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#433895 Sci-Fi Movies Are the Secret Weapon That ...

If there’s one line that stands the test of time in Steven Spielberg’s 1993 classic Jurassic Park, it’s probably Jeff Goldblum’s exclamation, “Your scientists were so preoccupied with whether or not they could, they didn’t stop to think if they should.”

Goldblum’s character, Dr. Ian Malcolm, was warning against the hubris of naively tinkering with dinosaur DNA in an effort to bring these extinct creatures back to life. Twenty-five years on, his words are taking on new relevance as a growing number of scientists and companies are grappling with how to tread the line between “could” and “should” in areas ranging from gene editing and real-world “de-extinction” to human augmentation, artificial intelligence and many others.

Despite growing concerns that powerful emerging technologies could lead to unexpected and wide-ranging consequences, innovators are struggling with how to develop beneficial new products while being socially responsible. Part of the answer could lie in watching more science fiction movies like Jurassic Park.

Hollywood Lessons in Societal Risks
I’ve long been interested in how innovators and others can better understand the increasingly complex landscape around the social risks and benefits associated with emerging technologies. Growing concerns over the impacts of tech on jobs, privacy, security and even the ability of people to live their lives without undue interference highlight the need for new thinking around how to innovate responsibly.

New ideas require creativity and imagination, and a willingness to see the world differently. And this is where science fiction movies can help.

Sci-fi flicks are, of course, notoriously unreliable when it comes to accurately depicting science and technology. But because their plots are often driven by the intertwined relationships between people and technology, they can be remarkably insightful in revealing social factors that affect successful and responsible innovation.

This is clearly seen in Jurassic Park. The movie provides a surprisingly good starting point for thinking about the pros and cons of modern-day genetic engineering and the growing interest in bringing extinct species back from the dead. But it also opens up conversations around the nature of complex systems that involve both people and technology, and the potential dangers of “permissionless” innovation that’s driven by power, wealth and a lack of accountability.

Similar insights emerge from a number of other movies, including Spielberg’s 2002 film “Minority Report”—which presaged a growing capacity for AI-enabled crime prediction and the ethical conundrums it’s raising—as well as the 2014 film Ex Machina.

As with Jurassic Park, Ex Machina centers around a wealthy and unaccountable entrepreneur who is supremely confident in his own abilities. In this case, the technology in question is artificial intelligence.

The movie tells a tale of an egotistical genius who creates a remarkable intelligent machine—but he lacks the awareness to recognize his limitations and the risks of what he’s doing. It also provides a chilling insight into potential dangers of creating machines that know us better than we know ourselves, while not being bound by human norms or values.

The result is a sobering reminder of how, without humility and a good dose of humanity, our innovations can come back to bite us.

The technologies in Jurassic Park, Minority Report, and Ex Machina lie beyond what is currently possible. Yet these films are often close enough to emerging trends that they help reveal the dangers of irresponsible, or simply naive, innovation. This is where these and other science fiction movies can help innovators better understand the social challenges they face and how to navigate them.

Real-World Problems Worked Out On-Screen
In a recent op-ed in the New York Times, journalist Kara Swisher asked, “Who will teach Silicon Valley to be ethical?” Prompted by a growing litany of socially questionable decisions amongst tech companies, Swisher suggests that many of them need to grow up and get serious about ethics. But ethics alone are rarely enough. It’s easy for good intentions to get swamped by fiscal pressures and mired in social realities.

Elon Musk has shown that brilliant tech innovators can take ethical missteps along the way. Image Credit:AP Photo/Chris Carlson
Technology companies increasingly need to find some way to break from business as usual if they are to become more responsible. High-profile cases involving companies like Facebook and Uber as well as Tesla’s Elon Musk have highlighted the social as well as the business dangers of operating without fully understanding the consequences of people-oriented actions.

Many more companies are struggling to create socially beneficial technologies and discovering that, without the necessary insights and tools, they risk blundering about in the dark.

For instance, earlier this year, researchers from Google and DeepMind published details of an artificial intelligence-enabled system that can lip-read far better than people. According to the paper’s authors, the technology has enormous potential to improve the lives of people who have trouble speaking aloud. Yet it doesn’t take much to imagine how this same technology could threaten the privacy and security of millions—especially when coupled with long-range surveillance cameras.

Developing technologies like this in socially responsible ways requires more than good intentions or simply establishing an ethics board. People need a sophisticated understanding of the often complex dynamic between technology and society. And while, as Mozilla’s Mitchell Baker suggests, scientists and technologists engaging with the humanities can be helpful, it’s not enough.

An Easy Way into a Serious Discipline
The “new formulation” of complementary skills Baker says innovators desperately need already exists in a thriving interdisciplinary community focused on socially responsible innovation. My home institution, the School for the Future of Innovation in Society at Arizona State University, is just one part of this.

Experts within this global community are actively exploring ways to translate good ideas into responsible practices. And this includes the need for creative insights into the social landscape around technology innovation, and the imagination to develop novel ways to navigate it.

People love to come together as a movie audience.Image credit: The National Archives UK, CC BY 4.0
Here is where science fiction movies become a powerful tool for guiding innovators, technology leaders and the companies where they work. Their fictional scenarios can reveal potential pitfalls and opportunities that can help steer real-world decisions toward socially beneficial and responsible outcomes, while avoiding unnecessary risks.

And science fiction movies bring people together. By their very nature, these films are social and educational levelers. Look at who’s watching and discussing the latest sci-fi blockbuster, and you’ll often find a diverse cross-section of society. The genre can help build bridges between people who know how science and technology work, and those who know what’s needed to ensure they work for the good of society.

This is the underlying theme in my new book Films from the Future: The Technology and Morality of Sci-Fi Movies. It’s written for anyone who’s curious about emerging trends in technology innovation and how they might potentially affect society. But it’s also written for innovators who want to do the right thing and just don’t know where to start.

Of course, science fiction films alone aren’t enough to ensure socially responsible innovation. But they can help reveal some profound societal challenges facing technology innovators and possible ways to navigate them. And what better way to learn how to innovate responsibly than to invite some friends round, open the popcorn and put on a movie?

It certainly beats being blindsided by risks that, with hindsight, could have been avoided.

Andrew Maynard, Director, Risk Innovation Lab, Arizona State University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Posted in Human Robots

#433884 Designer Babies, and Their Babies: How ...

As if stand-alone technologies weren’t advancing fast enough, we’re in age where we must study the intersection points of these technologies. How is what’s happening in robotics influenced by what’s happening in 3D printing? What could be made possible by applying the latest advances in quantum computing to nanotechnology?

Along these lines, one crucial tech intersection is that of artificial intelligence and genomics. Each field is seeing constant progress, but Jamie Metzl believes it’s their convergence that will really push us into uncharted territory, beyond even what we’ve imagined in science fiction. “There’s going to be this push and pull, this competition between the reality of our biology with its built-in limitations and the scope of our aspirations,” he said.

Metzl is a senior fellow at the Atlantic Council and author of the upcoming book Hacking Darwin: Genetic Engineering and the Future of Humanity. At Singularity University’s Exponential Medicine conference last week, he shared his insights on genomics and AI, and where their convergence could take us.

Life As We Know It
Metzl explained how genomics as a field evolved slowly—and then quickly. In 1953, James Watson and Francis Crick identified the double helix structure of DNA, and realized that the order of the base pairs held a treasure trove of genetic information. There was such a thing as a book of life, and we’d found it.

In 2003, when the Human Genome Project was completed (after 13 years and $2.7 billion), we learned the order of the genome’s 3 billion base pairs, and the location of specific genes on our chromosomes. Not only did a book of life exist, we figured out how to read it.

Jamie Metzl at Exponential Medicine
Fifteen years after that, it’s 2018 and precision gene editing in plants, animals, and humans is changing everything, and quickly pushing us into an entirely new frontier. Forget reading the book of life—we’re now learning how to write it.

“Readable, writable, and hackable, what’s clear is that human beings are recognizing that we are another form of information technology, and just like our IT has entered this exponential curve of discovery, we will have that with ourselves,” Metzl said. “And it’s intersecting with the AI revolution.”

Learning About Life Meets Machine Learning
In 2016, DeepMind’s AlphaGo program outsmarted the world’s top Go player. In 2017 AlphaGo Zero was created: unlike AlphaGo, AlphaGo Zero wasn’t trained using previous human games of Go, but was simply given the rules of Go—and in four days it defeated the AlphaGo program.

Our own biology is, of course, vastly more complex than the game of Go, and that, Metzl said, is our starting point. “The system of our own biology that we are trying to understand is massively, but very importantly not infinitely, complex,” he added.

Getting a standardized set of rules for our biology—and, eventually, maybe even outsmarting our biology—will require genomic data. Lots of it.

Multiple countries already starting to produce this data. The UK’s National Health Service recently announced a plan to sequence the genomes of five million Britons over the next five years. In the US the All of Us Research Program will sequence a million Americans. China is the most aggressive in sequencing its population, with a goal of sequencing half of all newborns by 2020.

“We’re going to get these massive pools of sequenced genomic data,” Metzl said. “The real gold will come from comparing people’s sequenced genomes to their electronic health records, and ultimately their life records.” Getting people comfortable with allowing open access to their data will be another matter; Metzl mentioned that Luna DNA and others have strategies to help people get comfortable with giving consent to their private information. But this is where China’s lack of privacy protection could end up being a significant advantage.

To compare genotypes and phenotypes at scale—first millions, then hundreds of millions, then eventually billions, Metzl said—we’re going to need AI and big data analytic tools, and algorithms far beyond what we have now. These tools will let us move from precision medicine to predictive medicine, knowing precisely when and where different diseases are going to occur and shutting them down before they start.

But, Metzl said, “As we unlock the genetics of ourselves, it’s not going to be about just healthcare. It’s ultimately going to be about who and what we are as humans. It’s going to be about identity.”

Designer Babies, and Their Babies
In Metzl’s mind, the most serious application of our genomic knowledge will be in embryo selection.

Currently, in-vitro fertilization (IVF) procedures can extract around 15 eggs, fertilize them, then do pre-implantation genetic testing; right now what’s knowable is single-gene mutation diseases and simple traits like hair color and eye color. As we get to the millions and then billions of people with sequences, we’ll have information about how these genetics work, and we’re going to be able to make much more informed choices,” Metzl said.

Imagine going to a fertility clinic in 2023. You give a skin graft or a blood sample, and using in-vitro gametogenesis (IVG)—infertility be damned—your skin or blood cells are induced to become eggs or sperm, which are then combined to create embryos. The dozens or hundreds of embryos created from artificial gametes each have a few cells extracted from them, and these cells are sequenced. The sequences will tell you the likelihood of specific traits and disease states were that embryo to be implanted and taken to full term. “With really anything that has a genetic foundation, we’ll be able to predict with increasing levels of accuracy how that potential child will be realized as a human being,” Metzl said.

This, he added, could lead to some wild and frightening possibilities: if you have 1,000 eggs and you pick one based on its optimal genetic sequence, you could then mate your embryo with somebody else who has done the same thing in a different genetic line. “Your five-day-old embryo and their five-day-old embryo could have a child using the same IVG process,” Metzl said. “Then that child could have a child with another five-day-old embryo from another genetic line, and you could go on and on down the line.”

Sounds insane, right? But wait, there’s more: as Jason Pontin reported earlier this year in Wired, “Gene-editing technologies such as Crispr-Cas9 would make it relatively easy to repair, add, or remove genes during the IVG process, eliminating diseases or conferring advantages that would ripple through a child’s genome. This all may sound like science fiction, but to those following the research, the combination of IVG and gene editing appears highly likely, if not inevitable.”

From Crazy to Commonplace?
It’s a slippery slope from gene editing and embryo-mating to a dystopian race to build the most perfect humans possible. If somebody’s investing so much time and energy in selecting their embryo, Metzl asked, how will they think about the mating choices of their children? IVG could quickly leave the realm of healthcare and enter that of evolution.

“We all need to be part of an inclusive, integrated, global dialogue on the future of our species,” Metzl said. “Healthcare professionals are essential nodes in this.” Not least among this dialogue should be the question of access to tech like IVG; are there steps we can take to keep it from becoming a tool for a wealthy minority, and thereby perpetuating inequality and further polarizing societies?

As Pontin points out, at its inception 40 years ago IVF also sparked fear, confusion, and resistance—and now it’s as normal and common as could be, with millions of healthy babies conceived using the technology.

The disruption that genomics, AI, and IVG will bring to reproduction could follow a similar story cycle—if we’re smart about it. As Metzl put it, “This must be regulated, because it is life.”

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Posted in Human Robots

#433872 Breaking Out of the Corporate Bubble ...

For big companies, success is a blessing and a curse. You don’t get big without doing something (or many things) very right. It might start with an invention or service the world didn’t know it needed. Your product takes off, and growth brings a whole new set of logistical challenges. Delivering consistent quality, hiring the right team, establishing a strong culture, tapping into new markets, satisfying shareholders. The list goes on.

Eventually, however, what made you successful also makes you resistant to change.

You’ve built a machine for one purpose, and it’s running smoothly, but what about retooling that machine to make something new? Not so easy. Leaders of big companies know there is no future for their organizations without change. And yet, they struggle to drive it.

In their new book, Leading Transformation: How to Take Charge of Your Company’s Future, Kyle Nel, Nathan Furr, and Thomas Ramsøy aim to deliver a roadmap for corporate transformation.

The book focuses on practical tools that have worked in big companies to break down behavioral and cognitive biases, envision radical futures, and run experiments. These include using science fiction and narrative to see ahead and adopting better measures of success for new endeavors.

A thread throughout is how to envision a new future and move into that future.

We’re limited by the bubbles in which we spend the most time—the corporate bubble, the startup bubble, the nonprofit bubble. The mutually beneficial convergence of complementary bubbles, then, can be a powerful tool for kickstarting transformation. The views and experiences of one partner can challenge the accepted wisdom of the other; resources can flow into newly co-created visions and projects; and connections can be made that wouldn’t otherwise exist.

The authors call such alliances uncommon partners. In the following excerpt from the book, Made In Space, a startup building 3D printers for space, helps Lowe’s explore an in-store 3D printing system, and Lowe’s helps Made In Space expand its vision and focus.

Uncommon Partners
In a dingy conference room at NASA, five prototypical nerds, smelling of Thai food, laid out the path to printing satellites in space and buildings on distant planets. At the end of their four-day marathon, they emerged with an artifact trail that began with early prototypes for the first 3D printer on the International Space Station and ended in the additive-manufacturing future—a future much bigger than 3D printing.

In the additive-manufacturing future, we will view everything as transient, or capable of being repurposed into new things. Rather than throwing away a soda bottle or a bent nail, we will simply reprocess these things into a new hinge for the fence we are building or a light switch plate for the tool shed. Indeed, we might not even go buy bricks for the tool shed, but instead might print them from impurities pulled from the air and the dirt beneath our feet. Such a process would both capture carbon in the air to make the bricks and avoid all the carbon involved in making and then transporting traditional bricks to your house.

If it all sounds a little too science fiction, think again. Lowe’s has already been honored as a Champion of Change by the US government for its prototype system to recycle plastic (e.g., plastic bags and bottles). The future may be closer than you have imagined. But to get there, Lowe’s didn’t work alone. It had to work with uncommon partners to create the future.

Uncommon partners are the types of organizations you might not normally work with, but which can greatly help you create radical new futures. Increasingly, as new technologies emerge and old industries converge, companies are finding that working independently to create all the necessary capabilities to enter new industries or create new technologies is costly, risky, and even counterproductive. Instead, organizations are finding that they need to collaborate with uncommon partners as an ecosystem to cocreate the future together. Nathan [Furr] and his colleague at INSEAD, Andrew Shipilov, call this arrangement an adaptive ecosystem strategy and described how companies such as Lowe’s, Samsung, Mastercard, and others are learning to work differently with partners and to work with different kinds of partners to more effectively discover new opportunities. For Lowe’s, an adaptive ecosystem strategy working with uncommon partners forms the foundation of capturing new opportunities and transforming the company. Despite its increased agility, Lowe’s can’t be (and shouldn’t become) an independent additive-manufacturing, robotics-using, exosuit-building, AR-promoting, fill-in-the-blank-what’s-next-ing company in addition to being a home improvement company. Instead, Lowe’s applies an adaptive ecosystem strategy to find the uncommon partners with which it can collaborate in new territory.

To apply the adaptive ecosystem strategy with uncommon partners, start by identifying the technical or operational components required for a particular focus area (e.g., exosuits) and then sort these components into three groups. First, there are the components that are emerging organically without any assistance from the orchestrator—the leader who tries to bring together the adaptive ecosystem. Second, there are the elements that might emerge, with encouragement and support. Third are the elements that won’t happen unless you do something about it. In an adaptive ecosystem strategy, you can create regular partnerships for the first two elements—those already emerging or that might emerge—if needed. But you have to create the elements in the final category (those that won’t emerge) either with an uncommon partner or by yourself.

For example, when Lowe’s wanted to explore the additive-manufacturing space, it began a search for an uncommon partner to provide the missing but needed capabilities. Unfortunately, initial discussions with major 3D printing companies proved disappointing. The major manufacturers kept trying to sell Lowe’s 3D printers. But the vision our group had created with science fiction was not for vendors to sell Lowe’s a printer, but for partners to help the company build a system—something that would allow customers to scan, manipulate, print, and eventually recycle additive-manufacturing objects. Every time we discussed 3D printing systems with these major companies, they responded that they could do it and then tried to sell printers. When Carin Watson, one of the leading lights at Singularity University, introduced us to Made In Space (a company being incubated in Singularity University’s futuristic accelerator), we discovered an uncommon partner that understood what it meant to cocreate a system.

Initially, Made In Space had been focused on simply getting 3D printing to work in space, where you can’t rely on gravity, you can’t send up a technician if the machine breaks, and you can’t release noxious fumes into cramped spacecraft quarters. But after the four days in the conference room going over the comic for additive manufacturing, Made In Space and Lowe’s emerged with a bigger vision. The company helped lay out an artifact trail that included not only the first printer on the International Space Station but also printing system services in Lowe’s stores.

Of course, the vision for an additive-manufacturing future didn’t end there. It also reshaped Made In Space’s trajectory, encouraging the startup, during those four days in a NASA conference room, to design a bolder future. Today, some of its bold projects include the Archinaut, a system that enables satellites to build themselves while in space, a direction that emerged partly from the science fiction narrative we created around additive manufacturing.

In summary, uncommon partners help you succeed by providing you with the capabilities you shouldn’t be building yourself, as well as with fresh insights. You also help uncommon partners succeed by creating new opportunities from which they can prosper.

Helping Uncommon Partners Prosper
Working most effectively with uncommon partners can require a shift from more familiar outsourcing or partnership relationships. When working with uncommon partners, you are trying to cocreate the future, which entails a great deal more uncertainty. Because you can’t specify outcomes precisely, agreements are typically less formal than in other types of relationships, and they operate under the provisions of shared vision and trust more than binding agreement clauses. Moreover, your goal isn’t to extract all the value from the relationship. Rather, you need to find a way to share the value.

Ideally, your uncommon partners should be transformed for the better by the work you do. For example, Lowe’s uncommon partner developing the robotics narrative was a small startup called Fellow Robots. Through their work with Lowe’s, Fellow Robots transformed from a small team focused on a narrow application of robotics (which was arguably the wrong problem) to a growing company developing a very different and valuable set of capabilities: putting cutting-edge technology on top of the old legacy systems embedded at the core of most companies. Working with Lowe’s allowed Fellow Robots to discover new opportunities, and today Fellow Robots works with retailers around the world, including BevMo! and Yamada. Ultimately, working with uncommon partners should be transformative for both of you, so focus more on creating a bigger pie than on how you are going to slice up a smaller pie.

The above excerpt appears in the new book Leading Transformation: How to Take Charge of Your Company’s Future by Kyle Nel, Nathan Furr, and Thomas Ramsøy, published by Harvard Business Review Press.

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Posted in Human Robots

#433689 The Rise of Dataism: A Threat to Freedom ...

What would happen if we made all of our data public—everything from wearables monitoring our biometrics, all the way to smartphones monitoring our location, our social media activity, and even our internet search history?

Would such insights into our lives simply provide companies and politicians with greater power to invade our privacy and manipulate us by using our psychological profiles against us?

A burgeoning new philosophy called dataism doesn’t think so.

In fact, this trending ideology believes that liberating the flow of data is the supreme value of the universe, and that it could be the key to unleashing the greatest scientific revolution in the history of humanity.

What Is Dataism?
First mentioned by David Brooks in his 2013 New York Times article “The Philosophy of Data,” dataism is an ethical system that has been most heavily explored and popularized by renowned historian, Yuval Noah Harari.

In his 2016 book Homo Deus, Harari described dataism as a new form of religion that celebrates the growing importance of big data.

Its core belief centers around the idea that the universe gives greater value and support to systems, individuals, and societies that contribute most heavily and efficiently to data processing. In an interview with Wired, Harari stated, “Humans were special and important because up until now they were the most sophisticated data processing system in the universe, but this is no longer the case.”

Now, big data and machine learning are proving themselves more sophisticated, and dataists believe we should hand over as much information and power to these algorithms as possible, allowing the free flow of data to unlock innovation and progress unlike anything we’ve ever seen before.

Pros: Progress and Personal Growth
When you let data run freely, it’s bound to be mixed and matched in new ways that inevitably spark progress. And as we enter the exponential future where every person is constantly connected and sharing their data, the potential for such collaborative epiphanies becomes even greater.

We can already see important increases in quality of life thanks to companies like Google. With Google Maps on your phone, your position is constantly updating on their servers. This information, combined with everyone else on the planet using a phone with Google Maps, allows your phone to inform you of traffic conditions. Based on the speed and location of nearby phones, Google can reroute you to less congested areas or help you avoid accidents. And since you trust that these algorithms have more data than you, you gladly hand over your power to them, following your GPS’s directions rather than your own.

We can do the same sort of thing with our bodies.

Imagine, for instance, a world where each person has biosensors in their bloodstreams—a not unlikely or distant possibility when considering diabetic people already wear insulin pumps that constantly monitor their blood sugar levels. And let’s assume this data was freely shared to the world.

Now imagine a virus like Zika or the Bird Flu breaks out. Thanks to this technology, the odd change in biodata coming from a particular region flags an artificial intelligence that feeds data to the CDC (Center for Disease Control and Prevention). Recognizing that a pandemic could be possible, AIs begin 3D printing vaccines on-demand, predicting the number of people who may be afflicted. When our personal AIs tell us the locations of the spreading epidemic and to take the vaccine it just delivered by drone to our homes, are we likely to follow its instructions? Almost certainly—and if so, it’s likely millions, if not billions, of lives will have been saved.

But to quickly create such vaccines, we’ll also need to liberate research.

Currently, universities and companies seeking to benefit humankind with medical solutions have to pay extensively to organize clinical trials and to find people who match their needs. But if all our biodata was freely aggregated, perhaps they could simply say “monitor all people living with cancer” to an AI, and thanks to the constant stream of data coming in from the world’s population, a machine learning program may easily be able to detect a pattern and create a cure.

As always in research, the more sample data you have, the higher the chance that such patterns will emerge. If data is flowing freely, then anyone in the world can suddenly decide they have a hunch they want to explore, and without having to spend months and months of time and money hunting down the data, they can simply test their hypothesis.

Whether garage tinkerers, at-home scientists, or PhD students—an abundance of free data allows for science to progress unhindered, each person able to operate without being slowed by lack of data. And any progress they make is immediately liberated, becoming free data shared with anyone else that may find a use for it.

Any individual with a curious passion would have the entire world’s data at their fingertips, empowering every one of us to become an expert in any subject that inspires us. Expertise we can then share back into the data stream—a positive feedback loop spearheading progress for the entirety of humanity’s knowledge.

Such exponential gains represent a dataism utopia.

Unfortunately, our current incentives and economy also show us the tragic failures of this model.

As Harari has pointed out, the rise of datism means that “humanism is now facing an existential challenge and the idea of ‘free will’ is under threat.”

Cons: Manipulation and Extortion
In 2017, The Economist declared that data was the most valuable resource on the planet—even more valuable than oil.

Perhaps this is because data is ‘priceless’: it represents understanding, and understanding represents control. And so, in the world of advertising and politics, having data on your consumers and voters gives you an incredible advantage.

This was evidenced by the Cambridge Analytica scandal, in which it’s believed that Donald Trump and the architects of Brexit leveraged users’ Facebook data to create psychological profiles that enabled them to manipulate the masses.

How powerful are these psychological models?

A team who built a model similar to that used by Cambridge Analytica said their model could understand someone as well as a coworker with access to only 10 Facebook likes. With 70 likes they could know them as well as a friend might, 150 likes to match their parents’ understanding, and at 300 likes they could even come to know someone better than their lovers. With more likes, they could even come to know someone better than that person knows themselves.

Proceeding With Caution
In a capitalist democracy, do we want businesses and politicians to know us better than we know ourselves?

In spite of the remarkable benefits that may result for our species by freely giving away our information, do we run the risk of that data being used to exploit and manipulate the masses towards a future without free will, where our daily lives are puppeteered by those who own our data?

It’s extremely possible.

And it’s for this reason that one of the most important conversations we’ll have as a species centers around data ownership: do we just give ownership of the data back to the users, allowing them to choose who to sell or freely give their data to? Or will that simply deter the entrepreneurial drive and cause all of the free services we use today, like Google Search and Facebook, to begin charging inaccessible prices? How much are we willing to pay for our freedom? And how much do we actually care?

If recent history has taught us anything, it’s that humans are willing to give up more privacy than they like to think. Fifteen years ago, it would have been crazy to suggest we’d all allow ourselves to be tracked by our cars, phones, and daily check-ins to our favorite neighborhood locations; but now most of us see it as a worthwhile trade for optimized commutes and dating. As we continue navigating that fine line between exploitation and innovation into a more technological future, what other trade-offs might we be willing to make?

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Posted in Human Robots

#433400 A Model for the Future of Education, and ...

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.

Join Me & Get Involved!
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