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Summary keywords: people, learning, labour markets, education, skills, technology, countries, jobs, pandemic, digital, future, longer, scenarios, world, incredibly, systems, work, test, progressing, artificial intelligence

Andreas Schleicher 00:34

Hello and thank you so much for inviting me to your conference on transforming skills and inclusion. These are difficult times even before the pandemic, labour markets were polarising, digitalisation was transforming most of the jobs, inequality kept rising in many countries.

If you think about it, you know, digitalisation has been incredibly democratising. Everybody can collaborate, everybody can contribute. But it's also concentrated power at a rate we've never seen before.

Technology has been incredibly polarising, the smallest slice can be heard everywhere you post something on Twitter, and the world can follow you. But technology has also been incredibly homogenising, squashing individual differences cultural uniqueness.

Technology has been incredibly empowering. The most successful companies these days, you know they have the product before they have the money. They start with a big idea not you know, with a lot of epic industry. But technology has been also incredibly disempowering when we suddenly become the slaves of algorithms that we no longer understand. You think about it, digital platform technology drives the reorganisation of France, we no longer know what's a big and a small company, sometimes very few people can transform the world.

Peer to Peer markets are blurring the distinction between consumers and businesses and even governments are starting to leverage the platform economy. Some people say well, you know automation is taking away jobs. But actually what we see is that digital intensive workplaces are much better at extracting value from the skills of people and converting better skills into better jobs and better lives of people.

And this is not just about technological skills, you can see almost in any skill category, the returns now that our earnings and employment are rising for people in digital intensive industries.

Data from our survey finance skills have also shown you know, where you work in a more digital intensive workplace, you are more likely to learn from your coworkers, you're more likely to learn by doing trying things, finding things out for yourself and you're more likely to keep up to date.

Now the digital world is pushing us you know, to remain at the frontier to keep progressing to keep advancing. So we should see the digital world is not an empowering word as a world that actually transforms you know better skill to the backdrops and better lives. And that seems almost direct relationship between between the skills in population here I measure literacy and numeracy skills through our server fuddled skills, and the risk of automation.

On the left side, you see countries where labour markets are not so much at risk to be automated. By you can see also these are countries where numeracy skills typically cannot be well developed, you go towards the right side. These are countries where numeracy skills seem to be less developed in the workforce, and the risk of automation seems higher. So seem to be great insurance against the risk of automation for individuals and for nations.

Now, this is what people in the workplace does. When you look towards the young people now in our latest PISA survey, they asked teenagers, young people at age 15 What are their dreams for the future? What are their own aspirations? And it's quite frightening that you have many countries where you have you know, 40%, sometimes over 50% of young people looking for jobs that may no longer exist when they graduate.

A very large chunk of teenagers, and even more so among disadvantaged groups aspire to jobs that have disappeared. They don't seem good enough to give Yeah, People better signals about the evolution of labour demand about the nature of jobs in the future. And that is so important.

You know, if you have never seen a scientist was a scientist, why would you start to study hard in mathematics and science subjects that are difficult? One of the six, we've also seen that the Korea concentration, basically the educational expectations, has not, you know, declined, but increased.

Think about it. The diversity of jobs in our labour markets is rising, you know, we get more and more kind of complex jobs, modern differentiated kind of workplaces and so on. But actually, the occupational expectations of 15 year olds have narrowed, become more by myopic between the year 2000. In the year 2018, particularly so among girls now, think about it in 2018, half of the 15 year old girls look just for 10 jobs, among hundreds of jobs.

How can we change this? Now that brings me to the toughest part one i people prepared for the digital world. When we looked among older people, you know, 55 to 65 year olds, you can see in, on average, across countries, we're talking about one in 10, older workers, who were better protect, for those who are better prepared for the digital world.

They have, you know, problem solving skills with which they can manage complex digital information. country like the United States, New Zealand, we're better positioned on this, but overall, you know, actually, a lot of older people lack the skills they need for today's digital economy.

Now, I know you're gonna tell me, Well, that's all soft. And among, you know, the digital natives, the next generation has accumulated all of those skills that are required. And actually, yes, the bars get longer when you look at the skills of 25 to 34 year olds that we also tested in our server for Dell skills.

But if you look at it's close enough, not only talking about every second 25 to 34 year old, reasonably equipped for the world in which we live today. being integrated digital native doesn't imply that you have the digital skills that are needed to be successful in our world, in our economy.

And also the rank order of countries, it's changed quite dramatically. Look, you know, the United States used to be at the frontier among young people is just in the middle of the pack, not because things got worse, but because things got so much better, so much quicker, and other countries.

Very same picture for the UK, UK used to be at the frontier. That's why you know, workforce qualifications today are quite good. If you look at the incoming cohort, you know, moving into the labour market, things such as so so you see the opposite picture in a country like Singapore, you know, they used to be the laggards and the older generation or education was very limited.

Today, they're at the frontier together with countries like Finland, and Sweden. So the global talent pool is going to look very, very different geographically ended up across different groups.

The drivers behind those developments are not difficult to understand the kinds of things that are easy to teach easy to test routine tasks, you know, have also become easy to digitise to automate, to outsource disappearing from our labour market, technology intensive tasks are on the rise, you put the two things together, you get a pretty clear picture of the future of work. Some people call this a race between technology and education.

You know, before the first industrial revolution, neither technology in our education merit for the vast majority of people, people lived happily and self sufficient.

On the front end came the first industrial revolution, moving technology ahead of the skills of people and causing huge amount of social pain.

People that badly prepared for the new technologies. But then, you know, that's when we started to build, you know, education system, the kind of systems that we know today, making people compatible with the ideas of the industrial age and its credit generations of prosperity.

But if you're honest, you know, we haven't actually changed the model very much since those days and today, you know, we are seeing the digital revolution now once again, moving technology ahead of the skills of people and causing the same kind of social pain with young people leaving university was great degrees and having difficulty finding good work and at the very same time, employers say we cannot find people with the skills we need.

That's a dilemma we need to solve no more We once again know people ahead of the technologies of our times. You know, to put this in quantitative Trump's, when we tested, you know, literacy skills of adults, we found around 20%, you know, perform very poorly not 20% of adults in the OECD countries in the wealthiest countries, you know, have literacy skills that you would expect from a 10 year old child.

And you can say, well, for many, it looks better. For some it looks good. And for a few, it looks great. And then we ask ourselves a question.

And what if we asked, you know, modern computer, artificial intelligence to solve those very same problems that we gave to humans in this literacy test?

And actually, the answer is, the near term computer capabilities come close to the 70th percentile of humans. This tells us actually, many of the skills that we are developed developing today are quite commonplace. We need actually to become much better to develop a different skill profile.

Success is no longer just about literacy and numeracy. We need to think hard of providing people with a reliable compass and the tools to navigate with confidence through a world that is increasingly complex, volatile, and biggest capacity of people to imagine, to create, to resolve and manage tensions and dilemmas not to live with themselves to live with other people to live with the planet.

It's about cognitive, social, emotional resources that we need to develop, if we want to make people you know, you know, fit for the for the workforce of tomorrow. And for life of tomorrow.

Our education systems know how to educate second class robots, you know, people are very good at repeating what we tell them. We need to think harder about what makes us human, in the time of artificial intelligence, how we complement not substitute the artificial intelligence be created in our computers.

You know, today, our eyes are very much fixed on the pandemic. But actually, the future will always surprise us, you know, clearly, climate change is going to transform our lives more radically, then this pandemic, artificial intelligence is probably more disruptive than the pandemic, in many ways he cannot even imagine and then there'll be many other forces are transforming the context in which we learn a war.

We cannot predict the future. But we need to become better to think about alternative futures, to imagine to project to build scenarios for the future. If we are more agile if we are better capable to navigate out to alternative futures, but probably be better prepared for the future that will eventually materialise.

Let me know highlight a few of those scenarios. Of course, one of the scenarios is simply the status quo.

Now, our education systems will just you know, little bit improve gradual development. And you might dismiss this particularly now, after the pandemic, people say no, everything is going to be fundamentally different.

One, actually, you have said that many times in history, and actually our education systems have proved to be remarkably resilient to change the gap between what our societies expect and what education delivers, hasn't become narrower, it's become wider, not everywhere, there have been some countries with enormous change.

And if I look, for example, here is the average skill level in the older generation, you saw that before. And here's the skill level in the younger generation, you can see overall, you know, things have progressed on our survey of adult skills when we gave people a test. And in some countries, much more so than what you can see here, for example, Singapore started out, you know, very poorly now, and the young generation is doing quite well.

Children not moving from poor to better off, still very much behind but actually can see the progress. France, you know, moving from below average and the older generation, to average, you can see Germany, you know, studying where the older generation was about average, you know, generation is a little bit better than average, Lithuania, you know, New Zealand, but then you get to the United States. In the United Kingdom. The older generation performs reasonably well. The young generation doesn't do any better. Imagine this.

Young people in the UK moving into the labour market are no longer better skilled than those getting up for retirement and it completely changed labour market. So there is no inherent automaticity that our education systems we'll adapt to changing requirements.

That is something that requires a lot of policy initiatives. Education is a remarkably conservative social enterprise. And you know, sometimes we as parents are part of the problem, not part of the solution, we get very anxious when our children no longer learn what was very important for us, and they get even more anxious.

When they do learn things we no longer understand. Teachers are often more likely to teach how they were taught and how they were taught to teach him as a policymaker, you can lose an election of education when something small gets wrong, but you rarely win an election over education, because it's simply very, very hard, you know, takes a long time to translate, you know, good ideas into better outcomes.

Well, you know, another scenario, simply, you know, one day, education systems will crack apart under the pressures of, you know, acceleration, like everything else in the digital world, as people will start to, you know, walk with their feet, look for alternative education resources in their amazing opportunities for this.

Artificial Intelligence offers us entirely new learning experiences, making learning more interactive, more granular, more adaptive to the individual needs of individuals.

When you study mathematics on a computer, the computer can study how you study, and then you know, tailor learning environments, to your specific learning needs.

Evaluation and Assessment. You know, one of the biggest mistakes we've made in learning is to divorce learning, and assessment. You know, we pile up lots of knowledge. And then, you know, one day we asked students come back and tell us everything you learn in a very constrained, artificial, narrow environment.

And if you future, we can integrate learning and assessment, giving students instant feedback to help them learn better, giving teachers instant feedback for how their students are progressing. And helping policymakers understand something more about the effectiveness of education.

Learning Analytics gives educators so much better tools to see how different people learn differently and to embrace that learner diversity with more differentiated pedagogical practice.

But, you know, the reality is actually, when we looked at this, in our latest PISA study, that actually technology intensity tended to be negatively related to learning outcomes. Better technology doesn't automatically mean better learning outcomes. Sometimes it can make learning more superficial, technology is only as good as its use, we have to become much better to design pedagogies, around 21st century technologies.

In other scenarios, yet, schools become you know, more hubs of learning, integrating into a wider range of social functions. Now, you can see that in the Nordic countries, maybe in Canada, let me know, make one more scenario here.

And that is, you know, one day maybe every single unravel, and we will learn anywhere, anytime, any people will just be on their own, there will be so many devices around us that help us, you know, push us learning, you know, learning through our lives, in ways that we cannot imagine today.

But, you know, it can said likely today, this very, very live little investment in innovative capacity of our education systems. Global venture capital in the field of education is so tiny compared with adults, and it's so much concentrated, you know, 2014, it was mainly about a story about the United States nowadays, is mainly a story about China, Europe, you know, you can see this tiny kind of slipped in this trap, we're not actually making the investments to keep education innovating in a way that you would come to transform itself.

Last but not least, you know, we used to love to do the work now. And now learning has become the work. In the past everything used to be quite simply, you know, credit score, you go to a university or vocational education, you work and then you retire.

Well, in the future, we need to invest a lot more in earliest Yes. Now, we know that some of the social and emotional capabilities that are so transformational for people, I develop in earliest use brain sensitivity is highest.

And, you know, learning in the university sector needs to be a lot more open a lot more transversal. And then, you know, learning a working need to be integrated.

The future places of work will be future places of lightning. But that raises some really difficult questions for us. How is the additional funding shared between governments employed, and beneficiaries?

What are the incentives for people continue to learn? Who will set the standards? Who will accredit that learning? How will we recognise levels of skills?

Firms are learning environments, we need very, very different kinds of tools. How do we certify skills in a digital world? You know, everybody talks about microcredentials. But how do we build a more coherent currency that, you know, gets people moving and gets people you know, recognising investment in skirts and gets employers understand what employers can actually do? How do we diverse people, outside firms?

While the unemployed it's pretty clear, you know, government funding will probably pick the bill up for that. But you know, what about the people who are at risk of losing that job? Who's going to invest in today's truck drivers, then we know that their jobs are unlikely to exist and 20 years down the road?

Whatever we do, are people who want to change that jobs. What do we do about the gig economy where people are not so well organised in labour markets?

So that's a question we should be answering today. And new forms of work of means, you know, fewer forms of taxes, governments will lose a lot of you know, direct control when labour markets become more abstract mind form. These are the questions we need to be answering for tomorrow.

So all about you know, assessing risks and leveraging opportunities. What is the right balance between modernising and disrupting our skill systems? And how do we reconcile new goals, this old structures? How do we match the global was the local?

How do we, you know, advance and innovate our education systems in a very conservative social environment? How do we realise potential with existing realities, the existing infrastructures?

And how do we balance education and learning? How do we, you know, reconfigure this space as the people that time have the technology to educate learners for their future, rather than our past? Without you're going to find good answers for these questions at this conference? Thank you very much.