We used to think only humans could do mathematics. Then we invented the calculator. We used to think only humans could understand natural language; then we invented smart agents, voice recognition software, and supercomputers than can read and understand human language. We used to think only humans could drive cars. Then we invented self-driving cars. We used to think only humans could recognise faces; then we invented facial recognition software. We used to think only humans could do a whole bunch of stuff: play chess, direct traffic, compose music, create art, write stories etc. Today, we have A.i. that is capable of doing all this and these A.i. systems are improving at an exponential rate.
Consider Google’s Deep Dream system that can create art. It is a program that adjusts an image to stimulate the pattern recognition capabilities of a deep neural network. By running the image recognition programme backwards, Deep Dream was able to generate phantasmagoric pagodas, psychedelic dogs, alien-looking plants and so on — images that looked haunting and hallucinatory and not a little disconcerting when we realise that no human had programmed these systems to create art and we had little idea how the system was doing it.
We also have Deep Learning systems composing music. AIVA (Artificial Intelligence Virtual Artist) is a system that composes music for films. It recently released “Genesis,” its first album, and has officially become the first A.i. to acquire the worldwide status of Composer. It has even been registered under the France and Luxembourg authors’ right society (SACEM), and its work is copyrighted in its own name. The music AIVA has composed simply cannot be identified as having been created by a non-human intelligence. The title track from the album is sublime and deeply moving. To think that a non-human could create something this powerful and emotionally moving is hard to believe. You have to hear it to believe it. And once you do, it will shake you to the core.
Over in China, Baidu is the largest search engine. Their Baidu A.i. composer is now using the world’s largest neural network to compose original music inspired by art. Using image recognition software, the system scans various images of art and identifies various elements of the painting: objects, colours, setting etc. Analysing tags that people have used for each painting, the system can also associate tone and mood with each painting. Baidu’s Deep Learning system then connects with a database of musical compositions that are divided up into musical units and itemised based on the moods and emotions they evoke. The A.i. composer system then reinterprets the elements of the image as a series of notes, fits together bits of music based on the mood of the image, and ultimately creates a unique and original melody.
So, the big question — the urgent and pressing question, for those of us in the education industry to answer is this: if A.i. is set to do all these remarkable things that we used to think only humans could, then what is the purpose of education and what should the focus of schools of the future be? And what about the robots?
What is Robotics?
Very simply, robotics is the branch of A.i. that is concerned with the practical use of robots. It is a branch of technology that sees a conflation between engineering, computing, mathematics, and science. Science fiction author, Isaac Asimov is credited with using the word robotics for the first time in a 1940 short story
How will it change the way pupils learn?
· Robotics is now an information technology, and like all information technologies it is growing at an exponential rate.
· Robotics is an important part of STEAM education which is already a major focus in many progressive schools.
· A renewed focus on robotics and STEAM will help nurture creative innovate students.
· As the world becomes ever more digital, coding and programming (which are an integral part of robotics) will increasingly become core elements of what students learn.
· Robotics also helps to introduce an element of play into learning.
· The Maker Movement is an essential part of promoting innovation in schools. Robotics plays a vital role in the maker movement allowing students to learn through collaboration and by focusing on solving practical problems facing human society.
· MIT’s Media Lab sees coding as the new literacy. Students will increasingly be expected to create and design using programming skills.
What should we expect to see in schools in the near future?
· Increased focus on coding and programming
· More STEM/STEAM labs
· Emphasis on Maker spaces
· Less focus on subject content and more focus on solving real-world problems
· Increased emphasis on coding for 3D printers
· Robotics in the near future will become as important and as ubiquitous as ICT has been in recent years.
· Teachers will focus on upskilling themselves (even non-STEM teachers).
In which subjects, will robotics be most useful?
· Particularly in STEM subjects (from a surprisingly young age — perhaps even Foundation stage students).
· But depending on the creativity and imagination of the teacher and the lesson plan, it could be used in the Arts and Humanities as well.
· Robotics can be used in two ways: 1) as a subject on its own 2) As a tool to teach other subjects
How can robotics help those children with special needs?
· Introducing an element of play is useful when working with special needs students. Resources like the Lego Mindstorm kits make learning fun, but also teach students critical thinking, collaboration, problem-solving and creativity.
Will it impact the way children interact and potentially hinder communication?
· Students of the future cannot be expected to communicate the way we do today. It’s hard to say definitively one way or the other whether robotics will promote or hinder social communications.
· But we can say for sure, children of the future will communicate differently (as have all generations in comparison to their predecessors: the generation after the invention of papyri was different from the generation that read books, which in turn was different from the generation that read via CD ROMS, Kindles, tablets and mobile phones.)
How will robotics develop over time — in the next 10 years or so?
· Robotics and A.i. will increasingly complement one another.
· An ever-increasing number of jobs will be taken over by A.i. or be automated by robots.
· It’s not going to be a case of us v/s them. Humans will cognitively sync with their robots to form a Humanity 2.0
· Elon Musk’s new company, NeuraLink, aims to create a direct interface between humans and computers. This has the potential to have enormous ramifications and consequences for the future of our species.
· Ray Kurzweil, Founder of Singularity University and Director of Engineering at Google, predicts that in the coming decade we will have computing power trillions of times more powerful than the human brain. This computing power, combined with A.i. and Robotics will transform human society in ways we cannot yet imagine. (Just as the creators of the Internet couldn’t have imagined a world of YouTube, Facebook, Twitter, and ubiquitous Wi-Fi).
Will robotics form an essential part of learning forward?
· Robotics education will prove to be essential in promoting innovation.
· Robotics, coupled with Virtual Reality and Augmented Reality will play an ever-increasing role in all industries, particularly education, medicine, warfare, and space exploration.
· Robotics is connected with critical thinking, collaboration, and problem-solving — important 21st-century skills that will apply to all industries.
Simply put, computational thinking is the thought processes involved in formulating a problem and generating a range of solutions in a way that can be understood by humans or computers.
Developing knowledge and dispositions necessary to understand and create with computational thinking is now 21st -century imperative. With trillions of networked microchips transforming our lives, education has never been more important to our futures. Today’s students need to more than “code” in class; they need to use computational thinking in an ongoing way to inspire curiosity, imagination, play, invention and creation.
Going forward in the 21st century, it’s not enough for us to teach kids to code. We’ve got to focus on the thinking process behind coding that will have wide-ranging consequences and far-reaching impact on all aspects of life and society.
Computational thinking cornerstones
In its most basic form, computational thinking is an iterative process based on three stages: Problem formulation (abstraction); Solution expression (automation); Solution execution and evaluation (analyses).
Computational thinking is used to create programmes; however, it can also be used to solve a range of problems across disciplines. However, before we use computers to solve a problem, we have to understand the problem itself and identify ways in which the problem may could be resolved. Computational thinking techniques help with these tasks.
To do this, computational thinking is generally thought to be comprised of four cornerstones:
Decomposition: Breaking down a complex problem or system into smaller, more manageable parts.
Abstraction: Focusing on important information; ignoring irrelevant details.
Pattern recognition: Looking for similarities among and within problems
Algorithms: Developing a step by step solution to the problem.
It’s important that students are given opportunities to hone their computational thinking skills even outside their computer science or ICT lesson. One way of doing this is to revisit the curriculum and identify opportunities to inculcate computational skills.
It is important to be aware that computational thinking as a skill or concept is different from Computer Science as a subject. Computer Science is the study of information: How do you represent it? How do you best store it? How do you process it? Computer Science is the study of computation and its application using computers. On the other hand, computational thinking includes the skills and ways of thinking that are used when writing computer programmes.
Google’s course on computational thinking makes the following distinction between the two:
Computational thinking can be adapted and adopted in a range of other subjects. Google’s online course on computational thinking for Educators offers a few suggestions:
A danger we need to be wary about as we move forward is to avoid thinking of computational thinking as being the same as computer science. As described above, the two are very different. But there has been a tendency in many schools that are early adopters of computational thinking to club it with Computer Science or see it as a substitute for Computer Science. Computational thinking is an element of Computer Science — but it has applications in all subjects. There is also the other genuine concern that computational thinking is being added into the curriculum because it looks good in the school brochure or keeps the school inspectors satisfied that the school is being “innovative” in its curriculum offerings. However, the real innovation in the use of computational thinking is not just in its mere offering in schools. The real innovation would be in encouraging students and learners to think broadly about the challenges facing our species; break it down into its constituent parts; identify the core areas that require solutions, and then generate solutions in an organised and methodical manner for these grand challenges. All the while, we’ve got to take care to ensure that the solutions they come up with also take into consideration the relevant moral, ethical, and social ramifications and don’t create more problems in the process.
Ray Kurzweil points out that in the future we’ll see a merger between humans and machines. Thuc Vu, co-founder and CEO, OhmniLabs, says that the partnership between humans and machine will transform “how we arrange and direct our lives to seamlessly provide what we need, before we need, with just the wave of a hand per se. It’s possible to imagine a future in which machines become extensions of ourselves. Today we have digital natives. In ten years, we’ll have digital conductors.”
There is every reason to celebrate the sophisticated capabilities of today’s emerging technologies. These new human-machine collaborations will usher in a future in which humans and machines build on their mutual strengths to contribute a staggering improvement to the conditions for everyday living.
Classifying the skills that machines should bring to the table and what humans should contribute to the partnership is key. Forging strong working relationships depends upon each party bringing something unique to the collaboration.
Jordan Howard, Social Good Strategist and Executive Director of GenYNot, sees tremendous promise for the future of human-machine partnerships: “Many of the complex issues facing society today are rooted in waste, inefficiency, and simply not knowing stuff, like how to stop certain genes from mutating. What if we could solve these problems by pairing up more closely with machines and using the mass of data they provide to make breakthroughs at speed? As a team, we can aim higher, dream bigger, and accomplish more.”
What most people are concerned about when they contemplate a future with robots and A.i. is the loss of jobs. But the fact is, we’ve been in the situation before — with the Luddites during the 19th century Industrial Revolution. This was a time of social upheaval and dramatic economic change. Machines and factories were taking over jobs that were traditionally done by humans. The working class began to become increasingly agitated about the scarcity of jobs caused by the invention of new machines. Rallying under the real or mythical figure of Ned Ludd, groups of agitated workers began destroying weaving machinery as a form of protest. They called themselves Luddites — and the word has now come to refer to any opponent of technological progress, industrialisation, automation, or computerisation. Ultimately, the Luddites were put down with military force and many were shot to death. And the Industrial Revolution went full steam ahead.
We have lessons to learn from this episode in history. Imagine, for a moment, what our current world would look like if the Luddites had had their way: a world with no machines and no factories, where hundreds of millions of humans would be consigned to a plodding life of drudgery, where production was slow, laborious, and filled with errors. Of course, this is not to imply that everything about the Industrial Revolution was positive. The matter of industrial-scale pollution and rampant ransacking of the Earth’s resources began at this time and has not ceased since. Capitalism, and all its associated avarice, also saw its birth at this time.
But the fact remains, that the Industrial Revolution resulted in more efficient production, cheaper goods, and an improvement in the quality of life for millions of people. To deny this is to evince a marked ignorance about history and the social and civic condition of pre-19th-century life. But the most important thing to remember is that ultimately, the Industrial Revolution created more jobs than it took away — and all the luxuries we take for granted today owe their antecedent causes to the events that took place in this period of human history.
However, many historians and futurists concur that we are currently live in a time unlike any other. A.i. and other Exponential Technologies are disrupting things faster than at any other point in human existence. As Pulitzer Prize-winning journalist, Thomas Friedman puts it: Whatever can be automated and outsourced will be automated and outsourced. Trying to stop this trend would be as futile and foolhardy as the attempts by the Luddites to destroy the weaving mills.
The reality is that robots and machines will take over all if not most jobs that are repetitive and require precision. A report in the Guardian published in February 2017, stated that the robot sector “could be ‘the next Uber’ and staff should embrace the gig economy amid a rise in automation.” The report continued to describe the findings of Reform, a right-of-centre think tank, which predicted that almost 250,000 public sector workers could lose their jobs to robots over the next 15 years because machines would be more efficient and save billions of pounds.
China is spending billions on equipping their factories with advanced manufacturing robots. The social and economic ramifications of this will extend far beyond the boundaries of China. We owe it to our kids to help prepare them for this rapidly changing future. Merging with machines and fostering a mutually beneficial collaboration will be key. In the near future, a combination of knowledge, experience, and expertise will still be valuable for most individual human beings. But more important than that will be the application of knowledge, experience, and expertise — and the ability to employ them in an entrepreneurial way while being able to see the big picture and connect ideas from disparate fields. The skills of the entrepreneur will be fundamental to a machine-human partnership. These skills include grit, passion, drive, empathy, ability to collaborate and inspire etc.
We are increasingly living in a world of reputation engines, data visualization, and smart analytics. This is making it ever-easier to search for individuals’ skills, competencies, and abilities. Therefore, it is vital that we teach our kids how to network, how to build connections, find mentors, and develop a strong personal brand. Building a vibrant and trustworthy personal and professional reputation will be crucial for the future workforce.
Just as important is to be aware that we now live in an Age of Information. We are bathed in it and are generating ever more information at a staggering pace. The future workforce will need to be able to use technologies to sift through mountains of information, sort out fake news and alternative facts, separate fact from fiction and information from misinformation, differentiate between disinformation and propaganda. They will be required to reach conclusions, synthesise ideas, and formulate conclusions using a healthy mix of scepticism, critical thinking, and common sense.