Partnering with machines: 4 scenarios for the future

Following on from yesterday's post about the impact technological innovation and change will have on the workforce, this post is about 4 possible scenarios for the future of work as jobs become increasingly automated.  Yesterday's post was about the 2 trends evident today:  the rise of smart machines and the decline of full-time employment.  This post projects into the future, to 2040, and looks at how these trends might play out and how education will need to change in order to adapt to these futures.  There may be either low or high technological displacement, and governments may take an active or passive role in these changes.  I have adapted the graphic in Redefining Readiness for the Era of Partners in Code from KnowledgeWorks.

Scenario 1 - Partnering for Mobility
In this future automation has eliminated some jobs and changed others, however at the same time new jobs have emerged.  While manual tasks are mostly being done by machines, there is still the need for high-value services.  The most common employment is "mosaic careers" and jobs are those that rely on completing short-term projects lasting several months to a year.  Companies use predictive analytics to project their workforce needs, and provide skill development to meet their needs, so reskilling and upskilling are constant.  The defining characteristics of this future are:

• partnerships between people and machines
• data-driven feedback to help people develop mosaic careers
• workforce analytics that support the design of adaptive career pathways
• more emphasis on micro-credential and certificates
• lifelong learning

Impact on education:  schools and universities need to help students develop human-machine partnerships in ways that augment and leverage their uniquely human capabilities.

Scenario 2 - Checking for Upgrades

In this future workers are seen as "professional nomads", charting their own paths, juggling multiple contracts and moving from one short-term project to another, where they build their own capacity and professional networks. Jobs are tied to the emerging needs of organizations that are reconfiguring work processes by using AI and smart devices, as in general employers concentrate on doing more with less people.  Full-time positions, if they can be found, are likely to average 1-3 years.  Keeping current with digital tools will be necessary in these integrated environments, along with building a solid reputation and strong support networks.  In this scenario low-skill workers are likely to scramble to keep up with the rapid pace of change.  The defining characteristics of this future are:

• extensive human-machine partnerships leading to fewer full-time employees
• individuals must take responsibility for staying relevant
• a mixed response to the new automation infrastructure

Impact on education:  educators will need to learn about AI and schools need to foster flexibility to prepare students for ongoing learning in uncertain environments.

Scenario 3 - Finding New Meaning

In this future AI and automation enable a new social infrastructure in which paid work is just one of several options (which implies some sort of universal basic income to buffer people against changing economic conditions).  In turn this may lead to more opportunities for meaningful work with social purpose, such as relationship-intensive caring roles.  Such roles as nurses, educators and care providers will combine AI with human expertise.  In this future with mass production of cheap products, more value may be placed on unique artisanal products.  Community infrastructure projects may be compensated in the form of vouchers or credits for goods and services.  With less traditional careers, education will need to reevaluate its purpose.  The defining characteristics of this future are:

• a human-centred economy that drives growth in the arts and civic projects and in the caring professions
• education shifting to more emphasis on personal growth rather than skills needed for the job market

Impact on education:  schools will need to prepare students for a world in which paid work may not be the primary organizing principle and will need to promote lifelong learning.

Scenario 4 - Working the Platforms

In this (dystopian) future there will be intensive automation and extreme taskification with workers being involved in fragmented short-term work.  Low-skilled workers will need to compete for jobs locally, whereas middle-skilled workers will be competing globally for professional and knowledge work.  University degrees will be regarded as luxuries, and most people will find jobs through work-life logs that give evidence of quantifiable performance metrics.  There will be chronic unemployment and under-employment, and a shrinking tax base will lead to strained public infrastructure and services.  The defining characteristics of this future are:

• extreme taskification
• quantified workers heavily monitored and evaluated through data capture and analytics
• traditional certificates and degrees replaced by work-life logs showing proof of experience

Impact on education:  the focus will be on helping students cultivate their personal brands and on reputation management.

Personally I find this final scenario very difficult to contemplate!  The final 5 pages or so of the report deal with opportunities for education.  This is where I'm going to be focused for my next blog post.