In 1996, Artificial Intelligence (AI) theorist Eliezer Yudkowsky wrote: “Our sole responsibility is to produce something smarter than we are; any problems beyond that are not ours to solve.”

Nearly 20 years later Yudkowsky seemed to have something to say about people at the other end of the intelligence spectrum. In what he coined Moore’s Law for Mad Science, Yudkowsky stated that, “Every 18 months, the minimum IQ necessary to destroy the world drops by one point.”

Just taking a moment to give credit where credit is due, this “Law” (more of a prediction or estimation) was no doubt suggested in tongue-in-cheek deference to Gordon Moore, co-founder of Intel Corporation. Moore predicted in 1965 that the number of transistors per silicon chip would double every year, an assertion known as Moore’s Law. That prediction was still on track up until 2019 when it finally came to an end.

But with Yudkowsky, was his “Moore’s Law” a reconsideration of the optimism and positivity implied in his earlier statement? Should we seriously consider placing limits on self-learning technologies as Elon Musk has warned? At what point do AI and system intelligence become a danger because human intelligence has not advanced enough to cope with it?

Another trend that ties into Yudkowsky’s Mad Science law is the fact that, over time, we’re putting more and more information, and therefore more power, into the hands of individuals. Should we try to place limits around the distribution of information that could prove dangerous?

Thanks to the Internet, all kinds of sensitive information is available, and not just to scientists.

With a little bit of digging, complex and dangerous information is not only available, it’s dumbed down for the rest of us, like me and you, as well as the anarchist who lives down the road, and the delusional schizophrenic working in their garage laboratory-workshop. After all, mad science information is for mad scientists, right?

So, yes, we need to be vigilant. We need to be aware that there are countless, remarkably detailed “how-to” articles available deep online about how to cause chaos or trigger widespread death.

But do we really have the ability to destroy the world? Releasing a more viral version of COVID-19 may be one approach. We’ve already seen some very entertaining television shows and movies have been built around foiling plots to destroy all or parts of the world.

What about nuclear weapons? We seem still to be in a kind of Cold War environment where wars between superpowers are fought regionally, often by proxies, using conventional weapons and armory. Outright utilization of nuclear mega-weapons by one of the superpowers would certainly trigger mutually assured destruction on a widespread or, yes, possibly global scale.

Our biggest concern, though, shouldn’t be that a rogue nation will choose to act, but that a rogue actor will be able to gain access to them, or reframe access to them through a sophisticated ransom scenario.

While the age of heavy military guns and hardware is ending, a new age of bio, cyber, and propaganda wars is just beginning. The concept of imminent risk and menacing danger is being reframed around non-intuitive, non-visible, and non-obvious threats related to the infrastructure and systems all around us.

Power grids, air traffic control systems, Internet misinformation and rumors, as well as medical labs all have technology-based points of entry.

As these systems become automated and smarter, as per Yudkowsky first statement, often weak links are discovered by hackers (granted, they’re smart people) and shared with others who don’t need to figure things out for themselves, leading to Yudkowsky second statement, by simply following the devious instructions they find online.

Yudkowsky is clearly someone that will make you think! That said, I would tie his two statements together into, “Our sole responsibility is to produce something smarter than we are, but let’s make sure the keys are locked away from those without a legitimate need to know.”

Otherwise yes, it will eventually become rather simple to destroy the world.

Podcast College has the potential to short circuit the path to a newer you!

What if getting a college degree involved little more than listening to podcasts and taking tests?

Podcasts can be squeezed into every crack in every day, like riding in a car, working out at the gym, going on a bike ride, or waiting at the doctors office. Most college classes cannot!

Colleges and higher ed are about to be transformed and it is in this transformation where amazing new opportunities will spring to life.

At the moment, we don’t know if the disruption will come from AI, videos, podcasts, mentor networks, or something else. But ten years from now, the process for getting a college degree, learning new skills, or simply brushing up on your latest hobby techniques will look vastly different than it does today.

We all have our own idea of what success should look like. But our notion that college degrees are a must-have component of success is quickly eroding.

For teenagers, their heroes are people who have launched their own video games, started a band, filmed a rockumentary, created a mobile app, written a graphic novel, or won a major video game tournament. To them, the accolades and notoriety that come with this kind of experience far outweighs the tedium involved in credentialing new skills.

For others, nothing resonates quite like being involved in an authentic accomplishment-based learning experience where meaningful work is making a meaningful impact.

Experience trumps diplomas every day of the week.

That said, we still have a need for credentialing.

Our Mandate for Humanity

One of our underlying mandates has been the transfer of knowledge from one generation to the next. And no, we’ve never been very good at it.

History is filled with stories of invading armies determined to wipe out every possible remnant of ancestral tribes, races, cultures, and ethnicities, and in doing so, many of the inventions, discoveries, and research projects that have brought us to this wobbly point in history have been lost along the way.

Every time there has been a burning of books, destruction of libraries and museums, or dismantling of schools, our ancestors have been forced to relearn, rediscover, and reinvent each of these pillars of accomplishment one sand pebble at a time.

Simply put, it is our ability to look back at everything we’ve learned, discovered, invented, and imagined in the past that helps jumpstart every new generation of young people by placing the starting blocks on a much higher plain of understanding. At least that’s the way it’s supposed to work.

Over the years we’ve developed a number of tools for doing this including libraries, books, museums, colleges, and more recently countless forms of digital archive sites including YouTube, Facebook, LinkedIn, and Instagram.

Until recently, the greatest responsibility for this generational transfer of knowledge has fallen on colleges.

In much the same way books have evolved into a convenient way of packaging information, college courses have become the default form of packaging learning units.

Yet, anyone who’s written a book knows how onerous and demanding the process can be. And creating a curriculum for a college course is equally demanding.

Of course we’ve seen a number of shortcut processes come out of the woodwork, but for truly meaningful books and courses, it’s still a painful process.

More recently, however, the online digital world has given us a completely new set of tools to work with, and the reinvention of learning processes will send shockwaves of disruption through our existing school systems.

Listening to a podcast becomes an intensely personal experience!

Enter the Podcast Universe

At the DaVinci Institute, we hosted our first Podcast Bootcamp in 2005, shortly after podcasting itself was invented.

Podcasting was first created in 2004 by former MTV video jockey Adam Curry and software developer Dave Winer. Curry wrote a program called iPodder that enabled him to automatically download Internet radio broadcasts to his iPod. Several developers improved upon his idea, and podcasting was officially born. Curry now hosts a show called The Daily Source Code, which is still one of the most popular podcasts on the Internet.

The name itself came from the idea of loading audio files onto an Apple iPod.

I remember how our Podcast Bootcamp turned into a bit of a geek-fest because the whole process of recording and loading audio files online was still in the prehistoric, cutting-edge early years.

Today, most of the rough edges are gone and podcasting itself has become a massively fast growing and hugely popular medium.

Currently there are over 850,000 podcasts featuring over 30 million episodes. And these numbers are moving up a steep growth curve with projections that we’ll break the million podcast barrier later this year.

51% of people in the US have listened to podcasts, and the audiences are split into 56% men and 44% women.

Most of the growth in podcasting started in 2014, with 157% growth since then, when smartphones started to become more podcast-friendly.

Right now, podcasting is free from government regulation. Podcasters don’t need to buy a license to broadcast their programming, as radio stations do, and they don’t need to conform to the Federal Communication Commission’s broadcast decency regulations. That means anything goes — from four-letter words to sexually explicit content. Copyright law does apply to podcasting, though. Podcasters can copyright or license their work, and Creative Commons is just one online resource for copyrights and licenses.

Testing will be a key component of every future learning system!

Inventing Podcast College

What if college lectures, with a single professor discussing a topic, were replaced with 2, 3, or 4 very bright people discussing the same subject matter on a podcast?

Podcast courses already exist, and many colleges already have their own podcast course offerings, but so far no one has managed to pull together an organically scalable YouTube-for-podcast-courses site with testing and revenue sharing that offers legitimate credentialing for next generation learners.

Here are some of the components that could make it a rapidly scalable online service:

• Audio and Video

  Since there are no one-size-fits-all forms of learning, podcasts will include both audio and video.

• AI-Driven Recommendation Engine

  Finding good podcasts is easy. But finding great ones is hard. Over time an AI recommendation engine will learn your interests, quirkiness, idiosyncrasies, and personal preferences.

• Industry-Driven Certification Standards

  Every profession, personal skill, or area of learning has logical points where experts in that field would consider the necessary learning to be sufficiently complete. But every profession or skill is different.

• Instant Language Translatio

  Switching from French to English to Mandarin should be automatic based on your profile.

• Official Record Keeping System

  Building a system with impeccable integrity means that the system for archiving the accomplishments of every participant must be secure, private, and managed by an organization with impeccable credentials. While many people will think that a government-run archive is the best solution, the best possible record-keeping system will be one that transcends governmental boundary lines.

• Participative Wealth Pricing

  The revenue stream generated by each courseware unit will be divided between the courseware producer, distribution company, transaction company, system operations company, and the official record keeping system. Maybe more. Courseware prices need to be kept low to make courseware accessible to anyone interested in learning.

• Multi-Dimensional Tagging Engine

  Tagging will help train the AI. Much of the system usability will be driven by multi-dimensional tagging engines that will include:

  • Personal Rating Tags

    Upon completion, each student will be asked to rate the pod-course. Courses will be graded on accuracy, quality of the learning experience, ease of use, and overall effectiveness.

  • Quality Assessment

    Listeners will up-vote and down-vote podcasts so the best-of-the-best will rise to the top.

  • Truth Assessment

    Virtually every aspect of society has their own version of the ‘truth’ – religious truths, scientific truths, legal truths, etc. For this reason, individual groups will place their tags of approval or disapproval on courses. For example, organizations like the American Chemical Society, People for the Ethical Treatment of Animals, Focus on the Family, American Civil Liberties Union, National Rifle Association, National Education Association, or the Catholic Church can all review the new courseware that is being introduced and make a determination as to whether or not it meets their criteria.

  • Taxonomy Tags

    Invariably, courseware topics will be understood differently by every student. For this reason, allowing students to place descriptor tags on all completed courses will create the necessary taxonomy markers so an AI recommendation engine can find it.

  • Prerequisite & Post-Requisite Tags

    Knowledge builds on knowledge. As an example, students cannot study literature until they know how to read, and they cannot study computer programming until they know math and algebra. So courses have to happen sequentially, and it becomes imperative to develop a system for sequencing courses based on the order of which learning must take place.

  • Comment Tags

    Comment sections will allow students to voice their own thoughts on each course.

Podcast college has the potential to become the most liberating shift in learning in all history!

Launching the Business of “You”

How many traditional schools are currently prepping students to be “freelancer-ready?” In a word – none. It’s simply not happening.

Instead, the hard transition from student grunt to skilled worker is occurring in radically different ways – through friends, through trial and error, and through existing project teams.

Mentorship is quickly becoming the new classroom.

When LinkedIn founder Reid Hoffman said, “You need to think and act like you’re running a start-up of ‘you’,” he’s referring to your own career.

Every new free agent that enters the project-to-project job world quickly realizes that their growing lists of questions simply don’t have textbook answers. They have to find their own answers, and the quickest way is through peer groups and mentors.

Living in the U.S., the country with the highest educated waitresses and bartenders in the world, an increasingly vocal underground feels they’ve been lied to. Academic credentials no longer live up to the promise implied with every new student loan that’s being applied for.

That’s one of the reasons coworking is becoming so trendy; they’re looking for a better network.

Your next career move may only be a few podcasts away!

Final Thoughts

The best schooling occurs when you have a project where you can instantly apply the things you learned.

Writing a book, receiving a patent, or starting a business are all noteworthy symbols of achievement in today’s world. But being the author of a book that sells 50,000 copies, or inventing a product that a million people buy, or building a business that grosses over $10 million in annual sales are all significant accomplishments far more meaningful than their academic equivalents.

Most of what happens in today’s universities is based on “symbols of achievement,” not actual accomplishments.

Academic competitions pit students against each other to produce results that best match their teacher’s expectations. Only rarely will they produce anything noteworthy.

Completing a class is nothing more than a symbol of achievement. Similarly, completing many classes and receiving a diploma is noteworthy, but still only a distant cousin to a real accomplishment.

No, this doesn’t mean that classroom training has no value. But, what we achieve in a classroom is at least one level of abstraction removed from a real-world accomplishment.

In the business world, it’s only an accomplishment if someone is willing to pay for it.

The global marketplace is not looking for people who have learned how to be great students. It wants results.

Podcast College has the potential to short circuit the path to a newer you!

The world is currently undergoing a massive demographic shift, with over half of all new born babies born in six countries – Angola, Congo, Ethiopia, Nigeria, Tanzania, and Pakistan.

First world countries, with their ambitious lifestyles are far less interested in the labor intensive, burdensome, and expensive path of child-rearing, and with easy access to birth control, it often becomes an obvious no!

Modern pressures on highways, power, water, and waste reinforce a belief that population growth is a problem. Blamed for crowded restaurants, brownouts, urban sprawl and other irritants of modern life, the popular refrain is that we have too many people with too few resources.

While some of us may conjure up images of huge populations of starving people left to fend for themselves in the squalors of war-torn villages, the true human potential is a radically different story.

Every problem we face today has a potential solution ready to percolate to the top in the mind of a soon-to-be-born child somewhere in the world. Location shouldn’t matter.

The future of the world rests in the minds of our baby Einstein’s!

Asking the toughest of tough questions

If we step back and take a macro view of our world and the myriad of trends fashioning it, I find the most interesting questions coming from the following unanswerable questions that no one seems to be asking.

1. How many Einstein and Mozart-level geniuses are currently being born in the midst of every million newborns?

This is a question we should be asking every day? But we don’t even have a well-accepted definition for what constitutes a genius. Every modern-day Picasso, Galileo, Beethoven, Van Gogh, Archimedes, and DaVinci will require a radically different measuring stick to assess the depth and value of their true talent.

2. How many genius-level babies have been born throughout history?

Sadly, we have no existing way of measuring genius-potential when a baby is born. Realistically, we should be tracking it back to the point of conception since many factors surrounding a pregnancy will also determine later life potential.

3. With the right set of circumstances, could we raise the percentage of genius births to as high as 20%, 30% or even 50%?

Since much of our potential in life stems from the struggles, setbacks, and rigors of our upbringing, it’s hard to imagine creating a set of optimal circumstances and what those results might look like.

4. Could every single live birth produce a true genius with the right stimulation, training, and effort?

Is every baby conceived with genius potential, and everything that happens in life simply a subtraction process from day-one perfection? In a perfect world, how close could we come to 100%?

5. Wouldn’t our first step be to create geniuses who can first answer these questions, before we can raise the bar for the rest of humanity?

If there are people currently working on this set of problems, I’m not aware of them. Somewhere in this line of thinking would appear to be an approach that can unlock an elevated plateau for all humanity. Shouldn’t this be our top priority for the entire world?

6. How many answers lie in the vast number of children that are currently not being born?

How many cures for cancer, hemorrhagic fever, diabetes, meningitis, rabies, smallpox, plague, HIV/AIDS, cholera, tuberculosis, and ebola never got discovered because the people with answers were never born?

7. Will the enormous value of the few outweigh the problems of the many?

Are people the problem or the solution? Can we create better and more consistent geniuses in smaller batches? It’s easy to get trapped into using the age-old top-down approach to thinking this through. But I’m fairly certain that we will never find the answers simply by having someone crown themselves king and demanding we see the world through their eyes.

8. Are we even smart enough to ask the right questions?

That’s an easy no! This set of questions is simply a starting point for far more sophisticated questions that are sure to follow. The real goal should be finding the right questions before we even think about answers!

9. Will emerging technologies like AI and quantum computing enable us to achieve better answers?

Over the coming years we will undoubtedly be working with promising technologies capable of boosting our genius-quotient. One question I love to ask is, “How will the world change when we can focus a million times more computing power on a particular problem?”

10. Do we live in an overpopulated world or an under-populated universe?

As humans, do we have a mandate to colonize other worlds? Many people believe this to be true. The number of humans that currently live in other corners of the universe equals zero. Different gravities, food supplies, atmospheric compositions, radiation levels, and a myriad of other conditions means that we will never encounter other “humans” as we explore the universe, and the likelihood of encountering “human-like” beings is extremely remote. Are we then destined to become the colonizers of new worlds, and who are the geniuses that will take us there?

David Sarnoff, the “Robber Baron” CEO of RCA

The David Sarnoff Story

Born in 1891, David Sarnoff, best know for his years as the heavy-handed CEO of RCA left a trail of technological carnage in his wake as he went to great lengths to cement his grasp on power in the broadcast industry.

While the famed TV inventor, Philo Farnsworth patented his first television in 1927, it would be decades of court battles with Sarnoff and RCA that delayed the introduction of television for over 25 years. At one point Sarnoff even claimed he was the inventor of television, reducing Farnsworth to a fraction of his boyhood genius in the process.

A similar story unfolded when Edwin Armstrong invented FM radio and pitched it to Sarnoff in 1948. After seven years of exhaustive court battles, Armstrong simply gave up and jumped out of his 13th floor apartment, committing suicide in 1954.

Sarnoff was a ruthless businessman and master manipulator who would go to great lengths to preserve his base of power. To be sure, every industry has a puppet-master like David Sarnoff controlling the agenda. The question we should all be asking is, “Who is the David Sarnoff of EdTech, FinTech, and HealthTech, preventing our emerging young geniuses from rising to the top?”

Clearly we have many in Africa, Asia, South America and the rest of the world who are more interested in exploiting talented people rather than letting their genius, ingenuity, and brilliance rise to the top.

History shows we’ve done a terrible job of protecting our most talented thinkers.

In this context, Sarnoff is an all-too-real symbol of the extreme challenges that will need to be overcome to achieve the optimal genius density we’ll need in the future.

Picasso in his Paris studio!

Final Thoughts

Counter to our historic approaches, relying on serendipity is not a good plan. Doing nothing is also not an option!

The survival of the human species is dependent upon our ability to preserve the best and the brightest.

Behind every advancement, new threats are lurking. Our challenges ahead will be far more demanding. Abilities of the past are no longer sufficient to solve the problems of the future. Global catastrophes are poised and waiting to make their appearance.

Extreme problems require extreme solutions.

We’ve all heard the stories and seen the movies of how famines, mounting deaths, social collapse, and mass migrations will ignite elevated forms of global conflict as civilizations crumbles.

We can no longer allow warlords, drug-lords, and human traffickers to reduce our polymaths and prodigies to soldiers, slaves, and servants. Nor can we let the David Sarnoffs, Joseph Stalins, Adolph Hitlers, Pol Pots, and Genghis Khans maim, kill, and destroy the billions of young men and women who should be filling our history books instead of them.

In much the same way that we can’t pay more bills with less money, we can’t solve greater problems with less talent. A planet with a shrinking population will suffer from entirely new kinds of problems, such as ghost town syndrome, neighborhood collapse disorder, community fragmentation, and social panic leading to fractured economies and large-scale financial failures.

We no longer have the luxury of allowing only a tiny fraction of our offspring to fight the one-in-a-billion odds to maybe find a seat on the world stage of thinkers, designers, and influencers.

If we get past the not-so-enlightened thinking that “people are the problem,” and move into a more realistic view that “people are the solution,” we can begin having more meaningful conversations.

And yes, many of our future scientists, engineers, entrepreneurs, and world leaders are being born in Angola, Congo, Ethiopia, Nigeria, Tanzania, and Pakistan.

Systems of the past are simply not good enough for the future. So the question remains, “how do we build the durable, survivable, sustainable structures needed in the future?”

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

Every time we talk to Alexa, Siri, Google, or Cortana, we are building the brains of the robot.

Whenever we speak to these devices, we are imparting tiny pieces of human intelligence, and over time, with the right kind of AI learning software, it will be possible to build the kind of foundational base of knowledge needed to operate our robots in the future.

Granted, we are still at the “chisel-on-stone writing” stage of this transformation, but our verbal exchanges are fueling the early reservoirs of human intelligence that will be needed to power the brains of our robots over the coming decades.

The robots, I’m referring to, may be drones, driverless cars, or actual robots, but an incoming stream of intelligence is what will be needed to separate the blind, order-following robots of the past from the emotionally-perceptive, multisensory bots that will be a common site in our future.

In many situations, the robot itself will begin to disappear, and over time will morph into forms of automation that we no longer consider to be associated with robotics.

How will we know if future robots are making good decisions?

The Ethical Robot Dilemma

How much authority will future bots have? Will they be given the authority to keep alcohol away from alcoholics, cigarettes away from minors, and turn off devices when kids should be doing their homework?

Will the same bots that serve as your personal trainer and image consultant also be given authority to change your diet, schedule doctor appointments, and arrange social engagements?

Will they be given authority to sign for certified mail, to fill a prescription, hire an exterminator, or care for a baby?

Could we also go down the dark side of robotics and direct them to terminate a dictator, rebel leader, or anyone else who may stand in our way?

Will bots be used as the intermediaries in drug deals, human trafficking, and arms shipments to keep the principals at a safe distance?

Will autonomous bots have their own bank accounts and also be required to pay taxes? Could community bots be organized like a foundation and evolve into the biggest tax haven of all times?

In the future, will you allow a robot to give you a haircut? How will you know the good bots from the bad ones?

Isaac Asimov’s “Three Laws of Robotics”

The thinking behind Asimov’s Three Laws of Robotics first started taking form in his 1942 short story “Runaround,” but he had mentioned some of his thinking in a few earlier stories.

In his “Handbook of Robotics” published in 1958, Asimov’s “Three Laws of Robotics” became official:

1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
2. A robot must obey orders given it by human beings except where such orders would conflict with the First Law.
3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

While the laws seemed very visionary and formed a cultural meme around the ethics needed for the coming age of automation, they are simply not adequate for the nuanced capabilities and behaviors we are beginning to see in today’s devices.

At the same time, Asimov was driving the first stake in the ground for machine ethics, a field that hadn’t even been invented yet, and should be commended for his farsighted approach to the human-machine relationships that we will be wrestling with for decades to come.

Our relationship with robots is changing. How will we know if they truly care?

Failsafe Mechanisms

If machines are using our conversations to add to the overall intelligence of robots in the future, they will also need to protect our privacy.

If a robot knows everything about me, then it will know our credit cards, bank accounts, and passwords. That level of intrusion into our lives becomes a very dicey issue because too much transparency means we lose our ability to own things, and ownership is a foundational principle upon which our society works.

Does the protection of privacy has become a “new law” required in every future robot operating systems?

At the same time our robots need to understand our preferences. What kind of products do we normally buy? What food do we like, who are our family members, friends, pets, what brands do we prefer, what forms of entertainment do we enjoy? Every piece of information helps streamline our transactions and reduces the amount of time invested in every accomplishment.

If we send our robot to the store to buy groceries, how will we empower it to select the right products?

The Economics of Automation

Our economy is based on people. Humans are the buying entities, the connectors, the decision-makers, and the trade partners that make our economy work.

Without humans there can be no economy.

Generally speaking, when a person buys tools, it increases their capability, and by extension, increases their value as an economic entity.

When a person buys a computer and becomes proficient at using it, this added piece of digitization increases their capabilities, their earning power, and their sphere of influence as a consumer. In general, people with computers earn and spend more than people without computers.

Similarly, people who own cars, homes, and businesses tend to earn and spend more than people without them. Ownership and control becomes part of our personal toolbox, a toolbox that gives us additional capabilities and thereby adds to our economic contribution.

Since the capabilities granted by owning a computer connected to the Internet can be far more scalable than owning a car or home, its influence upon economic theory has been largely underestimated.

We will encounter similar underestimations as we combine the scalability of Internet-connected automation to the capabilities of a person in the years ahead.

How long before your best friend is a robot?

Final Thoughts

Competing WITH robots is far different than competing AGAINST robots. When we add machine skills to the resume of an individual we end up with a far different equation.

So the coming decades will be far less about humans competing against machines and far more about how we can leverage them to our advantage.

For this reason, it’s imperative that the tech companies formulating these future “brains” get it right. We will need to trust our machines, and trust the decisions they make.

We are still a long way from creating Hollywood style robots with an emotional mind capable of making value judgments that we feel comfortable with. But we are very close to leveraging machine capabilities in far more interesting ways.

Machine-based automation will revolutionize our world every bit as much as our computers already have.

What cannot be lost in this discussion is the need for a rapid transitioning skill base where we quickly identify the gaps and train people to fill them.

Machines can become our greatest asset or our greatest liability. It’s up to us to decide which will dominate.

If you think you understand people, you’re not really paying attention.

At a past DaVinci Institute mastermind group we tackled the question, “Is the intelligence of nature greater than the intelligence of humans?”

After pondering this question, the responses were a mixture of “there is no intelligence in nature,” and “nature is not an entity with a singular intelligence.”

Each one of us is part of nature and the intelligence we add is critical to the overall ecosystem.

Logically this raises several questions about an overarching intelligence, and we’ll get to that later. But, exactly what is this thing we call nature, and why do we hold it in such high regard?

One of my pet peeves with the food industry has been the association of “all natural” with “good for you.”

Not everything found in nature is good for you. Things like poison ivy, hemlock, chrysanthemums, and rhododendrons are poisonous. Nature’s extreme weather events – tornadoes, hurricanes, and earthquakes – are massively destructive. Viruses and diseases can also be considered “natural.”

Even though it fails the logic test in spectacular fashion, we somehow continue to fall into the trap that nature has it right.

No, nature didn’t have it right when it came to the dinosaurs, the dodo bird, or the saber tooth tiger. Nor did it have it right for the Aztecs, Incas, or the Anasazi.

That said, we may have some fascinating clues as to why these things that don’t make sense continue to happen, and the clue comes in the form of a question that is impossible to answer.

The question: Why is there an exception to every rule?

Why does anything exist?

Call me a skeptic, but there is no place in my mind that I can rationalize the random coming together of bizarre factors to create the universe as it’s described in all the science text books.

Out of nothing, came something. Color me unconvinced!

How does any of this make sense? Every step used to describe the chronology of the universe fails the “why test.” Why did that happen, and why does anything exist.

Keep in mind; a description is not an explanation. And repeating these unproved and unprovable theories enough times does not make them true.

What we have been witnessing is the creation of multiple support theories to prop up the original unprovable theories, with literally billions of textbooks published to make it look like a given fact, when someday everyone will refer back to it and laugh at how it masqueraded as “big science.”

We still don’t have a clue about what’s in the center of the earth, so why do we think we can say with any level of certainty how the universe was created.

Gödel’s incompleteness theorem

In 1931, Kurt Gödel published his famous incompleteness theorem. They showed that in any mathematical system, there are certain questions that cannot be answered. As a result, mathematicians have come to grips with their inability to understand the universe.

It’s not that Gödel’s theorems super difficult, rather, they’re simply unknowable. His two theorems state:

1. No consistent system of axioms whose theorems can be listed by an effective procedure (such as an algorithm) is capable of proving all truths about the arithmetic of the natural numbers.
2. If a system is sufficiently complicated, it cannot be both consistent and complete.

Beyond what he had originally proposed, Gödel’s theorems also confirm the hypothesis that there is an exception to every rule, saying it’s impossible to find a complete and consistent set of axioms for all mathematics.

Approaching this topic a bit differently, in 1936 Alfred Tarski proposed his Undefinability Theorem stating that truth is officially undefinable.

As humans, we are officially inconsistent, undefinable, and incomplete. As a result, there are certain things in science we can’t know. They are the exceptions to our rules of understandability.

Without problems, there would be no work!

How can a flawed system work better?

If I were to design the operating system for humanity, logically I’d want everything to work as planned. I’d want consistent relationships between cause and affect.

In fact, I would want every scientific law to be irrefutable, to work perfectly, every time. And yet it doesn’t!

We live in a world where there is a flaw in every theory, imperfections in every design, and a continual degradation in every person, object, and system over time.

There is an exception to every rule.

Nothing is permanent, nothing is perfect, and nothing is 100% reliable. We all intuitively know this already, and yet we are constantly striving to make things as close to permanent, perfect, and reliable as possible.

But it’s not the fact that it’s unachievable that’s important, it’s why our overarching design for humanity works this way – that’s what I find most intriguing.

For some reason, flawed humans work better with flawed designs and flawed systems. But why?

Everything fails the sensibleness test, unless you assume there is a higher form of logic at play.

The forces of gravity, speed of light, and quantum theory don’t have their flaws just because gravity, light, and the quantum guy were sitting around having a beer one night saying, “Hey, I think we should mess with people’s heads and create a bunch of imperfections!”

No indeed, clearly there are bigger things in the works. This is not intended to be a religious argument; rather it’s an argument about the known vs. the unknown, and the preponderance of garbage theories that invariably expand to fill the void.

We are the center of a much bigger story!

Nature is not human-centric

Nature is neither our friend, nor our enemy.

If something is considered part of nature, it generally refers to the phenomena of the physical world, and also to life in general. It ranges in scale from the subatomic to the cosmic.

But it’s critical to frame our thinking around the fact that nature is not human-centric. It doesn’t have our best interest at heart.

There are no ethics or morality in nature. Morality comes from our values and nature doesn’t concern itself with any human-centered tenets or beliefs.

“If we continue to use ‘nature’ as our moral compass, we will invariably get it wrong. Nature doesn’t care.”

Final Thoughts

As we begin to deal with the complex issues ahead, I find my role and duty as a futurist changing. At times I’m looking at the future through the eyes of a philosopher, ethicist, and truth seeker even though “truth” has become such a murky issue in the increasingly squishy fields of science and physics.

Much like Schrodinger’s cat, truth is never there when you need it.

Understanding how the future unfolds will require accounting for difficult decisions along the way. These decisions become key turning points in human history. The ethics and morality of ages past will have little bearing on many issues we face in the future.

That said, I would love to hear your thoughts. Unlike most of the topics I cover, this has been more of a personal rant, so please feel free to help set the record straight.

I’ve been closely watching the debate on artificial intelligence with people like Rodney Brooks saying it’s only a tool, and others like Elon Musk and Stephen Hawking giving bone chilling warnings of how it could lead to the destruction of all humanity.

As I was pondering these differing points of view, it occurred to me that we currently don’t have any real way of measuring the potency of AI. How will we ever know there is a real threat of danger if we have no way of measuring it?

For this reason, I’d like to propose the creation of a standard for measuring AI based on “1 Human Intelligence Unit.”

Similar, in some respects, to James Watt’s ingenious way of calculating horsepower as a way of gauging the mechanical muscle behind his ever improving steam engines, I’d like to make a crude attempt at quantifying, in numerical terms, the influence of 1 Human Intelligence Unit (HIU).

Since horsepower is a rather one dimensional measure of force, and human intelligence is a complex, multidimensional combination of personal attributes that include thinking, reasoning, determination, motivation, emotional values, memories, fears, and frailty, the simple notion of quantifying human brainpower quickly mushroomed into one of those “infinity plus one” questions where the answer has become more of a philosophical debate rather than something we could assign a meaningful integer to.

Over the past few weeks I found myself immersed in this quandary, looking for a simple but eloquent approach vector for solving the 1 HIU riddle.

To put this into perspective, imagine a scene 20 years from now where you are walking into your local robot store to compare the latest models before you buy one for your home. The three models you’re most interested in have tags listing their HIUs as 4.6, 12.4, and 24.0 respectively.

Depending on whether you’ll use your robot to simply follow orders or to become a well-rounded sparing partner to debate the issues of the day, the HIU rating will become a hugely valuable tool in determining which one to choose.

For this reason, I’d like to take you along on my personal journey to solve for “infinity plus one” in the area of human intelligence, and the startling conclusions that are likely to disrupt all your thinking.

History of Horsepower

When James Watt worked on his second-generation steam engines, it occurred to him that he needed a simple method for conveying the power of his devices, and it needed to be something everyone could relate to.

After watching horses turn the giant 24-foot wheel at a local mill, Watt determined that a horse could turn the wheel 144 revolutions in an hour, or 2.4 times a minute. With some quick calculations, he concluded the average horse could pull with a force of 180 pounds, which translates into 33,000 ft-lb per minute, the number behind every unit of horsepower today.

Even though horses couldn’t maintain this level of effort over a very long period of time, the horsepower comparison caught on and became a hugely valuable tool in marketing his engines.

Needless to say, the quantification of effort exerted by a horse is far simpler than assigning value to the complex nature of human intellect.

A simple approach starts with one of mankind’s greatest accomplishments, the Apollo Moon Landing, and dividing it by the number of people it took to accomplish it, and we could say that it took exactly X number of HIUs to complete the mission. But this approach is far too simplistic to have any real value.

What exactly would we be measuring, computational skills? How could a measure like this have any value in comparing say a robot doing laundry, a self-driving car, or Watson playing Jeopardy?

Last year I wrote a column introducing the concept of “synaptical currency” as a way of quantifying mental effort and creating a better way of valuing a person’s contribution to a project based on a comparison of synapse firings over a given period of time.

According to neuroscientist Astra Bryant, a rough number for neural signal transmissions in the average brain ranges from 86 billion to 17.2 trillion actions per second, with a person in a deep meditative state being on the low end and someone experiencing a full blown, category-five epiphany on the high end.

Even though having an HIU rating system based on the average number of decisions or calculations a person can make in an hour would have some merit, it represents little more than a horsepower rating for the brain, loosing intangibles like passion, ingenuity, and imagination in the process.

Being Human

Humans are odd creatures. We have exceptions for every rule, we value intangible things based on our emotional connection to them, and our greatest strength is flawed logic.

Yet in the midst of our love dance with imperfection where we find ourselves grabbing on to clumsy-footed conundrums just to maintain some semblance of poise, we remain the dominant higher order species in the universe.

Certainly some will argue with that assessment, and we know little of what exists beyond our own planet, but here’s the key.

What we lack as individuals, we make up for as a whole.

One person’s deficiencies are counterbalanced by another person’s over-adequacies. Individually we’re all failures, but together we each represent the pixels on life’s great masterpiece.

Wherever we find insufficiencies, we create dependencies to help fill the gap, and every “need” produces movement.

Using this line of thinking, the human race does not exist as self-sufficient organisms. We all pride ourselves as being rugged individualists, yet we have little chance of surviving without each other.

Even though we are constantly fighting to become well-balanced people, the greatest people throughout history, the people most lauded as heroes, were highly unbalanced individuals. They simply capitalized on their strengths and downplayed their weaknesses.

If humans were wheels, we would all be rolling around with lumpy flat sides and eccentric weight distribution. But if 1,000 of these defective wheels were placed side-by-side on the same axil, the entire set would roll smoothly.

This becomes a critical piece of a much bigger equation because every AI unit we’re hoping to create is just the opposite, complete and survivable on its own. Naturally this raises a number of philosophical questions:

1. How can flawed humans possibly create un-flawed AI?
2. Is making the so-called “perfect” AI really optimal?
3. Will AI become the great compensator for human deficiencies?
4. Does AI eventually replace our need for other people?

The Button Box Theory

One theory often discussed in AI circles is the button box theory. If a computer were to be programmed to “feel rewarded” by having a button pressed every time it completed a task, eventually the computer would search for more efficient ways to receive the reward.

First it would look for ways to circumvent the need for accomplishing tasks and figure out ways to automate the button pushing. Eventually it would look for ways to remove threats to the button, including the programmer who has the power to unplug things altogether. Since computers cannot be reasoned with, it is believed that the machines would eventually rise up to battle humans.

This scenario is key to many dark movie plots where intelligent machines begin to battle against humanity in the future. Yet it is filled with assumptive flaws that these machines will somehow learn to take initiative, and their interests will instantly blind them to any other interests in the world.

A Few Startling Conclusions

Virtually every advancement in society is focused on the idea of gaining more control.

We all know what it’s like to get blindsided by bad serendipity, and we don’t like it. Our struggle for control is a coping reaction for life’s worst moments. If only we could have more control, nothing bad would ever happen to us.

Artificial intelligence promises to solve this dilemma. We not only create avoidance mechanisms for every danger, but fixes for every problem, and self-sufficiency on a grand scale.

Eventually we become stand-alone organisms, content in our surroundings, wielding off-the-chart levels of intelligence and capabilities exceeding our wildest imagination.

However, this is where the whole scenario begins to break down.

Self-sufficiency will lead to isolation and our need for each other will begin to vanish. Without needs and dependencies, there is no movement. And without the drive for fixing every insufficiency, our sense of purpose begins to vanish.

Being super intelligent is meaningless if there is nothing to apply the intelligence to. Much like a perpetual motion machine that never gets used, there’s little purpose for its existence.

For this reason, it becomes easy for me to predict that all AI will eventually fail. It will either fail from its imperfection or fail from its perfection, but over time it will always fail.

However, just because it’s destined to fail doesn’t mean we shouldn’t be pursuing these goals. As we journey down this path we will be creating some amazingly useful applications.

Narrow AI applications will thrive in countless ways, and even general AI will create immeasurable benefits over the coming decades. But it is delusional to think that solving all problems will be a good thing.

Final Thoughts

Sometimes our best intentions reveal themselves as little more than a mirage to help guide us to an area we never intended to go.

I started off this column talking about a new unit of measure – one human intelligence unit (1 HIU). But along the way, it has become clear that human intelligence and artificial intelligence exist on different planes… or do they?

Without dependencies there can be no human intelligence. Something else perhaps, but it won’t be human.

There’s something oddly perfect about being imperfect.

When it comes to measuring the potential danger of AI, leveraging it for good can be as dangerous as leveraging it for evil.

Will we eventually have some form of HIUs or will we have to know more to answer this question? Perhaps it’s just my way of waging a personal protest against perfection, but like a train that has yet to leave the station, this is a movement still decades away.

As I close out this discussion, I’d love to hear your thoughts. Are the doubts and fears that cloud my assessment as real as I imagine them, or simply delusional thinking on my part?

By Futurist Thomas Frey

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