Robot-proof and experiential education
Robot-proof and experiential education are both terms that are bound to each other.
If you don’t want to read, just watch the video:
We wanted to confront our ideas with what is “hot” on the market in education.
Robot – Proof: Higher Education in the Age of Artificial Intelligence was the new title we checked over the holidays.
We picked up two major concepts that in our opinion determined the character of this book:
- Robot-proof / ness
- Experiential education
and created this title…
Robot-proof and experiential education
Here’s the review as well as the hint what kind of education you should start acquiring in 2019.
Robot – Proof
Joseph E. Aoun is a passionate Professor of linguistics and innovator of higher education.
It’s very thrilling to see when we have right people on the right spots – passionate and aware about future of higher – education…
In his book, he gives a good debunk through history, what is the purpose of education and to the most part what is the purpose of higher education – the universities.
Fears of Robotic Future as he plots are not new.
“Machines have been replacing human labor ever since of flint proved to be sharper than a fingernail.”
Technologies simply increase our capacity for labor and thus the nature of labor changes. It’s simple as that. And the civilizations are hungry for more labor outputs, productivity, and energy that seemingly enables them to move forward. The question of “progress” is still relevant, but somehow we cannot stop it.
Some cultures were so enrooted with their old traditions that they repelled the change apriori. But, such cultures, like that of Native Americans were not saved from the events that occurred nearby.
On the planet of 7 billion people it’s either embrace it or be changed by it – either you change the world a little bit or the world changes you.
The fears of machine learning (automation) and artificial intelligence are almost ubiquitous.
I believe it’s right there after the fear of terrorism. The pictures of despair that losing a job can bring are tangible and very moving.
Where is A.I. actually at now and how troubled should we be?
We tried to summarize current knowledge and opinions we have on this topic here:
The fact is computers outperform us in many disciplines and sterile, repetitive jobs are doomed to vanish.
On the other hand, the replica of the human brain functioning is far from complete – even optimists must count with decades to come.
Let’s get back to education.
The engine of progress
We can argue with an academician what is the reason for the socio-economic and technological progress of mankind.
We, at Inex, would start with an undefeatable quest of human nature to explore and thrive.
To Joseph Aoun it is undoubtedly science and higher – education.
Agreed, although incomplete, we let go…
It is a fact that in 1850s, the United States was mostly rural, agrarian, and unlearned country.
In 2019 it is the country with 8 out of 10 best higher education institutions and the country that attracts the best talent from all around the world. That along with international monetary system on its side mixed up with supreme military strength are the basis for world’s leading position – even though the international relations are moving forward to multipolarity.
It’s complex, but universities play a humongous role there.
Joseph Aoun gets into details of the role of higher education institutions in the economic and cultural development and he backs it up with solid data.
Here occurs one fundamental question from us and this is:
Who is influenced here? Do universities influence societies or is it the opposite way around?
The simplest answer would be the influential lines go vice versa.
This question deserves a meticulous and honest work on side of research.
However, universities must reflect and react upon changes present in the society and nation.
The change is the fourth industrial revolution – the upcoming of a digitalized era and the surge of lifelong learning.
If you are craving higher institutions reforms and adjustments policies, this is the book for you.
We at inex are self – oriented education propagators. Universities yes, but we believe that higher education is not the answer for vast individual needs. It might be, but we are not policymakers. Until higher education will adapt to the needs of the 21st century, there’s no time to sit back and get replaced by robots.
Education should a proprietary, crucial interest and responsibility of every individual alone. You are an architect of it as it is your life that is enhanced through it.
What has caught our attention is especially the notion of experiential learning.
Robot-proof and experiential education
There is a dichotomy of contemporary learning – two major contributions of nowadays, let’s say.
Or is this everlasting?
First is the first principle learning, popularized by Elon Musk. It’s good approach to form a productive thinking process.
First principles thinking helps you to cobble together information from different disciplines to create new ideas and innovations. You start by getting to the facts. Once you have a foundation of facts, you can make a plan to improve each little piece. This process naturally leads to exploring widely for better substitutes.
So, your thinking process may look something like this:
- An assumption is: “Growing of my business is gonna cost me a lot of money!”
Your thinking process as of first principles can go like this:
What do I need to grow my business? I need to sell products and services to more customers!
Does it have to cost a lot of money to sell to new customers? Not necessarily, but I’ll probably need access to these new customers inexpensively.
How to create a win-win deal? Sell half of my business to a larger partner with a traffic in exchange for access to that traffic – customers.
On the hand there is robot-proof and experiential education.
Experiential education is of course the education that drives from experience.
This is a very human approach to learning that is tough to replicate for machines. It is of course not impossible.
Have you heard of supervised vs unsupervised learning?
Supervised learning is when you define the clear data of what is an object, for instance, an apple. The subject, the machines are very good at this, they go and analyze terabytes of other data to determine if they match with “what is an apple” input. Machines beat us humans in this…
Unsupervised learning is when you don’t have the input data “what is an apple”. You just learn as you go, follow the patterns that could tell you what an apple might be. Machines are getting better at this, but they still struggle to determine the vast context or we should say contexts the world has to offer.
In 2011, IBM’s Watson supercomputer was the first computer to compete in the game show Jeopardy!
Even though watching Watson playing jeopardy was impressive, it was not flawless.
There were many times Watson did not sound that impressive. You can see the whole episode on Youtube.
Its biggest mistake occured in the final round of day 2. Under the “U.S. Cities” category, the clue read: “Its largest airport was named for a World War II hero; its second-largest for World War II battle.” Both humans answered correctly – “What is Chicago?” But Watson had focused on the precise wording of the clue, giving less wight to the category title. U.S. city never appeared in the phrasing, so it guessed – “What is Toronto”?
It was not that Watson was stupid in Geography. It simply just lacked context outside the exact question.
And there are myriad of these context shaping inputs that can come in place that humans have no trouble plugging into the equation, but machines struggle to.
Aoun argues that this is the future – Robot-proof and experiential education. Once humans possess patterns of knowledge they can replicate it in a more complex contexts.
Why is experiential learning effective
Robot-proof and experiential education must follow certain path. You first acquire component skills. Second, they need to be integrated into given context. And lastly they are applied.
So, step aside from academy, the theory in short – you learn a recipe, you test them by preparing many meals and then you cook it for Orlando Bloom at the Hollywood’s dinner party.
Build your concept map of knowledge. Understand your concept and propositional relations between them and apply them through different context.
In another word, keep busy in life. Say yes to many opportunities and never stop to learn.
I can almost remember my first coding job from way ago. When I first came into the company with a very limited coding knowledge I was thrown into solving of complex problems.
I thought that for the first two months or so I’d be busy with doing tutorials and learning from assignments. But, the company was basically a very skilled freelancer and some students around him.
He told me that he can’t pay for my education, he was actually screaming at me telling this.
I remember how frustrated and desperate I had been when none of my colleagues could have helped me with solving Django parler problem.
But, it was there and the work needed to be done. The kind of a thrown into the water, and learn to swim situation – that’s what it is all about.
You read information, test in tutorials, make sample apps and then most of the time you ask older colleagues and senior programmers to help you if you have a hard time.
And then you plug the shit out of it. Just iterate and be willing to spend hours in front of the screen. Hopefully, don’t forget to stretch your back along the process, because you might beat the crap out of your backbone.
Another interesting concept from Professor Aoun is the concept of Humanics.
It’s the certain set of skill – set for 21st century you definitely should get conversational in.
Robot-proof and experiential education – Humanics
In a digitized era, every employee or entrepreneur is missing out when he or she is not conversational with computers.
Maybe, this is an exaggerated statement. People are awesome when they can incorporate some level of leverage into their organized functionings. It can be automation or being a manager, that can simply say – “go to this!” statement on his subordinates.
But, even a manager is better when he has an idea what’s going on in Humanics.
Humanics are qualities:
- Technology overview – coding as in the book
- Data prowess
- Cultural adaptability, socials.
Technology overview – coding
Coding is fun and I do not see why anyone should not try to learn it – at least to some level. Proficiency in coding requires years and years of experiential learning, but to hop in and get a grasp of it – that you can do relatively quickly.
Once you understand the core syntax and can work with documentation – you search, you google, you know all that jazz.
What it’s really about is that it’s solving problems. Not only that, but solving problems efficiently once you can solve them somehow.
And that’s always a good thing.
I don’t think it’s going to make you an awesome entrepreneur, but there are many professions where you are exposed to a problem solving as in software developing industry.
Once you have a computer, it’s not expensive to learn too. Most of the tools are free and there are hundreds of courses and tutorials that can start you for zero dollars.
You can start at Codeacademy.
Then you should throw your eyes on projects like Project Euler.
Many problems there are not even code related – you don’t even need to code them. They are more like logic and math problems. Afraid of the math?
Well, that’s the point of superlearning. You might suck at it and be “afraid” now, but you do it anyway, if it fascinates you and you see the use of the subject.
Being savvy with Data
Embracing robot-proof and experiential education calls for data intelligence.
Being good or let’s say conversational with data is the new Lingua Franca of the 21st century.
Everything is data based. They (Big guys but also small ) are collecting gigantic amount of data about our behavior online, that they can transform into sound strategies that make even more money.
Who gets savvy with data, won’t have trouble to find a job and put bread on a table. They can pay you a lot of money.
Collecting and working with data is one thing, but what is exceptionally robot – proof is the context of data validated – making the sound interpretation of the data collected.
You will need some Excel, analytics and SQL skills that are just as inexpensive to obtain as coding skills mentioned above.
This guy is so awesome for introduction into Data Science and Data analyst jobs in particular, it hurts.
Check it and dedicate some time to it this year – 3 months spent on good learning.
Cultural adaptability & socials
Robots won’t be C3POs soon.
One big task for multinational companies is to find a framework for execution of common goals within teams where members come from different cultural backgrounds.
In Aoun’s book this is nicely shown how universities have been able to “Alma Mater” such conditions where even a Jew and a Muslim are eligible to live with each other at the dormitory.
Being social, communicating effectively, working well in a team, constructive management of social interactions – that’s here to stay and won’t go away in AI future.
We think humanics are not completed as we miss self – organization and managed diligence.
Ability to self – organize your self, working with your study materials, concept mapping, questioning yourself – these skills are also inevitable.
But, you can easily wrap them in cultural adaptability, although this was explicitly missing the Robot proof book.
So, now when you know what robot-proof and experiential education is or at least you are pumped into new read-ups, get busy learning in 2019.
You can start with humanics or reading something influential and inspiring like the book discussed in this article.
Just, get busy!
What’s superlearning’s got to do with it?
First, learn for your own circumstances, but mostly for your enhancement. Embrace learning as a single life – altering and enhancing entity, the best thing you can be possibly doing.
Second, use superlearning techniques.
With learning “hard” skills like data science or coding you pretty much don’t have any other chance as to learn and test your information learned in the practice. Create a project for you and learn as you go. It also helps if you are really dedicated, to change the ways of learning.
Like with coding – sometimes you need :
- To find a mentor
- To play with already done code
- To build stuff right away
One thing that we truly recommend is considering learning as semantic tree – get the fundamentals all right, so you can build on branches of knowledge later on.
So, it’s tedious but for instance with coding it really helps when you have solid basics of concepts like inheritance, polymorphism, encapsulation, strings and etc.
Download our course InEX Results – oriented learning as this is getting you well – tuned for awesome robot-proof and experiential education learning year of 2019.