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Cracking the Code for the Future of Education

by | Nov 29, 2016 | Future of Education

Thomas Frey Futurist Speaker cracking the code tor the future of education

This story started in 2012 when I was asked to speak at a TEDx event in Istanbul on the future of education. Several times throughout my talk I touched on the topic of teacherless education.

After my presentation, I was approached by Cozi Namer, a Google executive who explained why teacherless education was so important to them.

“Our team at Google is looking for ways to educate the people of Africa, but very few teachers actually want to move to Africa,” he said.

The conversation was brief, but he framed the problem very succinctly. No, most teachers don’t want to move to Africa. They also don’t want to move to Siberia, Bangladesh, Pakistan, or the Amazon rain forest. There are lots of places teachers don’t want to move to.

By some counts, we are short 18 million teachers globally, and a full 23% of kids growing up today don’t attend any school at all.

There simply aren’t enough teachers at the right time and place to satisfy our growing thirst for knowledge.

Because of this, we are severely limiting human potential all across the globe. Our limited number of teachers becomes a huge barrier, not the solution they were intended to be.

Over the coming decades, if we continue to insert a teacher between us and everything we need to learn, we cannot possibly learn fast enough to meet the demands of the future.

Throughout history, education has been formed around the concept of “place” with most communities defined by the quality of their school facilities and the caliber of their educators.

For the cities and towns lucky enough to be involved in higher education, most started with building fancy buildings, attracting world-renowned scholars, and over time a college or university would grow its way into existence. This model worked well in a culture built on the “teaching” model of education.

Over the past decade, with our hyper-connected world, we began shifting away from teacher-centric schooling to more of a learning model, and while “place” still matters, it matters differently.

Teaching requires experts. Teacherless education uses experts to create the material, but doesn’t require the expert to be present each time its presented.

Education is now on the verge of a major transformation and artificial intelligence-based teacherless education systems are quickly taking center stage.

The Quantified Self

A few years ago, Kevin Kelly, co-founder of Wired Magazine, made the statement, “Through technology we are engineering our lives and bodies to be more quantifiable.”

Along with the rise of sensors and Internet of Things devices, we are able to very accurately measure all of the input and outputs of the human body.

As example, we can accurately measure the quality of air that we’re breathing, the quality of water that we’re drinking, and we can even monitor the chemical composition of sweat coming off our arms.

So how long will it be before we can measure all the inputs and outputs of the human brain?

Imagine having a system capable of measuring our mental capabilities, monitoring a large number, say 947 different categories of skills, knowledge, attributes, and characteristics.

If you think this sounds far-fetched, Larry Page, founder of Google, recently said, “In the future, Google’s software will be able to understand what you’re knowledgeable about and what you’re not.”

Imagine connecting yourself to some sort of brain scanner and instantly knowing what jobs you’re qualified for, and what skills you’re deficient in. Instead of applying for a job with a resume, we’ll give our prospective employers a copy of our latest brain scan.

The greatest risk is taking no risk at all!

The Micro College Experience

After an extended look at the future of work, I’ve projected that the average person entering the workforce in 2030 had better plan to reboot their career six times throughout their working life. Anyone faced with shifting gears that often will want to do the retraining in the least amount of time possible, making traditional colleges a very poor fit.

This growing need to rapidly reskill our workforce has given rise to our recent explosion in micro colleges.

When we launched DaVinci Coders in 2012, we were the second in the nation. Today there are over 550 coding schools that have cropped up across the U.S. with many more around the world.

When Facebook bought Oculus Rift in 2014, there was an instant uptick in the demand for VR designers, coder, and production artists. But no one was teaching it. If anyone was teaching virtual reality, they most certainly were not teaching the Oculus Rift version of it.

It is no longer possible to predict the educational needs of business 6-7 years in advance, the time it takes for traditional colleges to start producing talent in a new field.

Our digital world is forcing us to change how we do business. Today’s most successful businesses have reshaped themselves around exponential thinking and the jump-off-a-cliff-and-build-your-wings-on-the-way-down model of doing business.

  • We are currently preparing students for jobs that don’t exist…
  • Using technology that hasn’t been invented…
  • To solve problems we don’t even know are problems yet!

Bold companies are instantly triggering the need for talented people with skills aligned to grow with cutting edge industries.

Micro colleges are simply immersive forms of post-secondary education done in short periods of time. We will soon see micro colleges spring up in thousands of different categories:

  • 3D print designer training center
  • Crowdfunding certification academy
  • Dog breeder university
  • Brew master college
  • Drone pilot school
  • Data visualization and analytics school
  • Aquaponics farmers institute
  • Urban agriculture academy

Thomas Frey Futurist Speaker Solving for why?

Artificial Intelligence-Based Education

We’re standing on the brink of an A.I. technological revolution that will fundamentally alter the way we live, work, and relate to one another.

Several early use cases for A.I. have begun to open our eyes as to how it will be used, but none quite as strikingly as when Google’s DeepMind was used to play the Atari game – Breakout.

In this exercise, DeepMind had no domain knowledge and was given very little background information. It was simply asked to maximize the score.

As a neural network, DeepMind teaches itself, learning from past mistakes.

  • After 30 minutes (100 games) – Pretty terrible, but still learning
  • After 2 hours – It had mastered the game, even with the balls moving very fast
  • After 4 hours – It came up with an optimal strategy, to dig a tunnel round the side of the wall, and send the ball around the back in a superhuman accurate way. (The designers of the game didn’t even know that was possible.)

Over the following weeks, DeepMind learned to play another 49 Atari 2600 video games with minimal background information, mastering everything from a martial-arts game, to boxing, and 3D car-racing games, consistently outscoring some of the best human gamers.

“If we apply A.I. to teacherbots, the new game

will be to find the fastest way to teach students.”

Cracking the Code for Cognifying Education

If we apply A.I. to teacherbots, the new game will be to find the fastest way to teach students.

Over time, AI’s will learn every students interests, their proclivities, idiosyncrasies, preferred tools, personal reference points, and how to stay engaged and learning even in the face of distractions.

A.I. will know when our:

  • Skills are deficient
  • What’s needed to bring them up to speed
  • How and when to schedule our next training
  • When we’ve mastered the topic

Throughout this training curve, individual learning will begin to scale far faster than anything we’ve ever dreamed possible – 4X, 6X and perhaps even 10X faster than anything today.

Completing a four-year college degree in 1-2 months is entirely possible with this form of A.I. learning systems.

Thomas Frey Futurist Speaker Life revolves around tiny accomplishments… even artificial life

Final Thoughts

If we work within our existing system for education, the best we can hope for is a few percentage points improvement. The system itself becomes the limiting factor.

By creating a new system, with high speed A.I. learning systems in place, we remove all of our past limitations.

Naturally, in describing the conceptual basis for a new kind of artificial intelligence-infused learning system I’ve glossed over thousand of details critical making it work. This will not unfold instantly and may easily take the better part of a decade before we can work most of the bugs out. But it’s coming.

We’re entering a world that will require higher caliber people to make it work, and it would be preposterous for us to think our existing systems can suddenly start producing better results.

When it comes to education, we have met the enemy, and it is us. Ironically, we need to step aside so we can finally achieve the full human experience.

By Futurist Thomas Frey

Author of “Epiphany Z – 8 Radical Visions for Transforming Your Future

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Cracking the Code for the Future of Education

by | Nov 29, 2016 | Future of Education

I was thoroughly intrigued when I found out the Colorado School of Mines in Golden, Colorado was offering a degree in asteroid mining.

Yes, the idea of extracting water, oxygen, minerals, and metals from an asteroid sounds like science fiction to most people, but it’s not that far away.  In fact, Colorado School of Mines’ newly launched “Space Resources” program will help people get in on the ground floor.

After thinking about the proactive nature of this approach, it became abundantly clear how backward thinking most colleges have become.

When colleges decide on a new degree program, they must first recruit instructors, create a new curriculum, and attract students. As a result, the talent churned out of these newly minted programs is the product of a 6-7 year pipeline.

For this reason, anticipatory-thinking institutions really need to be setting their sights on what business and industries will need 7-10 years from now.

The Risk-Averse Nature of Education

When Harvard professor Clayton M. Christensen released his best-selling book, The Innovator’s Dilemma, his core message that disruptive change is the path to success, was only partially embraced by higher education.

While many were experimenting with MOOCs and smart whiteboards, changes in the subject matter of their courses still evolved at the traditional pace of discovery.

This is not to say colleges are not innovative. Rather, the demands of today’s emerging tech environment are forcing business and industries to shift into an entirely new gear. And that most definitely includes our academic institutions.

From a management perspective, it’s far easier to oversee a contained system where all variables are constrained. But during times of change, we tend to give far more power to the “unleashers,” who are determined to test the status quo and release ideas and trial balloons to see what works.

For this reason, managers and creatives often find themselves on opposing sides, and the winners of these warring factions often determine what we as consumers see as the resulting ripples of change.

Offering Pilot Programs

When Facebook bought Oculus Rift in March 2014 for $2 billion, the job boards went crazy, as there was an instant uptick in the demand for VR designers, engineers, and experience creators. But no one was teaching VR, and certainly not the Oculus Rift version of it.

Colleges have a long history of being blindsided by new technologies:

  • When eBay launched, no one was teaching ecommerce strategies
  • When Myspace launched, no one was teaching social networking
  • When Google launched, no one was teaching online search engine strategies
  • When Uber launched, no one was teaching sharing economy business models
  • When Apple first opened their App Store, no one was teaching smart phone app design
  • When Amazon first allowed online storefronts, no one was teaching the Amazon business model
  • When YouTube first offered ways to monetize videos, no one was teaching it

Since most academic institutions are only willing to put their name on programs with long-term viability, the endorsement of half-baked agendas does not come easy. However, that is exactly what needs to be done.

Colleges can no longer afford to remain comfortably behind the curve.

52 Future College Degrees

As a way of priming your thinking on this matter, here are 52 future degrees that forward-thinking colleges could start offering today:

  1. Space Exploration – space tourism planning and management
  2. Space Exploration – planetary colony design and operation
  3.  Space Exploration – next generation space infrastructure
  4. Space Exploration – advanced cosmology and non-earth human habitats
  5. Bioengineering with CRISPR – policy and procedural strategies
  6. Bioengineering with CRISPR – advanced genetic engineering systems
  7. Bioengineering with CRISPR – operational implementations and system engineering
  8. Bioengineering with CRISPR – ethical regulation and oversight
  9. Smart City – autonomous traffic integration
  10. Smart City – mixed reality modeling
  11. Smart City – autonomous construction integration
  12. Smart City – next generation municipal planning and strategy
  13. Autonomous Agriculture – robotic systems
  14. Autonomous Agriculture – drone systems
  15. Autonomous Agriculture – supply chain management
  16. Autonomous Agriculture – systems theory and integration
  17. Swarmbot – design, theory, and management
  18. Swarmbot – system engineering and oversight
  19. Swarmbot – municipal system design
  20. Swarmbot – law enforcement and advanced criminology systems
  21. Cryptocurrency – digital coin economics
  22. Cryptocurrency – crypto-banking system design
  23. Cryptocurrency – regulatory systems and oversight
  24. Cryptocurrency – forensic accounting strategies
  25. Blockchain – design, systems, and applications
  26. Blockchain – blockchain for biological systems
  27. Blockchain – large-scale integration structures
  28. Blockchain – municipal system design strategies
  29. Global Systems – system planning, architecture, and design
  30. Global Systems – large-scale integration strategies
  31. Global Systems – operational systems checks and balance
  32. Global Systems – governmental systems in a borderless digital world
  33. Unmanned Aerial Vehicle - drone film making
  34. Unmanned Aerial Vehicle – command center operations
  35. Unmanned Aerial Vehicle – municipal modeling and planning systems
  36. Unmanned Aerial Vehicle – emergency response systems
  37. Mixed Reality - experiential retail
  38. Mixed Reality – three-dimensional storytelling
  39. Mixed Reality – game design
  40. Mixed Reality – therapeutic systems and design
  41. Advanced Reproductive Systems – designer baby strategies, planning, and ethics
  42. Advanced Reproductive Systems – surrogate parenting policy and approaches
  43. Advanced Reproductive Systems – organic nano structures
  44. Advanced Reproductive Systems – clone engineering and advanced processes
  45. Artificial Intelligence – data management in an AI environment
  46. Artificial Intelligence – advanced human-AI integration
  47. Artificial Intelligence – streaming AI data services
  48. Artificial Intelligence – advanced marketing with AI
  49. Quantum Computing – data strategies in a quantum-connected world
  50. Quantum Computing – quantum-level encryption and security
  51. Quantum Computing – quantum computing implementation strategies
  52. Quantum Computing – AI-quantum system integration

Final Thought

More so than any time in history, we have a clear view of next generation technologies. Naturally, we’re still a long way from 100% clarity, but for most of the technologies listed above, the shifting tectonic plates of change can be felt around the world.

Without taking decisive action, colleges run the risk of being circumvented by new types of training systems that can meet market demands in a fraction of the time it takes traditional academia to react.

The ideas I’ve listed are a tiny fraction of what’s possible when it comes to emerging tech degrees. Should colleges stick their neck out like Colorado School of Mines and offer degrees that may not be immediately useful? Adding to that question, how many college degrees are immediately useful today?

I’d love to hear your thoughts on this topic.

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