Disruption of Mental Work
As much of the muscle work has been replaced by machines, the brain work is starting to face a similar fate by “intelligent” software bots. Cognitive computing like IBM’s Watson is giving computers the ability to “think”, which has the potential to disrupt a wide range of occupations. Computer power will become exponentially more powerful and AI algorithms being fed Big Data from the Internet of Things will evolve from a Smart Assistants like Siri, into Smart Workers and Smart Bosses and even to Smart Teachers and Doctors within the next 20 years.
Disruption of Knowledge Work
A Pew report on AI, Robotics, and the Future of Jobs which asked experts, “Will networked, automated, artificial intelligence (AI) applications and robotic devices have displaced more jobs than they have created by 2025?”, one of the key themes they found and reasons to be concerned was that automation has thus far impacted mostly blue-collar employment; the coming wave of innovation threatens to upend white-collar work as well.
McKinsey Global Institute found that there were 230+ million knowledge workers in 2012 which accounts for 9% of the global workforce and 27% of global employment costs. They predict a $5–7 trillion potential economic impact by 2025 of automation of knowledge work.
“Over the next 10 years, the work of 110 million to 140 million knowledge workers around the globe may be handled by cognitive robotic process automation systems. his shift to robotic process automation — which digitizes labor through the use of advanced machine intelligence, engagement, analytics, big data, social media, mobile technologies and cloud computing — will change the knowledge worker labor market as we know it.” — KPMG’s Cliff Justice.
On its own, each technology has the capacity to change business activity. Taken together, they have the potential to radically reshape society, businesses, the workforce and the economy. These technologies are likely to significantly boost efficiency while eliminating many historic jobs. Big Data is allowing non-routine tasks to become programmable. When there is sufficient data information and computing power available, machine learning can be applied, aiding the computerisation of more tasks.
Improvements in cheap sensor technology will make the The Internet of Things(IoT) usage abundant in the near future plus “The Cloud” will become faster, more reliable and accessible from anywhere by any device. 5G is considered key to the IoT and is predicted to arrive in the US in 2020. Download speeds should increase from today’s 4G peak of 150 Mbps to at least 10 Gbps, that’s fast enough to download “Guardians of the Galaxy” in 4 seconds instead of 6 minutes. The response time will also drop from 15 to 25 milliseconds to 1 millisecond with 5G. The Internet will be ubiquitous.
The IoT is likely to have an application in, or be used by, every vertical segment in the economy. Companies using IoT technologies increased revenue by 16% in 2014, 40% of enterprises are growing their services businesses with IoT Initiatives. IoT spend will increase by 20% to $103m in 2018. Analyst firm Gartner predicts the number of networked devices will skyrocket from about 5 billion in 2015 to 25 billion by 2020. All those sensors will be producing mountains of data.
This will be a major source of information driving Big Data which can then be analyzed by AI to make data driven decisions to plan, manage, research, model, simulate, predict, optimize and execute business processes automatically. Brian Johnson, Principal Engineer at Intel, “We are an Intelligence company, we can bring intelligence to anything”
“General-purpose computers have replaced every other device in our world. There are no airplanes, only computers that fly. There are no cars, only computers we sit in. There are no hearing aids, only computers we put in our ears. There are no 3D printers, only computers that drive peripherals. There are no radios, only computers with fast ADCs and DACs and phased-array antennas.” - Cory Doctorow
Coupled with declining costs and expanding capabilities, billions of sensors will create entirely new opportunities to computerise and optimise routine work. The IoT technology will connect and embed intelligence in billions of objects and devices all around the world. This will lead to digitisation of the physical world, where then it becomes an exponential technology. Software is eating the world according to Marc Andreessen.
Jeremy Howard — “In the Industrial Revolution, we saw a step change in capability thanks to engines. The thing is, though, that after a while, things flattened out. There was social disruption, but once engines were used to generate power in all the situations, things really settled down. The Machine Learning Revolution is going to be very different, it never settles down. The better computers get at intellectual activities, the more they can build better computers to be better at intellectual capabilities, so this is going to be a kind of change that the world has actually never experienced before, so your previous understanding of what’s possible is different.”
Mental Labour
Customer service, back office, clerical, secretarial, and many types of support staff performing routine tasks have the potential to soon be replaced with a digital workforce of software bots. Machines will be more powerful, cheap and connected than ever before and have an increased ability to perform low-level knowledge tasks involving unstructured commands and subtle judgments. They will supplement human jobs and reduce the cost of operations.
“Software bots are far cheaper and quicker than their physical robot cousins. White collar workers on the other hand are numerous, high skilled and expensive. This means from a business perspective the incentive to replace them with automation is even greater than for low skilled work and manual labour. Paper work, discovery, analysis, IT Work, decision making and writing — all key features of white collar work and the professions — could end up under threat.” — Chris Thompson
One example of “thinking machines” is Warren, it is part of a new army of “smart” machines that are threatening to invade office life. These computers do not just collect and process information; they draw inferences, answer questions and recommend actions, too. Gartner says smart machines will have widespread and deep business impact through 2020.
Kenneth Brant, research director at Gartner — “Many new combinations of technology — from intelligent software agents, expert systems and virtual reality assistants to software systems embedded in smart products and revolutionary new forms of robotics — will emerge and have great impacts in this decade. We won’t need to develop a full-functioning artificial brain by 2020 for smart machines to have radically changed our business models, workforce, cost structure and competitiveness.”…
… “It’s worth remembering that IT cost is typically about four percent of annual revenue, whereas the labor costs that can be rationalized by smart machines are as high as 40 percent of revenue in some knowledge and service industries. The supply side of the market — including IBM, GE, Google, Microsoft, Apple and Amazon — is placing large bets on the success of smart machines, while the demand side includes high-profile first movers that will trigger an ‘arms race’ for acquiring and/or developing smart machines. ”
Cognitive computing systems such as IBM’s Watson get better over time as they build knowledge and learn a domain. Rather than being programmed to anticipate every possible answer or action needed to perform a function or set of tasks, cognitive computing systems are trained using AI algorithms to sense, predict, infer and, in some ways, think.
IBM Research is exploring the next step of a machine’s ability to model human intelligence: generating ideas the world has never been imagined before demonstrating computational creativity. A system that can model human intelligence and generate new ideas has many applications and the opportunity to transform customer experience.
Newer generations of Watson are currently being trained in customer service as a support representative. Individual consumers can interact with Watson in plain English to get personalized responses to questions and receive actionable insight with supporting evidence and confidence to help create the experiences customers expect.
As just one of many examples, a bank might offer Watson directly to customers to help understand the types of savings accounts and facilitate the opening of the account that meets their requirements. Between 2010 and 2013, the cost of the servers that comprise Watson, IBM’s AI supercomputer, fell by at least 50%.
“One obvious area of shrinkage is the back office. A reason why small companies scale up into mid-size ones is the need to bring in a range of supporting functions — such as book-keepers, marketers and secretaries — and then middle managers to look after such functions Over the past decade technology has been steadily digitising these roles. In the next ten years much of this will either be automated or else simply handled by external specialists. One major back-office role that will shrink in many firms is the information technology (IT) function: 76% of executives think that it is either highly or somewhat likely to be handled by external partners in the coming decade.” — Economist Intelligence Unit
Powerful computers and sophisticated internet services in the cloud will make individuals far more productive than they currently are and could significantly reduce the demand or need for as many workers. This is not a new trend, but the pace of change is potentially considerably faster than in the past.
Many people who work in the services performing routine knowledge work are set to be disrupted by powerful digital technologies and ubiquitous connectivity. All it takes is one company to use any of these knowledge automation technologies to gain a competitive edge and other companies will have to compete.
Mihir Shukla, CEO of Automation Anywhere — “Take the example of invoice processing. In a week or two a software bot will learn how to process those invoices at your company and begin doing it by itself. In that sense it behaves like a robot, but is software. In the next 5–7 years we will have ten million of these in the market. So this is a huge wave, and it will transform the very basic definition of how we work and at what efficiency. It will transform what productivity means. Software is already defining the workforce today and that will certainly accelerate.”
Another AI software example is Kensho. It’s system is designed to interpret natural-language search queries such as, “What happens to car firms’ share prices if oil drops by $5 a barrel?” It will then scour financial reports, company filings, historical market data and the like, and return replies, also in natural language, in seconds. The firm plans to offer the software to big banks and sophisticated traders.
Yseop, a French firm, uses its natural-language software to interpret queries, chug through data looking for answers, and then write them up in English, Spanish, French or German at 3,000 pages a second on their websites. Firms such as L’Oréal and Vet Online already use Natural Language Processing Software(NLP) for Customer support on their websites.
Journalism has the potential to be disrupted with software that can write stories that are indistinguishable from humans, they are at work now writing many sport and financial stories.
“Every company is becoming, or already is a software company. Even if they don’t know it yet. We buy TVs online with Kogan. We bet online, we buy cars, property and insurance online , We can get a degree online now with Open Universities, and then go on to find a job with Seek. Each of these is disrupting billion dollar industries with software.” — Scott Farquhar
A company called SmartAction uses an Intelligent Voice Automation(IVA) bot to handle calls. It has natural language ability to be conversational and dynamically generate personalised conversations. IVA is best handling customer experience calls, both inbound and outbound, it can solve business problems using a variety of applications across a broad range of industries and is useful for payments, order entry & returns, outbound alerts, FAQs, account status, scheduling, surveys, technical support and info access & verifications.
IVA combines artificial intelligence, natural language, and speech recognition to make customer service calls feel natural, effortless and painless for callers that sometimes customers think they are actually talking to a live agent.
“Automated intelligent assistants are already hard at work doing customer support, sales, marketing, retail, healthcare, utilities, education, and hospitality, the AIAs are designed to recognize real-world implementations that are the pinnacle of real-time natural language understanding, knowledge management, machine learning, and conversational technologies.” — Speech Technology
Nathan Taylor CEDA Chief Economist — “Since the start of the computer revolution, the real cost of computing has created large economic incentives for employers to substitute labour for computer capital. However, these efforts have been blocked because the tasks that computers are able to perform are only those that a programmer can perfectly define. Specific routines have been required for all possible contingencies. For instance, it was once thought that it would be impossible for a computer to come close to a human driver in traffic. The sheer number of potential contingencies of driving through a busy city, with automobiles and pedestrians contesting the use of space, was thought to be such to forever defeat a programmer. But the computer is now out of the box.”
Digital Managers
Middle management is due to become more efficient and advanced by algorithms generated by AI. Machines will begin to understand complex data in real time and will have insight and domain expertise to make the best decisions.
“We should no longer expect traditional job ladders for managers to move up the ranks, or even retaining the notion that middle managers are the glue that connects workers and ensures goal alignment up and down the hierarchy. This is different. Rather than managerial “rules of thumb” to guide such decision-making, real data based on past behaviours has become remarkably effective at predicting what we like to consume. All of these changes — technology, business culture, and demographics — add up to a world where middle managers will be less valued, and less needed.” - A BBC article on The end of middle management
Siri, Google Now and Cortana didn't even exist 6 years ago. How much smarter and what will these personal assistants be capable of within 20 years? You may actually start to think there is an actual person in your phone.
Vivek Wadhwa — “Kurzweil, a renowned futurist and the director of engineering at Google, now says that the hardware needed to emulate the human brain may be ready even sooner than he predicted — in around 2020 — using technologies such as graphics processing units (GPUs), which are ideal for brain-software algorithms. He predicts that the complete brain software will take a little longer: until about 2029. The implications of all this are mind-boggling. Within seven years — about when the iPhone 11 is likely to be released — the smartphones in our pockets will be as computationally intelligent as we are. It doesn't stop there, though. These devices will continue to advance, exponentially, until they exceed the combined intelligence of the human race.”
In the example above the AI could understand the screen information automatically, could these be used on office computers in the future and perform worker tasks automatically, how close are smart AI workers?
We can actually predict with reliable accuracy due to Moore’s Law, computers will be so much more advanced and powerful in the future, plus they will be receiving even more data from the billions of sensors making up the Internet of Things which the AI can use to better understand its surroundings as the world becomes more digitalized. Here is where machine learning can be used to optimise and automate even more complex tasks, such as giving out making decisions, giving orders and providing feedback. Smart AI Workers will evolve to become Smart AI Bosses.
Andy Baker, director at Hitachi Consulting: “Following the rise of social, mobile and cloud technologies, which enable the collection of big data, sophisticated analytics tools are now emerging to deliver unprecedented levels of insight. Employers can keep a close eye on operational efficiency, employee engagement and consumer engagement, allowing them to make informed decisions about business processes like never before.”
An article by New Scientist found employees will start to have wearables as part of their uniform, which computer systems can track, wearables are already being used to monitor exactly how employees work. At the UK warehouses of Tesco, workers wear armbands that track where they go so they can be sent location-specific tasks. At Capriotti’s Sandwich Shop in Las Vegas, new recruits record their work with Google Glass for managers to assess later, Virgin Atlantic has plans to do the same. Starbucks employs a widely-used software program that examines sales patterns and other data to determine scheduling of its baristas. IoT will allow you to virtualize your business and view it’s operations.
Imagine cheap wifi cameras sending data to a powerful computer which can understand scenes as computer vision and AI improves, giving the digital boss a pair of eyes or augmenting employees with an earpiece or smart watch and have an smart AI monitoring every aspect and status of the place of work, overseeing employee/customers activity and locations through the IoT and using it’s advanced analytics to narrate commands or assign tasks dynamically to each employee to optimise the running of the business.
A machine learning algorithm from Google DeepMind was able to learn to play Atari games and control it’s “player” to get high scores. This may be really basic and possibly naive of me but imagine in 20 years time, could a business use a similar training model, have profits as a high score, employees as the player, run simulations to learn the best strategy and then use it’s operational visibility from all it’s sensors to control the human “players” to achieve an optimised goal in a real situation?
A very basic example this could be used is a shop, suppose many customers suddenly walk in, a notification to an employee to go to the cashier spot to prevent a queue from forming in the 1st place, or maybe the AI spots a customer who appears to be confused, walking round in circles like they can't find an item and the AI alerts the nearest employee to assist them. Cameras with advanced vision AI could even be used as security guards to perform “human intuition” to notice and monitor suspect behaviour. It could instantly recognize faces from police databases of shoplifters and advise appropriate safe action, although this could lead to privacy concerns.
Extract from the article, Can a Robot Be Your Boss? by the University of Pennsylvania, Wharton.
Research from MIT show how groups of two humans and one robot worked together in one of three conditions: manual (all tasks allocated by a human); fully autonomous (all tasks allocated by the robot); and semi-autonomous (one human allocates tasks to self, and a robot allocates tasks to other human). The fully autonomous condition proved to be not only the most effective for the task, but also the method preferred by human workers. The workers were more likely to say that the robots ‘better understood them” and “improved the efficiency of the team.”
In nearly all categories relating to HR from recruitment to performance management, companies participating in the CedarCrestone 2013–2014 HR Systems Survey said they were substantially increasing technology enablement of HR processes. (The survey represented 20 million employees, mostly in the U.S.)
Ben Waber, CEO of Sociometric Solutions, thinks firms can sell the idea of “people analytics.” Waber’s firm tracks employee movements during the day through sensor badges, detects email and phone call algorithms, and analyzes workforce behavior like facial expressions and tone of voice — up to 100 data points a minute — to ultimately recommend changes to improve efficiency and productivity.
In one case, at a Boston-area hospital, this meant mapping teamwork patterns among nurses and tracking their footpaths and interactions with patients in a post-surgical ward. By putting into place a real-time map showing who was doing what and when, the firm says it was able to reduce costs while improving overall health and recovery times. People analytics is gathering so much sophistication, says Waber, that “over the next decade you are going to see it subsume all of the functions HR does.”
Hiring and recruitment is already being automated and showing better results such as a more diverse workforce. A new wave of start-ups is trying various ways to automate hiring. They say that software can do the job more effectively and efficiently than people can. Many people are beginning to buy into the idea. Established headhunting firms like Korn Ferry are incorporating algorithms into their work, too. If they succeed, they say, hiring could become faster and less expensive, and their data could lead recruiters to more highly skilled people who are better matches for their companies.
In 20 years, with the exponential growth of computing power, improved AI Algorithms, rise of the IoT and a powerful innovation and entrepreneurial force of a growing educated planet, which expects 2–3 billion more people with access to the Internet in 2025, the capabilities of our current state of art AI’s such as self driving cars, may look pretty dumb in comparison.
“The world’s capital is flowing towards automation and away from investing in human labour simply because automation has a better ROI. This is the tipping point economically speaking and there is no return from it. In any job involving forms processing, there’s less and less need for a human to be involved.” — Kamila Hankiewicz CEO at Amuse
High Skilled Jobs Disruption
Some of the most highly skilled occupations needing vast amounts of training and knowledge are at risk of disruption. A report predicting the shape of the legal market has envisaged that robots and AI will dominate legal practice within 15 years, perhaps leading to the “structural collapse” of law firms. There is a 94% probability of accountants, auditors, paralegals and legal assistants, all being replaced by automation within 20 years according to a study by Carl Frey and Michael Osborne.
A study by Gartner found one-third of highly skilled work by doctors, lawyers, traders and professors will instead be done by smart machines, or by less-skilled workers using computers by 2023.
Kenneth Brant, research director at Gartner — “Most business and thought leaders underestimate the potential of smart machines to take over millions of middle-class jobs in the coming decades, Job destruction will happen at a faster pace, with machine-driven job elimination overwhelming the market’s ability to create valuable new ones.”
Finance is susceptible to large amounts of disruption by technology according to Vivek Wadhwa, he explains that “innovations such as crowdfunding and Bitcoin represent disruptions to the financial industry as well. Experiments involving crowdfunded loans are already being made outside the U.S. We may not need the banks anymore. We may not need financial institutions the way we do right now.” Recently a venture capital firm hired an algorithm to its board of directors to help with financial and business decisions.
The entire banking industry can be disrupted for the better and bricks and mortar banks are “heading for tough times”, according to Taavet Hinrikus, founder and executive chairman of TransferWise. “Every vertical in banking is a huge opportunity,” Hinrikus told the audience at WIRED Money 2015. “As a consumer, I’m definitely waiting for what’s going to come after banks.”
Machines are evolving from automating basic tasks to becoming advanced self-learning systems as capable as the human brain in many highly specialized professions. Other highly skilled occupations such as STEM face increasing risk of disruption from increased global competition and new technologies as explained comprehensively in my article on STEM Disruption.
Watson Discovery Advisor which can be used in many areas such as Law or Cancer Research is as an engine that can search thousands of unstructured data sources in seconds with a level of “intelligence” that can make sense of semantics, idiom, and grammar and be trained to understand technical expressions, disciplinary jargon, abbreviations, acronyms, and labels with the purpose of making connections between these and delivering new insights for researchers, clinicians, drug manufacturers and others that saves them inordinate amounts of time and millions of development dollars.
Watson is using its cognitive computing tools is used to create targeted cancer therapy based on you and your cancer’s genetics by using Big Data. In 2013 IBM’s Watson’s successful diagnosis rate for lung cancer is 90 percent, compared to 50 percent for human doctors. In 2011, IBM announced that Watson had “learned” the same amount of knowledge as the average second-year medical student. Watson’s ingestion of more than 600,000 pieces of medical evidence, more than two million pages from medical journals and the further ability to search through up to 1.5 million patient records for further information gives it a breadth of knowledge no human doctor can match.
“I don't think physicians will be seeing patients as much in the future,” says David Lee Scher, a former cardiac electrophysiologist and the president of DLS Healthcare Consulting, which advises health-care organizations and developers of digital health-care technologies.“I think they are transitioning into what I see as super-quality-control officers, overseeing physician assistants, nurses, nurse-practitioners, etc., who are really going to be the ones who see the patients.”
Peter Diamandis who runs the XPrize Foundation says people will become the CEO of their own health. Wearables will be tracking your vitals constantly, combined with data about your genealogy, allowing you and others to make better health decisions. By the end of this year Diamandis will have the 1st step towards a personal doctor in your pocket with the Xprize Tricorder. The mobile health market will grow from $5.1 billion in 2013 to $41.8 billion in 2023 — an eightfold increase, this is why many companies are looking to get into this market.
Your phone will also become your optician. A smartphone app is as effective at testing eyesight as an optician’s clinic, a trial suggests. The team modified a smartphone to develop a series of eye tests that could be used with little training and were easily portable.It uses the camera’s flash to illuminate the back of the eye to check for disease.
Eventually your mobile phone will diagnose better and cheaper than any human could, it will be like having a team of the world’s best medical experts in your pocket. If object recognition improves over the next 20 years then a phone camera could be used to spot what type of rash or skin condition and use your genealogy to instantly suggest the appropriate ointment. It’s possible you may feel more open about dicussing bodily issues to a robot doctor, for example in drug abuse or intimate issues.
“While robots that look too much like actual humans generally repulse people, this is not the case with Ellie. In fact, people seem more willing to talk openly with a robot shrink than they do with a human one. In turn, Ellie is able to track subtle changes in human facial expressions, body language, and vocal tone, allowing her to read emotions and provide this information to human therapists who wish to flag depressed or suicidal patients” — Alex Spiegel, NPR.
Machines will replace 80 percent of doctors in a healthcare future that will be driven by entrepreneurs, not medical professionals, according to Sun Microsystems co-founder Vinod Khosla. Khosla went on to refer to common medical practice as being akin to voodoo, saying “healthcare is like witchcraft and just based on tradition” rather than data driven, as he believes it should be. Machine learning, he argues, will be a more efficient, cheaper and more accurate diagnosis tool one day.
“Consider a world where patients are constantly being monitored by biosensors on their bodies and the data from those sensors is being assessed in real-time by machine-learning algorithms looking for anomalies, and diagnosis is performed by a Watson-like computer. Under these circumstances, the number of patients each physician can deal with will rise and thus there will be a need for fewer physicians per head of population than today.” — Hugh Bradlow
Digital Teachers
Massive Open Online Courses(Moocs) have only just started to arrive, if you look at current huge list of free available Moocs such as Coursera, Udacity, edX, The Open University, Khan Academy, Udemy, Canvas Network, FutureLearn, Code Academy, Apple U and many others you can see the amount of free or cheap education that is now accessible to anyone with an internet connection.
A Netflix of on demand education will be available, similarly to how people(especially generations about to enter education) are watching TV on demand when it’s convenient for them, the idea of set times or no catch up services may be incomprehensible to them. As more courses become doable online, then attitudes could change. If a college student has a choice between a travelling to a 9am lecture in the winter, or a lie in and watching the lecture and reading the course notes from the comfort of their own warm bed, then the structured set time model has no chance in competing.
Online education may help with diversity issues, currently at Google only 2 percent of employees are black and 3 percent are Hispanic. This open-access model does seem to help — Codecademy says 34 percent of its users are women, for example, nearly double the percentage of female graduates from university computer science programs in the United States.
The first MOOCs were replicas of the traditional, full-semester experience. Now people are experimenting with a lot of formats that break with tradition, the next generation of Moocs will become “Hollywoodified”. The course materials will be made more engaging to users and they will use the best charismatic, passionate and entertaining educators in the world to make absorbing information more captivating than any local teacher.
“I think of the days of old without movie or video games, if you wanted to see a play, at any given town you would have a troop of actors generally usually wouldn't be very good. Now with movies you take the best actors in the world, best script writers, best directors, best sound, best editing and special effects, multiple takes, all to make it really compelling, that's why you want to sit down and watch a movie, that's how teaching should be. There is still a role for teachers but it should be a helping role as for when pupils get stuck as opposed to just lecturing in front of a classroom” — Elon Musk
We know the traditional lecture format in teaching students has many inefficiencies and limitations, in the lecturing format. A class can not all learn at the same pace and in the same way, pupils who miss a lesson due to illness are at a disadvantage and can find it difficult to catch up. Teachers have to spread out there time and resources to the whole class, minimising personal interaction. Teachers are not of the same skill level and can have bad days plus with modern day distractions like smart watches teachers may find it increasingly to keep the class’s attention.
With a movie you also have the ability to pause and rewind to rewatch scenes or take breaks. If Moocs had bigger budgets where they could recruit the best people in each department they could improve the education experience. Look at the recent audience for Cosmos. A whopping 135 million people — including 45 million in the U.S. — watched at least some of the 13-part science series. When you make education fun and interesting people want to learn.
We will soon have incredibly immersive VR and AR technology. Using it students can go back in time to simulations of ancient Rome as you learn about Caesar, stand on the surface of Mars as you learn about the Solar System or learn new practical skills and knowledge cheaply and safely, e.g. dissecting frogs without harming any animals or expensive Lab equipment.
The old model of looking at text, pictures and even video will not be able to compete with the much of an interactive experience. The “Hollywoodified VR Mooc” will become more engaging than any passive experience such as listening to a teacher at a blackboard or watching a video.
Operating virtually unchanged for over 500 years, universities around the world are not going to be able to carry on at their current pace of educating people against exponential disruptive technologies. Universities themselves need a radical shakeup of their operations and move to become an exponential technology themselves, they have to utilise new technology to optimise teaching. Just like an AI will soon become the world's best doctor, an AI will become the worlds best personal teacher.
Vivek Wadhwa — “Today, the blackboard has become a whiteboard; chalk has become a magic marker; the slates that students used have been replaced by notebooks; and classes have sometimes gotten smaller. Little else has changed. True, some schools are providing their students with laptops, and teachers are increasingly using technology and encouraging collaboration. But the methods are essentially the same — with the teacher dictating learning.
What is becoming possible, however, is a revolution in education. I am not talking about the much-hyped Massive Open Online Courses. To me, these are as imaginative as the first TV shows in which radio stars stood in front of a camera with a microphone in hand. I am talking about a complete transformation of the way teaching is done, with the computer taking the role of the lecturer, the teacher becoming a coach, and students taking responsibility for their own learning. The digital tutor of the future will do knowledge transfer better than a human can”
Computers will mark the written component of the NAPLAN exams from 2017 under plans from the Australian Curriculum Assessment and Reporting Authority. They found that the computers could score as accurately as humans. A follow up in 2013 yielded the same result. Auto-marking is central to being able to return student results within a two week period, he said. Under the current system schools have to wait up to five months to receive their results. Dr Rabinowitz has dubbed “NAPLAN 2.0”, will see the replacement of paper tests with online exams at every school in the country by 2019.
Interactive and gamified elements will enter education allowing instant feedback and gratification, examples of this already exist, students can earn points for good behavior on ClassDojo, or by answering questions on their smartphones in the Kahoot! app, which claims 30 million users. Students playing ClassCraft use special powers to advance their team through a virtual world. Correct answers unlock perks like asking questions during tests.
Duolingo believes it can create software that can teach students fluency in different languages. To achieve this goal it is hiring more learning experts and studying the data, says cofounder Severin Hacker. A team of machine-learning specialists is fine-tuning the way its algorithm determines what students know, what they should study next, and what messages best motivate them to keep learning, delivering an adaptable, personalized learning experience. Duolingo feels more like a game than like traditional language learning. Originally it would award students three hearts at the start of a 20-exercise lesson. Every mistake cost the user one heart. Lose all three, and you had to repeat the section.
Artificially Intelligent Hollywoodified Gamified VR/AR Interactive Moocs…phew… will be the future of knowledge transfer. You can say “Ok Google, teach me about Newton’s Laws of Motion” an AI teacher will bring the best materials in your preferred style of learning. The software will explain difficult concepts easily at your pace, you can ask it questions without feeling dumb as you might in a classroom surrounded by peers. The software will be able to read your face when you are stuck, and react by slowing down or advising a break. A VR experience could have visualisation and playing around with Newtonian mechanics in a VR world as you learn in a gamified way.
Michael Osborne, associate professor of machine learning at the University of Oxford — “Each student will have a device at their desk which will be delivering their content tailored to their interest and expertise, rather than everyone receiving the same material from the teacher in front of the class. Robots could replace teachers as the primary source of information in classrooms around the world. Technology allows superior delivery of information.”
AI driven MOOCS after refinement will start to make some university’s obsolete as they prove to be better at teaching and assessing skill levels. Their credentials will speak for themselves and be favoured by employers. An educational app designed to help provide a better education for children in Malawi has proved an equally effective learning tool for pupils in the UK. Working on the iPads for 30mins a day, UK children made the same progress in Maths in six weeks as expected after 12 to 18 months of teaching.
Education giant Pearson has launched Pearson Catalyst, an incubator for the most ambitious start-ups in education. Pearson knows that education is on the brink of a technological revolution. The scheme will provide mentoring and advice for ten lucky start-ups. More than 200 firms have applied.
Peter Diamandis launched a $15 million Global Learning Xprize to develop open source and scalable software app that will enable children in developing countries to teach themselves basic reading, writing and arithmetic within 18 months. It currently has 198 teams registered working on it and is expected to be finished by 2019. There’s also an Adult Literacy Xprize which aims to empower adults to learn and improve their reading ability.
Investors have increased funding of educational technology startups worldwide, from $1.6 billion in 2013 to $2.4 billion in 2014; they invested over $1 billion more in the first quarter of 2015. Advancing Artificial Intelligence will become better than humans at knowledge transfer. Current education models will be inferior and struggle to compete. IBM are working on educational software which learns about you to tailor make lesson plans for your ability.
“Since the days of the one room schoolhouse, both K-12 and higher education classrooms have been focused on a one-to-many interaction between a teacher and a group of students. All students receive the same material from a teacher in a lecture setting because individual attention for 30 or more is nearly impossible. But IBM and its education partners think the classroom of the future will shift from a one-size-fits-all model to a truly personalized environment.
University is very expensive in the US, there may be a limit where students decide against plunging themselves into debt and see AI Moocs as a better, cheaper alternative, this new technology could make many college buildings and the numerous amounts of staff that work there unnecessary.
Even though this will disrupt many jobs its the best solution to better prepare all students and adults, especially low skilled people, to continually adapt and improve their skill set quickly and cheaply for the disruptive job market of the future.
As the new wave of this digital revolution makes more and more roles redundant, it is important that proactive steps be taken to ensure workers develop the skills to remain, and current non-workers, are able to participate in the workforce, economy and society.
Erik Brynjolfsson — “I think that there are bigger technological changes likely in the next ten years than there were in the last ten years and we know that those were pretty disruptive for the economy.” Right now I don't think we’re taking it seriously enough. “It’s not a matter of slowing down the technology, it’s a matter of speeding up our response to it.”
In conclusion this thorough and comprehensive explanation shows clearly the potential for automation of much mental work within the next 20 years. The best investment the government can make is in education, having a highly skilled adaptable workforce will be key to navigating this disruptive period we are entering. We can all equally enjoy what this wonderful technology is bringing us. I discuss 5 solutions to achieve this.
The Government needs to incentivize Worker Self-Directed Enterprises (Worker Co-op’s) and encourage an increase in Unions(especially for self employed workers) to bring democracy to the workplace. This will reduce income/wealth inequality which will raise working people's wages. It will also keep jobs from being outsourced, reduce climate change and force companies to invest and allow their workers time to transition to new jobs or skills, if they decide to automate their roles.
A Lower Work Week and Increased Vacation Time(which is achievable as people's incomes have been raised by Worker Co-ops) to spread out decreasing amount of jobs more equally which will increase economic productivity and prevent social division between people who work and those who don't or can't work. The Government can also top up low wages by raising taxes on the super rich and preventing tax evasion. This will give us more leisure time to enjoy the wealth and prosperity this technology should rightfully be bringing us.
A solution already discussed is Improving Education for people to gain higher skills at any age quickly and cheaply, the final solution is a Guaranteed Basic Income, which is needed as a safety net for people disrupted and unemployed, so they can retrain their skills for more complex jobs, without the fear of homelessness, child poverty for their children or going hungry. I discuss the solutions in more detail on my website.
