Pearson

The Future of Skills

The conversation about the future of jobs and skills is one of the most important in education.

A student entering formal education today will be making decisions about their career by 2030.

But wait, we already know about the future of jobs. The robots are taking them, right?

Let's take a step back.

Anxiety about workers being replaced is rampant.

But fear of automation is nothing new.

Fears of technologically-driven unemployment have arisen throughout the centuries, usually provoked by a disruption, like the Industrial Revolution.

But historically, technology creates more jobs than it destroys.

Of course, we don't know if it will be different this time.

But we do know that automation is only one part of the story.

Equally important are other interacting trends including: changing demographics, urbanization, globalization, inequality, political uncertainty, and climate change.

What do we mean by interacting? Consider for a moment, the following:

Urbanization and globalization are trends that are interacting with, and component parts of, climate change, all of which are driving the green sector.

Currently the green economy is creating new jobs faster than jobs are disappearing in the polluting sectors.

But in the face of increasing inequality, the high consumer cost of green energy could slow demand and job growth.

In addition, investments in green technologies are deeply intertwined with government policy, making prospects even more uncertain.

Understanding how these trends interact is clearly complex.

It is also critical to understanding the jobs and skills needed in the future.

That' why Pearson teamed up with researchers from Nesta and the Oxford Martin School to move the conversation past automation.

Our forward-looking research combines the best of human expertise with the power of machine learning to understand the trends and make more nuanced forecasts than previously possible.

What did we find?

The future of work is brighter than you might think.

And what's the best way to prepare for the future?

We invite you to explore the the Future of Skills: Employment in 2030.

Michael Osborne, Dyson Associate Professor in Machine Learning, University of Oxford:

So in 2013 we wrote a paper looking at the future automatability of current employment and as part of that we held a workshop in Oxford to ask some of the best people we knew about what they could see in the technical trends and how that was likely to affect the future of work?

Subsequent to that analysis we were quite often asked what that mean for skills and education? And we didn't really have clear answers. So it's really a pleasure to be involved in this project, which puts that question, the future demand for skills at its center.

Hasan Bakhshi, Executive Director, Creative Economy and Data Analytics, Nesta:

So in recent years a number of people have come to Nesta, and come to me and asked for my advice on what sort of skills areas the government should be focused on and developing its workforce? This research is important because in a very interesting and novel way generates predictions and actionable insights that policy makers can act on.

Previous studies which have looked at the future of work tend to focus on how automatable or not an occupation is. Our research is distinguished from those previously students by focusing on skills. And skills is something that whatever job you're in there's something that you can do about. And if you invest in the right skills you can leave yourself in a better place to benefit from the opportunities of the future.

So if there's one thing we can say with any certainty about the future is that it will look very different to the past. So that high degree of uncertainty is an environment in which governments, individuals, employers are trying to make their decisions about skills and investments and occupations.

John Fallon, CEO, Pearson:

The importance for people to be always learning throughout their career, the importance of collaborating, of working as parts of teams, developing those higher order cognitive skills, where you can interpret, analyse, make connections between seemingly different pieces of information, and persuade others of your argument, that you can provide good service and insight, that you can can emphasise, and care, and be concerning of others. These are skills that are going to be in greater demand than ever.

Methodology

Predicting the future of employment has itself been a booming growth sector in recent years, with analyses often designed to guide public sector and business investment and training policies. But we believe ours is the most comprehensive and methodologically ambitious to date.

We have developed a novel methodology for predicting the demand for work and skills in the US and UK economies in 2030, one that combines the expertise of humans with the power of machine learning. This enables us to forecast quantifiable directional predictions for occupation growth. In addition, we have identified the skills, knowledge types, and abilities that will be most likely experience growth and decline. Importantly we have grounded the analysis in structural change likely to affect US and UK labor markets in the coming years.

Laurie Forcier, Director, Global Thought Leadership, Pearson:

So there are two major things that make this project different. One is that it focuses not just on automation but on a whole host of megatrends that are influencing the future of work and skills, and what we might expect to see happening in the future. The second is that it combines human expertise with the capabilities of machine learning to be able to provide us a more nuanced view of the jobs and skills that we will be needing in the future.

Geoff Mulgan, CEO, Nesta:

The role Nesta has played in this has mainly been in pulling together some of the research and methods working with Oxford University and others. We have quite a strong team and a strong tradition of doing data-driven research and we were particularly keen to use some new methods of gathering together large data sets, but combining them with both expert groups, human intelligence, as well as machine learning to make sense of the patterns.

Hasan Bakhshi, Executive Director, Creative Economy and Data Analytics, Nesta:

So our research starts from three key facts. The first is that we ground our predictions in a historical analysis of what has driven the the labor market, and occupational change in the labor market. The second feature of our research design is that we go to the main experts in various aspects of structural change and tease out from them what are the implications for employment in the future? And thirdly we use machine learning and complex non-linear models to understand the interaction between skills and occupations.

And it’s these three key features of our research design that sets it apart from previous research in this area.

Micheal Osborne, Dyson Associate Professor in Machine Learning, University of Oxford:

As a machine learning expert myself obviously I was interested to see machine learning used to answer this question about the future demand for skills. So the advantages that our group brings is firstly its ability to capture non-linear interactions and that’s particularly important we think when considering skills, in that we know it’s not just a single skill or a linear combination of skills that’s going to be important in the future. It’s really those more subtle interdependencies between skills that will determine just how important that future demand will be.

Also our algorithm is explicitly acknowledging that uncertainty that exists in these quite complex developments, and finally of course our algorithm is run in an active learning way meaning it is interacting with those human experts in the the room, its kind of testing whether those labels they’re given us might be more or less certain, checking that it’s picking the true underlining trends, and ultimately yielding slightly more accurate predictions as a result we hope.

Foresight Workshops

At the foresight workshops, panels of experts - 12 in the US and 13 in the UK - were presented with three sets of ten individual occupations and invited to debate the future prospects of each in light of the trends. The first set of ten occupations were chosen randomly. Participants assigned labels to the occupations according to their view of its future demand prospects (increase, stay the same, or decline), as well as the level of confidence associated with their responses.

To sharpen prediction, an active learning method was implemented: the subsequent sets of occupations to be labeled by the experts were chosen by a machine learning algorithm. Specifically, the algorithm chose occupations in areas of the skills space about which it was least certain, based on the previous information it had received. This process was repeated twice to generate a training set of 30 occupations.

Predicting Jobs

We used all the labels (or predictions) assigned by our experts to train a machine learning classifier, which in turn generated predictions for all occupations. To do this, we relied on a detailed data set of 120 skills, abilities, and knowledge requirements against which the U.S. Department of Labor's O*NET service "scores" occupations (we also map this data to UK occupations using a "cross-walk").

Predicting Skills

Together with the predictions about changes in occupational demand, the O*NET data permitted us to forecast the skills that will most likely experience growth and decline. Using linear and non-linear analyses, we were also able drill down into the skills (and skill combinations) that are predicted to drive demand for the future.

Translating for Action

We interpreted the results of our analyses with particular attention to the discussions of our experts at the foresight workshops. Finally, we converted these insights into actionable implications for educators, employers, and individuals - both from a policy and a practice perspective.

Findings

We've translated the findings of the research to understand what the future of skills and employment in 2030 might look like, and why. Understanding the implications of the research will be vital to preparing for future demands.

John Fallon, CEO, Pearson:

We've just commissioned a major piece of academic research to look at what the world of employment looks like in 2030, and what that tells us is that for the overwhelming majority of jobs and professions, it's all up for grabs.

Laurie Forcier, Director, Global Thought Leadership, Pearson:

So there's a real debate, particularly in the UK, about what's more important: knowledge or skills. And so one of the real exciting things about this research is that it provides an underpinning based on the research that proves positive that it is the combination of knowledge and skills together that will be important and that will serve learners, and workers, well in the future.

Geoff Mulgan, CEO, Nesta:

There's a huge amount of fear, anxiety and uncertainty about what can happen to jobs in the next few years. People are worried that waves of automation might sort of destroy their life opportunities so it seemed important to get greater clarity on what we could expect, what the implications should be for schools, for governments, or for individuals, teenagers perhaps themselves in terms of planning their lives and that had to be more detailed, more granular, more analytical about what is knowable, as well as clear about what things we can't know because they are just by their nature uncertain.

The main findings of this report are really about what we can expect, and they show that, yes, there are likely to be big effects of automation on some parts of the workforce, some jobs could if not disappear, see fairly dramatic reductions in numbers. It also shows some parts of the labor market are highly likely to see significant growth, perhaps some slightly surprising parts of the labor market like many public sector jobs in teaching, or healthcare and in private services fields like hotels, hospitality, food and so on, are highly likely to grow.

There's then a big group in the middle where you simply can't be certain what is going to happen to those jobs but probably, one of the messages of this report is we'll see new redefinitions of jobs so some jobs will remain in some respects the same but have to learn new skills including skills perhaps of using; AI, robots, etcetera to enhance their work rather than replacing the work. And that can be everything from cleaning jobs, to legal jobs to civil service jobs to managerial jobs, to engineering jobs, are not likely to disappear but they are equally unlikely to remain exactly as they are.

Laurie Forcier, Director, Global Thought Leadership, Pearson:

The future of jobs and skills is one of the most important conversations in education. Our systems currently, right now for the most part, aren't prepared to get people ready for what's coming, particularly as people increasingly will be called on to work alongside smarter, digital tools and will be asking them to emphasize more the aspects and the attributes and the skills and the knowledge and the abilities that make them more human.

John Fallon, CEO, Pearson:

There are a number of groups that need to be paying attention to research like this. Pearson does, it needs to shape everything that we are investing in and all the products and services we are developing in partnership with others. Universities need to be paying attention. Schools and school boards need to be paying attention, parents need to be thinking about this, employers need to be paying attention; everyone who's involved in shaping the world of jobs, economic opportunity needs to be thinking hard and long, and more importantly they need to be acting on what this study is telling us.

Full Findings

We forecast that only one in five workers are in occupations that will shrink. This figure is much lower than recent studies of automation have suggested.

Occupations related to agriculture, trades and construction, which in other studies have been forecast to decline, exhibit more interesting and heterogeneous patterns with our research, suggesting that there may be pockets of opportunity throughout the skills ladder.

We forecast that only one in ten workers are in occupations that are likely to grow.

These jobs are in sectors such as education and healthcare, where the overriding effect of technology is likely to be an improvement in outcomes, not a reduction in workforce. Therefore, as trends such as demographic change raise demand for these services, the prospect for employment is also likely to rise.

We forecast that seven in ten workers are in jobs with where there is greater uncertainty about the future. However, contrasting the negative outlook of other research, our finding indicate that we can do a great deal to help people prepare for the future.

Our findings rank knowledge areas, skills, and abilities that will be in greater demand in the future. These findings, if implemented by educators and employers, can help individuals better prepare for the workforce of the future.

See Implications for more information on the skills that will be in demand, by occupation group.

Although there is already broad understanding that "21st century skills" will be in demand, this research leads to a far more nuanced understanding of which skills will be in greatest demand.

In the US, there is particularly strong emphasis on interpersonal skills. These skills include teaching, social perceptiveness, service orientation, and persuasion.

Our findings also confirm the importance of higher-order cognitive skills such as complex problem solving, originality, fluency of ideas, and active learning.

In the UK, skills related to systems-oriented thinking (i.e., the ability to recognize, understand, and acton complex sets of information), such as judgment, decision-making, systems analysis, and systems evaluation also feature prominently.

See the Glossary of Skills for more information on how each of the skills, knowledge areas, and abilities is defined.

Our research definitively shows that both knowledge and skills will be required for the future economy.

In our US results, knowledge and skills are fairly equally represented in the top half of all features we ranked according to predicted future demand.

In the UK results, the ranking leans more towards skills than knowledge, but not by a wide margin.

Occupations and their skill requirements are not set in stone. Occupations can be re-designed to pair uniquely human skills with the productivity gains from technology to boost demand for jobs.

For example, we know that eventually robots will be able to build bridges and diagnose diseases. But humans will retain the unique ability to engineer a bridge and care for a sick child. How we balance those skills with technology productivity will chart the course of our workforce.

Top 10 Occupations

The top 10 occupations predicted to experience increased demand through 2030 are as follows.

US

  • Preschool, Primary, Secondary, and Special Education School Teachers
  • Animal Care and Service Workers
  • Lawyers, Judges, and Related Workers
  • Postsecondary Teachers
  • Engineers
  • Personal Appearance Workers
  • Social Scientists and Related Workers
  • Counselors, Social Workers, and Other Community and Social Service Specialists
  • Librarians, Curators, and Archivists
  • Entertainers And Performers, Sports and Related Workers

UK

  • Food Preparation and Hospitality Trades
  • Teaching and Educational Professionals
  • Sports and Fitness Occupations
  • Natural and Social Science Professionals
  • Managers and Proprietors in Hospitality and Leisure Services
  • Health and Social Services Managers and Directors
  • Artistic, Literary and Media Occupations
  • Public Services and Other Associate Professionals
  • Other Elementary Services Occupations
  • Therapy Professionals

Top 10 Skills

The top 10 skills, abilities, and knowledge associated with rising occupations as follows.

US

  • Learning Strategies
  • Psychology
  • Instructing
  • Social Perceptiveness
  • Sociology and Anthropology
  • Education and Training
  • Coordination
  • Originality
  • Fluency of Ideas
  • Active Learning

UK

  • Judgment and Decision Making
  • Fluency of Ideas
  • Active Learning
  • Learning Strategies
  • Originality
  • Systems Evaluation
  • Deductive Reasoning
  • Complex Problem Solving
  • Systems Analysis
  • Monitoring

Implications

This research on the future of jobs and skills has implications for education systems, employers, and individuals. Some of the ideas described below are already being explored; our findings provide research support for these strategies. In addition, the research points to new areas for exploration by Pearson and our fellow education stakeholders.

Implications for Education

The research findings have significant implications for education systems around the US and UK:

Moving Beyond Generic Definitions of "21st Century Skills"

Education systems will need to support better understanding, teaching practice, and assessment of the granular skills that will be in greater demand.

Developing Pedagogies to Support Dynamic Knowledge and Skill Development

Educational institutions will need to provide supports to educators as they are asked to teach these new skills. This could require significant retooling of teacher education or faculty incentives in educational institutions.

Adapting Faster to the Changing Needs of the Labor Market

One thing that is clear from the research is that the pace of change will continue to accelerate. Education systems developed 20-30 years ago will actually need to plan for a future 20-30 years away.

Offering More Flexible and Adaptive Pathways

As the pace of change accelerates, learners will demand more ways to convert learning to earning. Although there will likely always be some demand for traditional brick-and-mortar experiences, more learners will want accelerated and flexible pathways, such as credentials or badges.

Implications for Employers

Employers serious about resolving future uncertainty for their workforce will need to think about:

Redesigning Roles to Balance Technology and Human Resources

The path to maximizing productivity will be through the effective use of technology to supplement uniquely human skills. In education, we talk about technology supplementing (not supplanting) the educator to personalize learning. This will be true in many other industries as well and employers will need to proactively redesign the jobs most at risk.

Moving Beyond the College Degree as the Primary Signal of Employability

As education systems offer more flexible and adaptive pathways for learners, employers will also need to learn how to identify and develop talent. The college degree has long been an imperfect signal for employment readiness and this is likely to become even more complex.

Implications for Individuals

Despite its technical nature, this research has a very human angle. It forecasts impacts of megatrends on real people and the findings provide a roadmap for how to thrive in the future workforce. Individuals will need to:

Develop Skills that are Uniquely Human

Although the advance of automation and artificial intelligence may feel like a losing battle to some, individuals will need to focus on developing the uniquely human skills identified in this research, such as originality, fluency of ideas, and active listening.

Commit to Lifelong Learning and Reskilling

The pace of economic change all but guarantees that a single degree started in your teens or a career picked in your 20s will not be everlasting.

Redesigning Occupations

We know that occupations and their skill requirements are not set in stone. But we often, as educators, employers, and individuals, lack the hard data we need to help us prepare for the future with intentionality and purpose.

Unlike other studies that have focused on whether or not an occupation will be automated in the future, our work includes a deeper look into the specific skills that we anticipate will help drive occupation demand in the future.

We know intuitively that it is likely we will increasingly be called upon to pair our uniquely human skills with the productivity gains from technology. But how should occupations be redesigned to maximize this traits, and how should education change to prepare us?

The innovative research methodology that our researchers used in The Future of Skills: Employment in 2030, allows us to predict for each sub-major occupation group in the US and UK, the three skills, abilities, or knowledge areas that would most drive:

  • A rising workforce share (e.g., complementary features), and
  • A falling workforce share (e.g., anti-complementary features).

This data is shared for the US and UK below.

Future Workers

One of the exciting things about this research is that it allows us to think about the occupations which may emerge in the future in response to the drivers of labor market change considered in the research. The model allows us to identify hypothetical occupations that are 'almost certain' to experience an increase in workforce share and the combination of skills that are most associated with it.

The following example workers demonstrate these hypothetical occupations identified from the model - four for the US and two for the UK. In the full report, we look at the occupations existing today that are 'closest' to these hypothetical occupations in order to understand more about them.

Our future workers help to show how the future of work could bring new opportunities and create new challenges. Each worker's profile shows their hypothetical occupation, that has been identified by our model, and the skills, knowledge and abilities features that are associated with their job.

Faisal

  • 2030 Age 32 (19 in 2017)
  • Location Daytona Beach, Florida
  • Sex Male
  • Job Careworker (mostly works with elderly)
  • Sector Health and social care

Skills/Tasks

  • Customer and personal service (K)
  • Static strength (A)
  • Service orientation (S)
  • Biology (K)
  • Arm-hand steadiness (A)
  • Problem sensitivity (A)
  • Active listening (A)
  • Extent flexibility (A)
  • Oral expression (A)
  • Manual dexterity (A)
  1. (A) Abilities
  2. (K) Knowledge
  3. (S) Skills

Trends

  • Rise in healthcare spending
  • Ageing in home
  • Increasingly ageing population
  • Greater dependency ratios
  • Immigration
  • Protectionist sentiment
  • IoT
  • Robotics
  • Need for productivity gains in these areas

After finishing school Faisal had to support his elderly parents, navigating care offers and supporting them emotionally. Through a government supported vocational course in health and social care he built on this experience to become a certified personal care assistant. While key skills requirements have not changed much over the past 15 years, the tools and scope of the job have . He is not just a care assistant: he is a cook, a dog walker, a cleaner, a companion, a health and wellbeing monitoring assistant and sometimes the first responder in case of emergencies.

The care profession has continued to boom, in part because robots do not possess the traits which make humans good carers such as compassion, humour, patience and flexibility; however, pay, working conditions and the status of the profession have not necessarily kept pace. To differentiate his services, Faisal performs a number of technical tasks. A preference for ageing at home means that one of his first roles is helping clients to physically adapt their homes, decide on what kinds of home assistive technology systems they will need and how that data will be used.

This includes giving advice on wearable technology to measure blood pressure, blood-glucose and sleep patterns for which Faisal has taken advantage of free training in biology. This information is available to him 24/7, helping catch potential issues before they lead to a hospital trip but equally, if not more importantly, it frees him to spend more time as a companion during home visits.

Faisal is also increasingly finding supplemental work outside of elderly care. A wider industry has risen up demanding many of the same skills to support working families manage their homes and lives. He does this on a freelance basis for the more well off families of the older clients he has come to know but is also exploring other opportunities.

Lisa

  • 2030 Age 39 (26 in 2017)
  • Location Anaheim, California
  • Sex Female
  • Job Green construction
  • Sector Construction

Skills/Tasks

  • Building and construction(K)
  • Customer and personal service (K)
  • Static strength (A)
  • Manual dexterity (A)
  • Arm-hand steadiness (A)
  • Administration and management (K)
  • Stamina (A)
  • Education and training (K)
  • Multilimb coordination (A)
  • Oral comprehension (A)
  1. (A) Abilities
  2. (K) Knowledge
  3. (S) Skills

Trends

  • Custom construction
  • Smart infrastructure
  • Urbanization
  • Green infrastructure
  • Climate change
  • Local production and distribution
  • Global demographics
  • Age in home
  • Political uncertainty

Lisa has worked in the construction industry for almost 20 years now. Entering the workforce during the Great Recession of 2007-09, she saw that green construction was one of the few segments which proved resilient to the slump in the construction market. After completing an apprenticeship program, demand for her services grew -initially in the commercial space but subsequently in the residential and industrial markets. The promise of lower costs, coupled with the ambition of some states for new homes to be net zero energy was an important catalyst for this growth as was the growing association of green homes with healthier living by consumers. While federal environmental regulation has made planning difficult at times, third-party standards such as the Leadership in Energy and Environmental Design (LEED) have helped spread awareness and trust in the marketplace.

A substantial part of Lisa's work has involved remodelling and refurbishment projects -from fitting water-efficient appliances, such as dual-flush toilets, or systems which reuse grey water to installing roofs with solar photovoltaic panels and even vegetation. Gig work, already prevalent in the construction industry, has become even more important, putting a high premium on strong administration and management. These skills have enabled Lisa to deliver a closer integration of subcontractors and the supply chain, resulting in reduced waste and performance improvements. Other nontechnical skills such as customer and personal service have been helpful in supporting and often pushing clients to take a long-term view of their 'green' investment.

Due to robust demand for green construction, labour shortages have emerged. The industry has not been able to shake off the reputation as physically dangerous, cyclical and low on job security. To encourage entry into the field, Lisa, who now runs a small company, has expanded the number of apprenticeships on offer, supported by government grants. She also serves as a local construction ambassador, visiting schools and attending careers fairs to give young people a real life perspective of what it is like to work in the industry.

Julia

  • 2030 Age 25 (12 in 2017)
  • Location Lafayette, Indiana
  • Sex Female
  • Job Aerospace Engineer (still in school)
  • Sector Engineering

Skills/Tasks

  • Engineering and technology(K)
  • Science (K)
  • Written comprehension (A)
  • Critical thinking(S)
  • Design (K)
  • Reading comprehension (S)
  • Operations analysis (S)
  • Complex problem solving (S)
  • Inductive reasoning (A)
  • Deductive reasoning (A)
  1. (A) Abilities
  2. (K) Knowledge
  3. (S) Skills

Trends

  • Biotechnology
  • 3D printing
  • Local production and distribution

Julia has always had an interest in science thanks to plenty of hands-on experiences in and outside school, though she really credits her secondary school chemistry teacher for giving her the confidence to pursue a career in the sciences. She chose to study Materials Science Engineering at University and had the opportunity to do work experience in two newer sectors where companies are keen to attract talent; bio-engineering and small-scale, custom manufacturing.

Julia's main interest, however, lies in aerospace. Additive manufacturing has had a considerable impact on the sector, reducing the cost and weight of aircraft structures. It calls for a better understanding of how bulk properties are created and affected by these new production techniques since materials are synthesised at the same time as aircraft parts. There is plenty of space for exploration for material engineers, especially as additive manufacturing opens the door to new forms of biomimicry, the borrowing of ideas from nature -everything from the sweeping curved shape of a bird's skeleton to the riblets on a shark's skin- to inform technological development,

This, however, is not the only reason Julia is attracted to the job. Arguably the biggest impact of new materials and manufacturing processes has been to bring design and manufacturing closer together. As there is a much wider design space to roam, designers, material engineers, system modellers and production workers benefit much more from iterating and exchanging skills, practices and knowledge. Julia's company recently announced that it would be reshoring some production capabilities and investing in the surrounding industrial ecosystem to exploit these synergies further.

Julia thrives in such an environment, communicating ideas and working across diverse teams. She particularly likes the idea that while she remains first and foremost a materials engineer, she is also actively helping shape the design of aircraft which she'll one day get to see in the sky.

Amit

  • 2030 Age 65 (52 in 2017)
  • Location Towson, Maryland
  • Sex Male
  • Job Part time non-traditional post secondary teacher and part time 100 year life counsellor
  • Sector Education and counselling

Skills/Tasks

  • Education and training (K)
  • Oral comprehension (A)
  • Social perceptiveness (S)
  • Written comprehension (S)
  • Reading comprehension (S)
  • Customer and personal Service (K)
  • Philosophy and theology (K)
  • Oral expression (A)
  • Speaking (S)
  • Complex problem solving (A)
  1. (A) Abilities
  2. (K) Knowledge
  3. (S) Skills

Trends

  • Ageing population
  • Technology
  • Millennials

After losing his job as a newspaper journalist, Amit switched careers and retrained as a community college teacher. His background in communications stood him in good stead when teaching increasingly important skills such as collaborative problem-solving and interpersonal skills. He was struck by the growing number of mature students who wanted and needed to re-skill in response to transitions in their lives. In particular, these changes were causing some students anxiety as they perceived education as a young person's game. He found that skills he had honed over the years as a journalist and then teacher such as social perceptiveness and the ability to convey complex ideas in an understandable way were very useful in advising mature students.

Amit recognised that this was only the tip of the iceberg: longer healthier lives and changes to pension age and the notion of retirement were disrupting the classic three stage view of life; education, work and then retirement. In its place is a set of unsettled questions: How can individuals develop productive assets when most education occurs in their 20s? How can they protect the value of these assets over the next 60 years against a backdrop of profound structural change? How can they balance the financial need for an extended working life against other important goals, such as family, health and friendships?

Some individuals have seized the opportunities presented by these questions to explore who they are and how they want to lead their lives; however, others have found them overwhelming, anxious they might make the wrong choices or break social taboos. Amit began to work with these individuals - helping them to imagine possible future selves and think through their implications for sequencing a multi-staged life. Sanjay has taken self-directed training courses in applied philosophy and ethics as well as reflective practices to enrich the advice that he is able to give to clients.

This support has extended to end of life issues which remain among the most traumatic events that individuals and loved ones face. The old adage that there are no atheists in foxholes may be an exaggeration but Amit has discovered that the search for meaning or purpose or value, remains central to many individuals. This is especially true as the increasingly complex and technical aspects of healthcare have narrowed what services are available. Amit is proud that his work has gone some way to filling this gap.

Wilson

  • 2030 Age 45 (32 in 2017)
  • Location Edinburgh, UK
  • Sex Male
  • Job Immersive experience designer
  • Sector Creative economy

Skills/Tasks

  • Fine arts (K)
  • Originality (A)
  • Design (K)
  • Fluency of ideas (A)
  • Visualization (A)
  • Sales and marketing (K)
  • Customer and personal service (K)
  • Arm-hand steadiness (A)
  • English language (K)
  • Visual colour discrimination (A)
  1. (A) Abilities
  2. (K) Knowledge
  3. (S) Skills

Trends

  • Technology
  • Millennials
  • Inequality

Wilson studied fine arts mixed media at university. This provided an environment in which Wilson developed an awareness of the diversity of media and media practices. By the end of his studies, Wilson was convinced that some of the most exciting developments in culture lay in digital technology. He enrolled on a 12-week course at a bootcamp where he deepened his knowledge of 3D design software for modelling, animation and rendering. Wilson chose this training pathway over postgraduate work as it focussed on the specific tools that he would be using in industry and exposed him to how projects worked in practice.

The games industry was an early adopter of virtual reality (VR) and Wilson quickly found a job with a small developer creating alien landscapes. As with any new technology there were growing pains. The holy grail of VR gaming, at that time, was designing an authentic first-person shooter (FPS) which permitted aiming and freedom of movement without causing motion sickness. A solution eluded Wilson's design team, though it provided him with a stream of challenges on which to cut his teeth and learn by doing at a time when industry knowledge was too fragmentary and constantly changing to be standardised.

As virtual, augmented and mixed reality technologies entered the mainstream, so industries such as healthcare, tourism and sports to education and manufacturing began to seek workers with Wilson's skills. Wilson was approached by a number of recruiters, though an old friend from art school convinced him to join his e-commerce start-up which was using new technologies to enhance shopping experiences and reduce the guesswork that accompanied buying new products. To this end, Wilson took a series of accredited online courses in sales and marketing which gave him an insight into how consumers make decisions and how to manage that journey from a behavioral and creative perspective.

After several years Wilson joined an education company which he believed was a natural home for his skills. Immersive experience technologies provided a way to teach complex concepts visually and motivate users who otherwise struggled with traditional learning methods. Wilson is very excited about the future -not only about the possibilities for these tools in STEM subjects where learners can interact with computer-generated objects but also in fields such as literature, history and economics. For example, a soon-to-be-launched product transports students to the mills of nineteenth-century Manchester as they read about the demand for social reform, an experience which Wilson hopes will give them a deeper connection and understanding of the beliefs, goals and values of their ancestors and other historical actors.

Mel

  • 2030 Age 52 (39 in 2017)
  • Location Manchester, UK
  • Sex Female
  • Job Restaurant owner
  • Sector Catering and hospitality

Skills/Tasks

  • Originality (A)
  • Fluency of ideas (A)
  • Judgment and decision making (S)
  • Active learning (S)
  • Oral expression (A)
  • Oral comprehension (A)
  • Active listening (S)
  • Sales and marketing (K)
  • Critical thinking (S)
  • Service orientation (S)
  1. (A) Abilities
  2. (K) Knowledge
  3. (S) Skills

Trends

  • Technology
  • Ageing population
  • Urbanization
  • Millennials
  • Local production

Mel has owned her own restaurant for many years and worked in the catering industry for even longer. The convergence of new technology and changing demographics, however, has dramatically shifted when, why and how people go out to eat as well as their relationship with food. More and more people, especially the elderly live alone and are opting to eat takeaways at home rather than go out. And many of them are not content with a greasy pizza in a crumpled box but expect greater variety and quality.

Mel felt that this delivery model had commercial promise in the higher end of the market. To make food exclusively for delivery, however, required an overhaul of the restaurant's service and operations. Mel brought considerable judgement and decision-making skills to bear on this task. She implemented a real-time dispatch algorithm to track riders and orders and identify which rider was best placed to fulfill the order. This slashed the restaurant's delivery times and allowed it to serve customers that other competitors could not reach without compromising food quality. In turn, this data was used to analyze customer preferences to keep menus fresh and profitable.

This asset-light business model allowed Mel to trial new recipes without severe or lasting penalties. Ideas could be terminated and Mel could move on without sinking substantial resources. Despite the appetite for food delivery, Mel came to the conclusion that the restaurant was still a viable proposition; it just had to be reimagined to appeal to a growing number of consumers who were turning their backs on big ticket items and seeking out experiences that could create a longer lasting sense of fulfillment.

Mel reached out to a number of contacts she knew from her earlier catering career for inspiration. As with other forms of creative endeavour, this involved people from different disciplines -everyone from designers and anthropologists to performance artists and experimental chefs. In Mel's view, having smart people was as, if not more, important than having good ideas. Her role was to listen and try to understand the thinking behind each suggestion and turn them into a coherent vision and clear instructions that her staff could implement.

Thanks to this collaboration, Mel has created a very successful series of experiential dining events. She has done away with the traditional separation between dining room and kitchen. Upon entering the restaurant, guests instantly smell what's cooking for that evening's dinner. They are also invited into the kitchen among the pots and pans where the chefs share stories and give bespoke cooking tips. Guests are occasionally asked before hand to reveal something personal that evokes a culinary memory. This is then incorporated into each guest's meal. Mel hopes to branch out into food tourism which she believes is the next step for those who want to understand the producer-to-plate story while aligning themselves with values, such as sustainability and local production.

About

Pearson teamed up with researchers from Nesta and the Oxford Martin School to build a research project that moves the conversation about the future of work past automation.

Our forward-looking methodology combines the best of human expertise with the power of machine learning to make more nuanced predictions about the future of work and skills than ever before.

We're the world's learning company, with expertise in educational courseware and assessment, and a range of teaching and learning services powered by technology. Our products and services are used by millions of teachers and learners around the world every day.

Our mission is to help people make progress in their lives through learning - because we believe that learning opens up opportunities, creating fulfilling careers and better lives.

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Nesta is an innovation foundation - backing new ideas to tackle the big challenges of our time. Nesta sees a world full of potential, where new ideas solve the big challenges that matter to everyone. The foundation seeks out, sparks and shapes powerful new ideas, joining with others to take on the big challenges of our time and shift how the world works for everyone.

nesta.org.uk

The Oxford Martin School at the University of Oxford is a world-leading center of pioneering research that addresses global challenges. The center aims to make an impact by taking new approaches to global problems, through scientific and intellectual discovery, by developing policy recommendations and working with a wide range of stakeholders to translate them into action.

oxfordmartin.ox.ac.uk

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