthrough, since one of the girls probably isn’t immune to HIV, but it sure was a surprise.”
For more, read Dr. Vora’s summary of this recent stunning news from China regarding CRISPR-editing human embryos.
Andrew Fursman | Co-Founder/CEO 1Qbit, Faculty, Quantum Computing, Singularity University
“There were two last-minute holiday season surprise quantum computing funding and technology breakthroughs:
First, right before the government shutdown, one priority legislative accomplishment will provide $1.2 billion in quantum computing research over the next five years. Second, there’s the rise of ions as a truly viable, scalable quantum computing architecture.”
*Read this Gizmodo profile on an exciting startup in the space to learn more about this type of quantum computing
Ramez Naam | Chair, Energy and Environmental Systems, Singularity University
“2018 had plenty of energy surprises. In solar, we saw unsubsidized prices in the sunny parts of the world at just over two cents per kwh, or less than half the price of new coal or gas electricity. In the US southwest and Texas, new solar is also now cheaper than new coal or gas. But even more shockingly, in Germany, which is one of the least sunny countries on earth (it gets less sunlight than Canada) the average bid for new solar in a 2018 auction was less than 5 US cents per kwh. That’s as cheap as new natural gas in the US, and far cheaper than coal, gas, or any other new electricity source in most of Europe.
In fact, it’s now cheaper in some parts of the world to build new solar or wind than to run existing coal plants. Think tank Carbon Tracker calculates that, over the next 10 years, it will become cheaper to build new wind or solar than to operate coal power in most of the world, including specifically the US, most of Europe, and—most importantly—India and the world’s dominant burner of coal, China.
Here comes the sun.”
GLOBAL GRAND CHALLENGES
Darlene Damm | Vice Chair, Faculty, Global Grand Challenges, Singularity University
“In 2018 we saw a lot of areas in the Global Grand Challenges move forward—advancements in robotic farming technology and cultured meat, low-cost 3D printed housing, more sophisticated types of online education expanding to every corner of the world, and governments creating new policies to deal with the ethics of the digital world. These were the areas we were watching and had predicted there would be change.
What most surprised me was to see young people, especially teenagers, start to harness technology in powerful ways and use it as a platform to make their voices heard and drive meaningful change in the world. In 2018 we saw teenagers speak out on a number of issues related to their well-being and launch digital movements around issues such as gun and school safety, global warming and environmental issues. We often talk about the harm technology can cause to young people, but on the flip side, it can be a very powerful tool for youth to start changing the world today and something I hope we see more of in the future.”
Pascal Finette | Chair, Entrepreneurship and Open Innovation, Singularity University
“Without a doubt the rapid and massive adoption of AI, specifically deep learning, across industries, sectors, and organizations. What was a curiosity for most companies at the beginning of the year has quickly made its way into the boardroom and leadership meetings, and all the way down into the innovation and IT department’s agenda. You are hard-pressed to find a mid- to large-sized company today that is not experimenting or implementing AI in various aspects of its business.
On the slightly snarkier side of answering this question: The very rapid decline in interest in blockchain (and cryptocurrencies). The blockchain party was short, ferocious, and ended earlier than most would have anticipated, with a huge hangover for some. The good news—with the hot air dissipated, we can now focus on exploring the unique use cases where blockchain does indeed offer real advantages over centralized approaches.”
*Author note: snark is welcome and appreciated
Hod Lipson | Director, Creative Machines Lab, Columbia University
“The biggest surprise for me this year in robotics was learning dexterity. For decades, roboticists have been trying to understand and imitate dexterous manipulation. We humans seem to be able to manipulate objects with our fingers with incredible ease—imagine sifting through a bunch of keys in the dark, or tossing and catching a cube. And while there has been much progress in machine perception, dexterous manipulation remained elusive.
There seemed to be something almost magical in how we humans can physically manipulate the physical world around us. Decades of research in grasping and manipulation, and millions of dollars spent on robot-hand hardware development, has brought us little progress. But in late 2018, the Berkley OpenAI group demonstrated that this hurdle may finally succumb to machine learning as well. Given 200 years worth of practice, machines learned to manipulate a physical object with amazing fluidity. This might be the beginning of a new age for dexterous robotics.”
Jeremy Howard | Founding Researcher, fast.ai, Founder/CEO, Enlitic, Faculty Data Science, Singularity University
“The biggest development in machine learning this year has been the development of effective natural language processing (NLP).
The New York Times published an article last month titled “Finally, a Machine That Can Finish Your Sentence,” which argued that NLP neural networks have reached a significant milestone in capability and speed of development. The “finishing your sentence” capability mentioned in the title refers to a type of neural network called a “language model,” which is literally a model that learns how to finish your sentences.
Earlier this year, two systems (one, called ELMO, is from the Allen Institute for AI, and the other, called ULMFiT, was developed by me and Sebastian Ruder) showed that such a model could be fine-tuned to dramatically improve the state-of-the-art in nearly every NLP task that researchers study. This work was further developed by OpenAI, which in turn was greatly scaled up by Google Brain, who created a system called BERT which reached human-level performance on some of NLP’s toughest challenges.
Over the next year, expect to see fine-tuned language models used for everything from understanding medical texts to building disruptive social media troll armies.”
Andre Wegner | Founder/CEO Authentise, Chair, Digital Manufacturing, Singularity University
“Most surprising to me was the extent and speed at which the industry finally opened up.
While previously, only few 3D printing suppliers had APIs and knew what to do with them, 2018 saw nearly every OEM (or original equipment manufacturer) enabling data access and, even more surprisingly, shying away from proprietary standards and adopting MTConnect, as stalwarts such as 3D Systems and Stratasys have been. This means that in two to three years, data access to machines will be easy, commonplace, and free. The value will be in what is being done with that data.
Another example of this openness are the seemingly endless announcements of integrated workflows: GE’s announcement with most major software players to enable integrated solutions, EOS’s announcement with Siemens, and many more. It’s clear that all actors in the additive ecosystem have taken a step forward in terms of openness. The result is a faster pace of innovation, particularly in the software and data domains that are crucial to enabling comprehensive digital workflow to drive agile and resilient manufacturing.
I’m more optimistic we’ll achieve that now than I was at the end of 2017.”
SCIENCE AND DISCOVERY
Paul Saffo | Chair, Future Studies, Singularity University, Distinguished Visiting Scholar, Stanford Media-X Research Network
“The most important development in technology this year isn’t a technology, but rather the astonishing science surprises made possible by recent technology innovations. My short list includes the discovery of the “neptmoon”, a Neptune-scale moon circling a Jupiter-scale planet 8,000 lightyears from us; the successful deployment of the Mars InSight Lander a month ago; and the tantalizing ANITA detection (what could be a new subatomic particle which would in turn blow the standard model wide open). The highest use of invention is to support science discovery, because those discoveries in turn lead us to the future innovations that will improve the state of the world—and fire up our imaginations.”
Pablos Holman | Inventor, Hacker, Faculty, Singularity University
“Just five or ten years ago, if you’d asked any of us technologists “What is harder for robots? Eyes, or fingers?” We’d have all said eyes. Robots have extraordinary eyes now, but even in a surgical robot, the fingers are numb and don’t feel anything. Stanford robotics researchers have invented fingertips that can feel, and this will be a kingpin that allows robots to go everywhere they haven’t been yet.”
Nathana Sharma | Blockchain, Policy, Law, and Ethics, Faculty, Singularity University
“2017 was the year of peak blockchain hype. 2018 has been a year of resetting expectations and technological development, even as the broader cryptocurrency markets have faced a winter. It’s now about seeing adoption and applications that people want and need to use rise. An incredible piece of news from December 2018 is that Facebook is developing a cryptocurrency for users to make payments through Whatsapp. That’s surprisingly fast mainstream adoption of this new technology, and indicates how powerful it is.”
Neil Jacobstein | Chair, Artificial Intelligence and Robotics, Singularity University
“I think one of the most visible improvements in AI was illustrated by the Boston Dynamics Parkour video. This was not due to an improvement in brushless motors, accelerometers, or gears. It was due to improvements in AI algorithms and training data. To be fair, the video released was cherry-picked from numerous attempts, many of which ended with a crash. However, the fact that it could be accomplished at all in 2018 was a real win for both AI and robotics.”
Divya Chander | Chair, Neuroscience, Singularity University
“2018 ushered in a new era of exponential trends in non-invasive brain modulation. Changing behavior or restoring function takes on a new meaning when invasive interfaces are no longer needed to manipulate neural circuitry. The end of 2018 saw two amazing announcements: the ability to grow neural organoids (mini-brains) in a dish from neural stem cells that started expressing electrical activity, mimicking the brain function of premature babies, and the first (known) application of CRISPR to genetically alter two fetuses grown through IVF. Although this was ostensibly to provide genetic resilience against HIV infections, imagine what would happen if we started tinkering with neural circuitry and intelligence.”
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2018 was a big year for science and technology. The first gene-edited babies were born, as were the first cloned monkeys. SpaceX successfully launched the Falcon Heavy, and NASA’s InSight lander placed a seismometer on Mars. Bitcoin’s value plummeted, as did the cost of renewable energy. The world’s biggest neuromorphic supercomputer was switched on, and quantum communication made significant progress.
As 2018 draws to a close and we start anticipating the developments that will happen in 2019, here’s a look back at our ten most-read articles of the year.
This 3D Printed House Goes Up in a Day for Under $10,000
Vanessa Bates Ramirez | 3/18/18
“ICON and New Story’s vision is one of 3D printed houses acting as a safe, affordable housing alternative for people in need. New Story has already built over 800 homes in Haiti, El Salvador, Bolivia, and Mexico, partnering with the communities they serve to hire local labor and purchase local materials rather than shipping everything in from abroad.”
Machines Teaching Each Other Could Be the Biggest Exponential Trend in AI
Aaron Frank | 1/21/18
“Data is the fuel of machine learning, but even for machines, some data is hard to get—it may be risky, slow, rare, or expensive. In those cases, machines can share experiences or create synthetic experiences for each other to augment or replace data. It turns out that this is not a minor effect, it actually is self-amplifying, and therefore exponential.”
Low-Cost Soft Robot Muscles Can Lift 200 Times Their Weight and Self-Heal
Edd Gent | 1/11/18
“Now researchers at the University of Colorado Boulder have built a series of low-cost artificial muscles—as little as 10 cents per device—using soft plastic pouches filled with electrically insulating liquids that contract with the force and speed of mammalian skeletal muscles when a voltage is applied to them.”
These Are the Most Exciting Industries and Jobs of the Future
Raya Bidshahri | 1/29/18
“Technological trends are giving rise to what many thought leaders refer to as the “imagination economy.” This is defined as “an economy where intuitive and creative thinking create economic value, after logical and rational thinking have been outsourced to other economies.” Unsurprisingly, humans continue to outdo machines when it comes to innovating and pushing intellectual, imaginative, and creative boundaries, making jobs involving these skills the hardest to automate.”
Inside a $1 Billion Real Estate Company Operating Entirely in VR
Aaron Frank | 4/8/18
“Incredibly, this growth is largely the result of eXp Realty’s use of an online virtual world similar to Second Life. That means every employee, contractor, and the thousands of agents who work at the company show up to work—team meetings, training seminars, onboarding sessions—all inside a virtual reality campus.To be clear, this is a traditional real estate brokerage helping people buy and sell physical homes—but they use a virtual world as their corporate offices.”
How Fast Is AI Progressing? Stanford’s New Report Card for Artificial Intelligence
Thomas Hornigold | 1/18/18
“Progress in AI over the next few years is far more likely to resemble a gradual rising tide—as more and more tasks can be turned into algorithms and accomplished by software—rather than the tsunami of a sudden intelligence explosion or general intelligence breakthrough. Perhaps measuring the ability of an AI system to learn and adapt to the work routines of humans in office-based tasks could be possible.”
When Will We Finally Achieve True Artificial Intelligence?
Thomas Hornigold | 1/1/18
“The issue with trying to predict the exact date of human-level AI is that we don’t know how far is left to go. This is unlike Moore’s Law. Moore’s Law, the doubling of processing power roughly every couple of years, makes a very concrete prediction about a very specific phenomenon. We understand roughly how to get there—improved engineering of silicon wafers—and we know we’re not at the fundamental limits of our current approach. You cannot say the same about artificial intelligence.”
IBM’s New Computer Is the Size of a Grain of Salt and Costs Less Than 10 Cents
Edd Gent | 3/26/18
“Costing less than 10 cents to manufacture, the company envisions the device being embedded into products as they move around the supply chain. The computer’s sensing, processing, and communicating capabilities mean it could effectively turn every item in the supply chain into an Internet of Things device, producing highly granular supply chain data that could streamline business operations.”
Why the Rise of Self-Driving Vehicles Will Actually Increase Car Ownership
Melba Kurman and Hod Lipson / 2/14/18
“When people predict the demise of car ownership, they are overlooking the reality that the new autonomous automotive industry is not going to be just a re-hash of today’s car industry with driverless vehicles. Instead, the automotive industry of the future will be selling what could be considered an entirely new product: a wide variety of intelligent, self-guiding transportation robots. When cars become a widely used type of transportation robot, they will be cheap, ubiquitous, and versatile.”
A Model for the Future of Education
Peter Diamandis | 9/12/18
“I imagine a relatively near-term future in which robotics and artificial intelligence will allow any of us, from ages 8 to 108, to easily and quickly find answers, create products, or accomplish tasks, all simply by expressing our desires. From ‘mind to manufactured in moments.’ In short, we’ll be able to do and create almost whatever we want. In this future, what attributes will be most critical for our children to learn to become successful in their adult lives? What’s most important for educating our children today?”
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A research team at the University of Washington has trained an artificial intelligence system to spot obesity—all the way from space. The system used a convolutional neural network (CNN) to analyze 150,000 satellite images and look for correlations between the physical makeup of a neighborhood and the prevalence of obesity.
The team’s results, presented in JAMA Network Open, showed that features of a given neighborhood could explain close to two-thirds (64.8 percent) of the variance in obesity. Researchers found that analyzing satellite data could help increase understanding of the link between peoples’ environment and obesity prevalence. The next step would be to make corresponding structural changes in the way neighborhoods are built to encourage physical activity and better health.
Training AI to Spot Obesity
Convolutional neural networks (CNNs) are particularly adept at image analysis, object recognition, and identifying special hierarchies in large datasets.
Prior to analyzing 150,000 high-resolution satellite images of Bellevue, Seattle, Tacoma, Los Angeles, Memphis, and San Antonio, the researchers trained the CNN on 1.2 million images from the ImageNet database. The categorizations were correlated with obesity prevalence estimates for the six urban areas from census tracts gathered by the 500 Cities project.
The system was able to identify the presence of certain features that increased likelihood of obesity in a given area. Some of these features included tightly–packed houses, being close to roadways, and living in neighborhoods with a lack of greenery.
Visualization of features identified by the convolutional neural network (CNN) model. The images on the left column are satellite images taken from Google Static Maps API (application programming interface). Images in the middle and right columns are activation maps taken from the second convolutional layer of VGG-CNN-F network after forward pass of the respective satellite images through the network. From Google Static Maps API, DigitalGlobe, US Geological Survey (accessed July 2017). Credit: JAMA Network Open
Your Surroundings Are Key
In their discussion of the findings, the researchers stressed that there are limitations to the conclusions that can be drawn from the AI’s results. For example, socio-economic factors like income likely play a major role for obesity prevalence in a given geographic area.
However, the study concluded that the AI-powered analysis showed the prevalence of specific man-made features in neighborhoods consistently correlating with obesity prevalence and not necessarily correlating with socioeconomic status.
The system’s success rates varied between studied cities, with Memphis being the highest (73.3 percent) and Seattle being the lowest (55.8 percent).
AI Takes To the Sky
Around a third of the US population is categorized as obese. Obesity is linked to a number of health-related issues, and the AI-generated results could potentially help improve city planning and better target campaigns to limit obesity.
The study is one of the latest of a growing list that uses AI to analyze images and extrapolate insights.
A team at Stanford University has used a CNN to predict poverty via satellite imagery, assisting governments and NGOs to better target their efforts. A combination of the public Automatic Identification System for shipping, satellite imagery, and Google’s AI has proven able to identify illegal fishing activity. Researchers have even been able to use AI and Google Street View to predict what party a given city will vote for, based on what cars are parked on the streets.
In each case, the AI systems have been able to look at volumes of data about our world and surroundings that are beyond the capabilities of humans and extrapolate new insights. If one were to moralize about the good and bad sides of AI (new opportunities vs. potential job losses, for example) it could seem that it comes down to what we ask AI systems to look at—and what questions we ask of them.
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As kids worldwide head back to school, I’d like to share my thoughts on the future of education.
Bottom line, how we educate our kids needs to radically change given the massive potential of exponential tech (e.g. artificial intelligence and virtual reality).
Without question, the number one driver for education is inspiration. As such, if you have a kid age 8–18, you’ll want to get your hands on an incredibly inspirational novel written by my dear friend Ray Kurzweil called Danielle: Chronicles of a Superheroine.
Danielle offers boys and girls a role model of a young woman who uses smart technologies and super-intelligence to partner with her friends to solve some of the world’s greatest challenges. It’s perfect to inspire anyone to pursue their moonshot.
Without further ado, let’s dive into the future of educating kids, and a summary of my white paper thoughts….
Just last year, edtech (education technology) investments surpassed a record high of 9.5 billion USD—up 30 percent from the year before.
Already valued at over half a billion USD, the AI in education market is set to surpass 6 billion USD by 2024.
And we’re now seeing countless new players enter the classroom, from a Soul Machines AI teacher specializing in energy use and sustainability to smart “lab schools” with personalized curricula.
As my two boys enter 1st grade, I continue asking myself, given the fact that most elementary schools haven’t changed in many decades (perhaps a century), what do I want my kids to learn? How do I think about elementary school during an exponential era?
This post covers five subjects related to elementary school education:
Five Issues with Today’s Elementary Schools
Five Guiding Principles for Future Education
An Elementary School Curriculum for the Future
Exponential Technologies in our Classroom
Mindsets for the 21st Century
Excuse the length of this post, but if you have kids, the details might be meaningful. If you don’t, then next week’s post will return to normal length and another fun subject.
Also, if you’d like to see my detailed education “white paper,” you can view or download it here.
Let’s dive in…
Five Issues With Today’s Elementary Schools
There are probably lots of issues with today’s traditional elementary schools, but I’ll just choose a few that bother me most.
Grading: In the traditional education system, you start at an “A,” and every time you get something wrong, your score gets lower and lower. At best it’s demotivating, and at worst it has nothing to do with the world you occupy as an adult. In the gaming world (e.g. Angry Birds), it’s just the opposite. You start with zero and every time you come up with something right, your score gets higher and higher.
Sage on the Stage: Most classrooms have a teacher up in front of class lecturing to a classroom of students, half of whom are bored and half of whom are lost. The one-teacher-fits-all model comes from an era of scarcity where great teachers and schools were rare.
Relevance: When I think back to elementary and secondary school, I realize how much of what I learned was never actually useful later in life, and how many of my critical lessons for success I had to pick up on my own (I don’t know about you, but I haven’t ever actually had to factor a polynomial in my adult life).
Imagination, Coloring inside the Lines: Probably of greatest concern to me is the factory-worker, industrial-era origin of today’s schools. Programs are so structured with rote memorization that it squashes the originality from most children. I’m reminded that “the day before something is truly a breakthrough, it’s a crazy idea.” Where do we pursue crazy ideas in our schools? Where do we foster imagination?
Boring: If learning in school is a chore, boring, or emotionless, then the most important driver of human learning, passion, is disengaged. Having our children memorize facts and figures, sit passively in class, and take mundane standardized tests completely defeats the purpose.
An average of 7,200 students drop out of high school each day, totaling 1.3 million each year. This means only 69 percent of students who start high school finish four years later. And over 50 percent of these high school dropouts name boredom as the number one reason they left.
Five Guiding Principles for Future Education
I imagine a relatively near-term future in which robotics and artificial intelligence will allow any of us, from ages 8 to 108, to easily and quickly find answers, create products, or accomplish tasks, all simply by expressing our desires.
From ‘mind to manufactured in moments.’ In short, we’ll be able to do and create almost whatever we want.
In this future, what attributes will be most critical for our children to learn to become successful in their adult lives? What’s most important for educating our children today?
For me it’s about passion, curiosity, imagination, critical thinking, and grit.
Passion: You’d be amazed at how many people don’t have a mission in life… A calling… something to jolt them out of bed every morning. The most valuable resource for humanity is the persistent and passionate human mind, so creating a future of passionate kids is so very important. For my 7-year-old boys, I want to support them in finding their passion or purpose… something that is uniquely theirs. In the same way that the Apollo program and Star Trek drove my early love for all things space, and that passion drove me to learn and do.
Curiosity: Curiosity is something innate in kids, yet something lost by most adults during the course of their life. Why? In a world of Google, robots, and AI, raising a kid that is constantly asking questions and running “what if” experiments can be extremely valuable. In an age of machine learning, massive data, and a trillion sensors, it will be the quality of your questions that will be most important.
Imagination: Entrepreneurs and visionaries imagine the world (and the future) they want to live in, and then they create it. Kids happen to be some of the most imaginative humans around… it’s critical that they know how important and liberating imagination can be.
Critical Thinking: In a world flooded with often-conflicting ideas, baseless claims, misleading headlines, negative news, and misinformation, learning the skill of critical thinking helps find the signal in the noise. This principle is perhaps the most difficult to teach kids.
Grit/Persistence: Grit is defined as “passion and perseverance in pursuit of long-term goals,” and it has recently been widely acknowledged as one of the most important predictors of and contributors to success.
Teaching your kids not to give up, to keep trying, and to keep trying new ideas for something that they are truly passionate about achieving is extremely critical. Much of my personal success has come from such stubbornness. I joke that both XPRIZE and the Zero Gravity Corporation were “overnight successes after 10 years of hard work.”
So given those five basic principles, what would an elementary school curriculum look like? Let’s take a look…
An Elementary School Curriculum for the Future
Over the last 30 years, I’ve had the pleasure of starting two universities, International Space University (1987) and Singularity University (2007). My favorite part of co-founding both institutions was designing and implementing the curriculum. Along those lines, the following is my first shot at the type of curriculum I’d love my own boys to be learning.
I’d love your thoughts, I’ll be looking for them here: https://www.surveymonkey.com/r/DDRWZ8R
For the purpose of illustration, I’ll speak about ‘courses’ or ‘modules,’ but in reality these are just elements that would ultimately be woven together throughout the course of K-6 education.
Module 1: Storytelling/Communications
When I think about the skill that has served me best in life, it’s been my ability to present my ideas in the most compelling fashion possible, to get others onboard, and support birth and growth in an innovative direction. In my adult life, as an entrepreneur and a CEO, it’s been my ability to communicate clearly and tell compelling stories that has allowed me to create the future. I don’t think this lesson can start too early in life. So imagine a module, year after year, where our kids learn the art and practice of formulating and pitching their ideas. The best of oration and storytelling. Perhaps children in this class would watch TED presentations, or maybe they’d put together their own TEDx for kids. Ultimately, it’s about practice and getting comfortable with putting yourself and your ideas out there and overcoming any fears of public speaking.
Module 2: Passions
A modern school should help our children find and explore their passion(s). Passion is the greatest gift of self-discovery. It is a source of interest and excitement, and is unique to each child.
The key to finding passion is exposure. Allowing kids to experience as many adventures, careers, and passionate adults as possible. Historically, this was limited by the reality of geography and cost, implemented by having local moms and dads presenting in class about their careers. “Hi, I’m Alan, Billy’s dad, and I’m an accountant. Accountants are people who…”
But in a world of YouTube and virtual reality, the ability for our children to explore 500 different possible careers or passions during their K-6 education becomes not only possible but compelling. I imagine a module where children share their newest passion each month, sharing videos (or VR experiences) and explaining what they love and what they’ve learned.
Module 3: Curiosity & Experimentation
Einstein famously said, “I have no special talent. I am only passionately curious.” Curiosity is innate in children, and many times lost later in life. Arguably, it can be said that curiosity is responsible for all major scientific and technological advances; it’s the desire of an individual to know the truth.
Coupled with curiosity is the process of experimentation and discovery. The process of asking questions, creating and testing a hypothesis, and repeated experimentation until the truth is found. As I’ve studied the most successful entrepreneurs and entrepreneurial companies, from Google and Amazon to Uber, their success is significantly due to their relentless use of experimentation to define their products and services.
Here I imagine a module which instills in children the importance of curiosity and gives them permission to say, “I don’t know, let’s find out.”
Further, a monthly module that teaches children how to design and execute valid and meaningful experiments. Imagine children who learn the skill of asking a question, proposing a hypothesis, designing an experiment, gathering the data, and then reaching a conclusion.
Module 4: Persistence/Grit
Doing anything big, bold, and significant in life is hard work. You can’t just give up when the going gets rough. The mindset of persistence, of grit, is a learned behavior I believe can be taught at an early age, especially when it’s tied to pursuing a child’s passion.
I imagine a curriculum that, each week, studies the career of a great entrepreneur and highlights their story of persistence. It would highlight the individuals and companies that stuck with it, iterated, and ultimately succeeded.
Further, I imagine a module that combines persistence and experimentation in gameplay, such as that found in Dean Kamen’s FIRST LEGO league, where 4th graders (and up) research a real-world problem such as food safety, recycling, energy, and so on, and are challenged to develop a solution. They also must design, build, and program a robot using LEGO MINDSTORMS®, then compete on a tabletop playing field.
Module 5: Technology Exposure
In a world of rapidly accelerating technology, understanding how technologies work, what they do, and their potential for benefiting society is, in my humble opinion, critical to a child’s future. Technology and coding (more on this below) are the new “lingua franca” of tomorrow.
In this module, I imagine teaching (age appropriate) kids through play and demonstration. Giving them an overview of exponential technologies such as computation, sensors, networks, artificial intelligence, digital manufacturing, genetic engineering, augmented/virtual reality, and robotics, to name a few. This module is not about making a child an expert in any technology, it’s more about giving them the language of these new tools, and conceptually an overview of how they might use such a technology in the future. The goal here is to get them excited, give them demonstrations that make the concepts stick, and then to let their imaginations run.
Module 6: Empathy
Empathy, defined as “the ability to understand and share the feelings of another,” has been recognized as one of the most critical skills for our children today. And while there has been much written, and great practices for instilling this at home and in school, today’s new tools accelerate this.
Virtual reality isn’t just about video games anymore. Artists, activists, and journalists now see the technology’s potential to be an empathy engine, one that can shine spotlights on everything from the Ebola epidemic to what it’s like to live in Gaza. And Jeremy Bailenson has been at the vanguard of investigating VR’s power for good.
For more than a decade, Bailenson’s lab at Stanford has been studying how VR can make us better people. Through the power of VR, volunteers at the lab have felt what it is like to be Superman (to see if it makes them more helpful), a cow (to reduce meat consumption), and even a coral (to learn about ocean acidification).
Silly as they might seem, these sorts of VR scenarios could be more effective than the traditional public service ad at making people behave. Afterwards, they waste less paper. They save more money for retirement. They’re nicer to the people around them. And this could have consequences in terms of how we teach and train everyone from cliquey teenagers to high court judges.
Module 7: Ethics/Moral Dilemmas
Related to empathy, and equally important, is the goal of infusing kids with a moral compass. Over a year ago, I toured a special school created by Elon Musk (the Ad Astra school) for his five boys (age 9 to 14). One element that is persistent in that small school of under 40 kids is the conversation about ethics and morals, a conversation manifested by debating real-world scenarios that our kids may one day face.
Here’s an example of the sort of gameplay/roleplay that I heard about at Ad Astra, that might be implemented in a module on morals and ethics. Imagine a small town on a lake, in which the majority of the town is employed by a single factory. But that factory has been polluting the lake and killing all the life. What do you do? It’s posed that shutting down the factory would mean that everyone loses their jobs. On the other hand, keeping the factory open means the lake is destroyed and the lake dies. This kind of regular and routine conversation/gameplay allows the children to see the world in a critically important fashion.
Module 8: The 3R Basics (Reading, wRiting & aRithmetic)
There’s no question that young children entering kindergarten need the basics of reading, writing, and math. The only question is what’s the best way for them to get it? We all grew up in the classic mode of a teacher at the chalkboard, books, and homework at night. But I would argue that such teaching approaches are long outdated, now replaced with apps, gameplay, and the concept of the flip classroom.
Pioneered by high school teachers Jonathan Bergman and Aaron Sams in 2007, the flipped classroom reverses the sequence of events from that of the traditional classroom.
Students view lecture materials, usually in the form of video lectures, as homework prior to coming to class. In-class time is reserved for activities such as interactive discussions or collaborative work, all performed under the guidance of the teacher.
The benefits are clear:
Students can consume lectures at their own pace, viewing the video again and again until they get the concept, or fast-forwarding if the information is obvious.
The teacher is present while students apply new knowledge. Doing the homework into class time gives teachers insight into which concepts, if any, that their students are struggling with and helps them adjust the class accordingly.
The flipped classroom produces tangible results: 71 percent of teachers who flipped their classes noticed improved grades, and 80 percent reported improved student attitudes as a result.
Module 9: Creative Expression & Improvisation
Every single one of us is creative. It’s human nature to be creative… the thing is that we each might have different ways of expressing our creativity.
We must encourage kids to discover and to develop their creative outlets early. In this module, imagine showing kids the many different ways creativity is expressed, from art to engineering to music to math, and then guiding them as they choose the area (or areas) they are most interested in. Critically, teachers (or parents) can then develop unique lessons for each child based on their interests, thanks to open education resources like YouTube and the Khan Academy. If my child is interested in painting and robots, a teacher or AI could scour the web and put together a custom lesson set from videos/articles where the best painters and roboticists in the world share their skills.
Adapting to change is critical for success, especially in our constantly changing world today. Improvisation is a skill that can be learned, and we need to be teaching it early.
In most collegiate “improv” classes, the core of great improvisation is the “Yes, and…” mindset. When acting out a scene, one actor might introduce a new character or idea, completely changing the context of the scene. It’s critical that the other actors in the scene say “Yes, and…” accept the new reality, then add something new of their own.
Imagine playing similar role-play games in elementary schools, where a teacher gives the students a scene/context and constantly changes variables, forcing them to adapt and play.
Module 10: Coding
Computer science opens more doors for students than any other discipline in today’s world. Learning even the basics will help students in virtually any career, from architecture to zoology.
Coding is an important tool for computer science, in the way that arithmetic is a tool for doing mathematics and words are a tool for English. Coding creates software, but computer science is a broad field encompassing deep concepts that go well beyond coding.
Every 21st century student should also have a chance to learn about algorithms, how to make an app, or how the internet works. Computational thinking allows preschoolers to grasp concepts like algorithms, recursion and heuristics. Even if they don’t understand the terms, they’ll learn the basic concepts.
There are more than 500,000 open jobs in computing right now, representing the number one source of new wages in the US, and these jobs are projected to grow at twice the rate of all other jobs.
Coding is fun! Beyond the practical reasons for learning how to code, there’s the fact that creating a game or animation can be really fun for kids.
Module 11: Entrepreneurship & Sales
At its core, entrepreneurship is about identifying a problem (an opportunity), developing a vision on how to solve it, and working with a team to turn that vision into reality. I mentioned Elon’s school, Ad Astra: here, again, entrepreneurship is a core discipline where students create and actually sell products and services to each other and the school community.
You could recreate this basic exercise with a group of kids in lots of fun ways to teach them the basic lessons of entrepreneurship.
Related to entrepreneurship is sales. In my opinion, we need to be teaching sales to every child at an early age. Being able to “sell” an idea (again related to storytelling) has been a critical skill in my career, and it is a competency that many people simply never learned.
The lemonade stand has been a classic, though somewhat meager, lesson in sales from past generations, where a child sits on a street corner and tries to sell homemade lemonade for $0.50 to people passing by. I’d suggest we step the game up and take a more active approach in gamifying sales, and maybe having the classroom create a Kickstarter, Indiegogo or GoFundMe campaign. The experience of creating a product or service and successfully selling it will create an indelible memory and give students the tools to change the world.
Module 12: Language
A little over a year ago, I spent a week in China meeting with parents whose focus on kids’ education is extraordinary. One of the areas I found fascinating is how some of the most advanced parents are teaching their kids new languages: through games. On the tablet, the kids are allowed to play games, but only in French. A child’s desire to win fully engages them and drives their learning rapidly.
Beyond games, there’s virtual reality. We know that full immersion is what it takes to become fluent (at least later in life). A semester abroad in France or Italy, and you’ve got a great handle on the language and the culture. But what about for an eight-year-old?
Imagine a module where for an hour each day, the children spend their time walking around Italy in a VR world, hanging out with AI-driven game characters who teach them, engage them, and share the culture and the language in the most personalized and compelling fashion possible.
Exponential Technologies for Our Classrooms
If you’ve attended Abundance 360 or Singularity University, or followed my blogs, you’ll probably agree with me that the way our children will learn is going to fundamentally transform over the next decade.
Here’s an overview of the top five technologies that will reshape the future of education:
Tech 1: Virtual Reality (VR) can make learning truly immersive. Research has shown that we remember 20 percent of what we hear, 30 percent of what we see, and up to 90 percent of what we do or simulate. Virtual reality yields the latter scenario impeccably. VR enables students to simulate flying through the bloodstream while learning about different cells they encounter, or travel to Mars to inspect the surface for life.
To make this a reality, Google Cardboard just launched its Pioneer Expeditions product. Under this program, thousands of schools around the world have gotten a kit containing everything a teacher needs to take his or her class on a virtual trip. While data on VR use in K-12 schools and colleges have yet to be gathered, the steady growth of the market is reflected in the surge of companies (including zSpace, Alchemy VR and Immersive VR Education) solely dedicated to providing schools with packaged education curriculum and content.
Add to VR a related technology called augmented reality (AR), and experiential education really comes alive. Imagine wearing an AR headset that is able to superimpose educational lessons on top of real-world experiences. Interested in botany? As you walk through a garden, the AR headset superimposes the name and details of every plant you see.
Tech 2: 3D Printing is allowing students to bring their ideas to life. Never mind the computer on every desktop (or a tablet for every student), that’s a given. In the near future, teachers and students will want or have a 3D printer on the desk to help them learn core science, technology, engineering and mathematics (STEM) principles. Bre Pettis, of MakerBot Industries, in a grand but practical vision, sees a 3D printer on every school desk in America. “Imagine if you had a 3D printer instead of a LEGO set when you were a kid; what would life be like now?” asks Mr. Pettis. You could print your own mini-figures, your own blocks, and you could iterate on new designs as quickly as your imagination would allow. MakerBots are now in over 5,000 K-12 schools across the US.
Taking this one step further, you could imagine having a 3D file for most entries in Wikipedia, allowing you to print out and study an object you can only read about or visualize in VR.
Tech 3: Sensors & Networks. An explosion of sensors and networks are going to connect everyone at gigabit speeds, making access to rich video available at all times. At the same time, sensors continue to miniaturize and reduce in power, becoming embedded in everything. One benefit will be the connection of sensor data with machine learning and AI (below), such that knowledge of a child’s attention drifting, or confusion, can be easily measured and communicated. The result would be a representation of the information through an alternate modality or at a different speed.
Tech 4: Machine Learning is making learning adaptive and personalized. No two students are identical—they have different modes of learning (by reading, seeing, hearing, doing), come from different educational backgrounds, and have different intellectual capabilities and attention spans. Advances in machine learning and the surging adaptive learning movement are seeking to solve this problem. Companies like Knewton and Dreambox have over 15 million students on their respective adaptive learning platforms. Soon, every education application will be adaptive, learning how to personalize the lesson for a specific student. There will be adaptive quizzing apps, flashcard apps, textbook apps, simulation apps and many more.
Tech 5: Artificial Intelligence or “An AI Teaching Companion.” Neil Stephenson’s book The Diamond Age presents a fascinating piece of educational technology called “A Young Lady’s Illustrated Primer.”
As described by Beat Schwendimann, “The primer is an interactive book that can answer a learner’s questions (spoken in natural language), teach through allegories that incorporate elements of the learner’s environment, and presents contextual just-in-time information.
“The primer includes sensors that monitor the learner’s actions and provide feedback. The learner is in a cognitive apprenticeship with the book: The primer models a certain skill (through allegorical fairy tale characters), which the learner then imitates in real life.
“The primer follows a learning progression with increasingly more complex tasks. The educational goals of the primer are humanist: To support the learner to become a strong and independently thinking person.”
The primer, an individualized AI teaching companion is the result of technological convergence and is beautifully described by YouTuber CGP Grey in his video: Digital Aristotle: Thoughts on the Future of Education.
Your AI companion will have unlimited access to information on the cloud and will deliver it at the optimal speed to each student in an engaging, fun way. This AI will demonetize and democratize education, be available to everyone for free (just like Google), and offering the best education to the wealthiest and poorest children on the planet equally.
This AI companion is not a tutor who spouts facts, figures and answers, but a player on the side of the student, there to help him or her learn, and in so doing, learn how to learn better. The AI is always alert, watching for signs of frustration and boredom that may precede quitting, for signs of curiosity or interest that tend to indicate active exploration, and for signs of enjoyment and mastery, which might indicate a successful learning experience.
Ultimately, we’re heading towards a vastly more educated world. We are truly living during the most exciting time to be alive.
Mindsets for the 21st Century
Finally, it’s important for me to discuss mindsets. How we think about the future colors how we learn and what we do. I’ve written extensively about the importance of an abundance and exponential mindset for entrepreneurs and CEOs. I also think that attention to mindset in our elementary schools, when a child is shaping the mental “operating system” for the rest of their life, is even more important.
As such, I would recommend that a school adopt a set of principles that teach and promote a number of mindsets in the fabric of their programs.
Many “mindsets” are important to promote. Here are a couple to consider:
Nurturing Optimism & An Abundance Mindset:
We live in a competitive world, and kids experience a significant amount of pressure to perform. When they fall short, they feel deflated. We all fail at times; that’s part of life. If we want to raise “can-do” kids who can work through failure and come out stronger for it, it’s wise to nurture optimism. Optimistic kids are more willing to take healthy risks, are better problem-solvers, and experience positive relationships. You can nurture optimism in your school by starting each day by focusing on gratitude (what each child is grateful for), or a “positive focus” in which each student takes 30 seconds to talk about what they are most excited about, or what recent event was positively impactful to them. (NOTE: I start every meeting inside my Strike Force team with a positive focus.)
Finally, helping students understand (through data and graphs) that the world is in fact getting better (see my first book: Abundance: The Future is Better Than You Think) will help them counter the continuous flow of negative news flowing through our news media.
When kids feel confident in their abilities and excited about the world, they are willing to work harder and be more creative.
Tolerance for Failure:
Tolerating failure is a difficult lesson to learn and a difficult lesson to teach. But it is critically important to succeeding in life.
Astro Teller, who runs Google’s innovation branch “X,” talks a lot about encouraging failure. At X, they regularly try to “kill” their ideas. If they are successful in killing an idea, and thus “failing,” they save lots of time, money and resources. The ideas they can’t kill survive and develop into billion-dollar businesses. The key is that each time an idea is killed, Astro rewards the team, literally, with cash bonuses. Their failure is celebrated and they become a hero.
This should be reproduced in the classroom: kids should try to be critical of their best ideas (learn critical thinking), then they should be celebrated for ‘successfully failing,’ perhaps with cake, balloons, confetti, and lots of Silly String.
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