Demographics, Data, Robots and Creativity

Updated: Jul 25, 2020

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Why is lifelong learning going to become even more important as people age and life expectancy grows? How susceptible is your job to computerisation? What percentage of work time might be automated? Is the future of teaching the use of robot tutors? Does creativity matter, and can it be taught and learned?

We have a wide-ranging exploration and discussion about work and learning this week. We look at how demographics are changing, why we'll work longer and how lifelong learning will no longer be an optional extra. We also look at two data sets that examine which jobs are susceptible to automation, and how much time is at risk of automation within different professions. Next we look at some research which examines the pros and cons of using robots to assist learning, and where this technology currently stands. And finally we discuss creativity, often stated as an essential ability for success in an uncertain future. We explore whether it can be learned, and how one of the best in the creative business provided us with a model to follow. Let's begin!

It's not only innovation and technology that has started disrupting how we work and live - it's also demographics. An ageing population and slowing birth rate in Europe means that more people will be supported by those who work. However as life expectancy rises so do the number of people who can continue working as they age, lessening these demographic effects. The ability to keep working will be important.

This generation of workers will need to be highly adaptable and skilled, as they will be pursuing their careers through one of the biggest transformations in how humans work in history. Most forms of routine work will likely be automated, and this automation brings huge uncertainty to those who are not prepared.

The ability to gain technical knowledge and a capacity for lifelong learning is built on a foundation of understanding of text and numbers, and this article argues that those who do not have this foundation face a highly uncertain future. As we've read recently, in the past it's been possible to have a well-paid job with no qualifications, but as these jobs are lost they are not always replaced with equivalent positions, and that's a problem for those who are unable to anticipate, learn and adapt quickly.

In addition to this foundation is that "Long and productive working lives start with building sound foundational cognitive and social-emotional skills from early childhood through secondary education." Children and young people need to learn how to think and get on with each other, regardless of social, cultural or economic contexts. They have to learn to inquire and be curious, and function effectively and sensitively as human beings.

Something a bit different here. In 2013 Carl Benedikt Frey and Michael A. Osborne published a report titled "The Future of Employment: How susceptible are jobs to computerisation?”. This site takes the data generated from the report together with further information from US Department of Labour statistics, and lets the user find out how susceptible their job might be to automation. It could also be an interesting tool for school leavers to use. The original data might be starting to get a little out of date now given how rapidly things are changing, but it's interesting nonetheless.

Further to this and based on analysis by McKinsey, this interactive demonstrates the automation potential of US jobs as a percentage of time that could be automated using adaptations of currently demonstrated technology. At the 90-100% we see production jobs such as machine setting and routine assembly work, food production, and machine operating jobs in industries such as mining.

Jobs in retail, construction and administrative support could see up to 50% of current work time automated, with teachers and other education workers having up to about 20% of their time potentially automated.

This would be fascinating to share with a group of students to see what conclusions they would draw from this data and whether it might affect decision making about their future plans, or prompt them if they don't have any. The days of leaving school and getting a factory job will soon be gone, and the sooner we get our young people joining this conversation the better.

Here's an interesting piece of research which explores how robots can be used in education as tutor or peer learners. It consists of a meta-analysis of all available literature on robots in education from several sources according to certain criteria. Findings include that social robots have been shown to have promise in assisting learning and have a physical presence that online technologies lack and students respond to, but they are not yet able to respond to speech effectively and develop a natural flow of interaction. Currently, robots that support educational practice are specialised, and although serious technical and logistical challenges exist we may one day see them alongside teachers as part of the learning infrastructure.

What are your thoughts about robot tutors being used to support learning?

As the world of work changes rapidly and the competencies people need to thrive in the new workplace evolve, we often see 'creativity' listed as an essential skill that all must learn and embrace. But what is creativity, and can be learned?

Walt Disney has been well recognised as a creative genius, and his method of discovering creative ideas and turning them into reality has been modelled and is being used by creative teams to generate, evaluate and critique ideas and solve problems.

The strategy is based on the three modes of operating that Disney's colleagues observed in him: the dreamer, the realist and the critic. The dreamer shares ideas and dreams without criticism or restriction, and all ideas are recorded and accepted. The realist asks how logical planning can be applied to the ideas and then can be turned into reality. The critic seeks to identify barriers and obstacles to the plan.

Disney's team never knew which mode Disney was going to adopt in any meeting on any given day, and as such they learned to operate within all three modes almost simultaneously, thereby disseminating Disney's method and flair for creativity across the organisation. The model in this articles seeks to systemise Disney's creative approach and immerse teams within a creative process.

Can this process, or any other be learned? Of course it can. Can creativity be learned? To varying degrees almost certainly, and cognitive barriers to creativity can be reduced or removed. Do our students have the opportunity to become immersed in and practice the application of creative models as they go about their work at school?

Thank you for joining us this week. Please don't forget to comment on our articles and posts - we want to share ideas, critical thought and constructive feedback.


#Research #Competencies #Lifelonglearning #Modernworkplace #Robots #Work #ArtificialIntelligence #Automation

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