Our clients care deeply about innovation and technology. We know this from our engagement with clients including discussions triggered by reflecting on the findings of the CSIRO's Workplace Safety Futures report.

Our clients care about "machines" (including "robots", artificial intelligence, biometrics and the harnessing of big data) being developed as a result of innovation and technology because of the unprecedented efficiencies and improvements in safety they unlock.

These benefits come with a potentially profound human cost. Depending on which research you turn to, the predictions are that between 9 and 50 per cent of jobs will be replaced by machines in the next decade.

This rapid pace of change has caused leading scholars to argue that some, if not a large majority of humans face a fate worse than redundancy: complete irrelevance.

The jobs of the future will involve "caring" and other "soft" skills machines can't replicate  

This sobering thought caused us to reflect on what the skills of the future should be to counter this impending irrelevance. The current thinking from some quarters (including most Governments in the Western world) is that science, technology, engineering and mathematics are the subjects of the "future" and that we should be teaching more students these subjects in our schools, technical colleges and universities.

Cybersecurity and understanding the potential vulnerabilities of machines and how to fix them is one growth area. Estimates are a near 40 per cent uplift in the number of people needed with these skills in the next decade.

At the same time, leaders of businesses are arguing that one of the hardest skills to recruit for is the ability of candidates to write and speak publicly to communicate ideas clearly. Chairman and CEO of Goldman Sachs, David Solomon, has said that "[h]ow you communicate with other people, how you interact with other people, how you express yourself will have a huge impact on your success".

The bigger question though is how we, as a society, prepare for the future?

Embedded in this question are further intrinsic questions around what it is that machines cannot do, or what it is that machines cannot do better than humans? An understanding of the answers to these questions is necessary if we attempt to protect ourselves from redundancy and, worse still, irrelevance.

It's heartening to hear that across all reports that communication skills remain valuable in the "new world" of work.  This is good news for lawyers and many professions.

Knowledge of machines + deep understanding of people = recipe to thrive

Perhaps the focus here should be on the things that, for now at least, machines can't replace. In the main these are the very things that make us human and make us feel. This includes the joy we experience through art, literature, movies, theatre, dance or music. It also includes the empathy we feel that comes from human care and kindness.

Leading organisation are already harnessing "blended" skill sets

Leading organisations with which we work have already recognised the need to combine a knowledge of machines with the "caring" and "feeling" skills, so called "softer" skills, that machines can't replicate. These organisations seek out and promote, through lifelong learning, essential skills in communication, creativity, innovation and intercultural competency.

The future is impossible to predict with accuracy. One thing though is clear –  the impact of machines on the jobs we have today is inevitable. If we set ourselves on a path to learn only the skills which machines can potentially replace, we set ourselves on a dangerous path.

Based on the inevitability of the machines replacing humans, combined with the focus on the "softer" skills associated with creativity, we are working with our clients to do just that get more creative.

Creativity is not only one of the key skills that will relate to employability in ever increasing ways but we are seeing employees seek out organisations that hold creativity as a core value. Why? They will be sustainable long term. We might care about machines, but as yet they don't care about us.

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