At the Global Lifelong Learning Summit in Singapore1, I recently participated in a panel session on The Future of Work is Now: Workplace Learning for a Future-Ready Workforce. At the end of the session, we were asked for a final comment which led me to suggest, ‘if skills are the answer, we could be asking the wrong question.’ A couple of delegates found this intriguing and asked me to elaborate. I’m not sure I gave them a compelling answer but on reflection there are three related ideas I was trying to capture.
Upfront, is a worry that too much focus is on task skills and the quest to develop better models of skills anticipation in response to the changing skill needs of employers. Here, I’m not suggesting skills and the training they necessitate are not important, but I’ve long believed in the integrity of knowing and doing. The best defence in the face of workplace transformation and advances in smart machines, is for people to apply their knowledge to changing circumstances, rather than constantly trying to accumulate new skills to meet the immediate (and rapidly changing) needs of employers. If skills are for the tasks of today, knowledge is for the challenges of tomorrow. Knowing and doing both matter! This view is consistent with much of what we’ve heard in interviews with companies and other stakeholders in Finland and Germany. Sustaining the occupational labour market in Germany is not simply a legacy response based on exist institutional arrangements, but a significant source of productive value in a context of rapid technological innovation. In Finland, sustaining the connection between knowing and doing is integral to a trust model of innovation, where permission to think is more than having the skills to perform immediate tasks.
A related concern about the one-sided focus on skills, is that it often rests on the assumption technological change leads to more and better jobs than we’ve seen in the past. What is called Robotic Process Automation, for instance, is widely held as positive news for the workforce, taking the ‘robot out of the human’ by automating routine tasks to ‘free up’ workers to focus on more interesting aspects of existing jobs or freeing them up to retrain for new jobs. The same is assumed for those in middle-level jobs as routine cognitive and non-cognitive tasks are hollowed out. While presenting temporary challenges in retraining for new jobs, it’s viewed as part-and-parcel of a shift towards a knowledge-intensive, high skills future, where new technologies complement the workforce on a digital journey, harnessing the creative, problem-solving, and technical talents of the workforce.
While our research findings are in line with those rejecting the ‘end of work’ thesis – and its prediction of mass technological unemployment resulting from automation – it doesn’t mean there’s little need to worry about job opportunities in a world of smarter machines and smarter workers. What we are calling the ‘cognitive challenge’ is not limited to training the future workforce, but has far-reaching consequences for the ‘opportunity bargain’ that has shaped the relationship between education, jobs and rewards, over the last century.
We can see technologies advancing in key areas of cognitive work, but to see this as a competition between machines and humans to do clever things, such as playing chess or Go, is to miss the point. We also need to understand the role of new technologies in enabling the redesign of the production process whether in offices, schools, hospitals, factories, etc. Tasks that were thought to be part of ‘knowledge’ work continue to be captured in algorithms and software, with advances in AI and machine learning likely to accelerate current trends. But technology is not destiny, and we found evidence of different ways of doing things that can be more or less labour enhancing. The problem today, however, is that many companies, large or small, are adopting a technology first, cost-cutting approach. This is why the core challenge posed by the ‘cognitive challenge’ is to (re)design productive processes in ways that sustain job quality for more than a small category at the top of organisations. To put this differently, how do we create a new (sustainable) opportunity bargain to avoid the consequences of digital Taylorism. And for public policy the cognitive challenge begins by thinking differently.
This links to the final idea I was trying to capture in highlighting a need to think about ‘purpose’, which can easily get lost when we focus on employability skills. Discussions of ‘green’ skills can quickly get reduced to a tick box exercise of what is or isn’t a green skill, with little consideration of sustainable development or how to build a new rationale for lifelong learning linked to a sustainable future of work. The good news is that the Global Lifelong Learning Summit, included some interesting examples of how our thinking needs to be linked to the UN’s Sustainable Development Goals.
1 The Global Lifelong Learning Summit was held in Singapore on the 1st and 2nd November 2022. The summit is organized by the Institute for Adult Learning and SkillsFuture Singapore, in partnership with ASEM, ILO, OECD and UIL. The inaugural summit examined examine how different stakeholders – learners, institutions, enterprises, Government – can come together to enable effective lifelong learning as a means to raise long-term employability, through discussions on different approaches to lifelong learning, best practices, and opportunities for collaboration.