What future do we want?
Even before the pandemic, many significant changes were transforming the nature of work. Our processes were becoming more flexible, organic, responsive, and adaptive. The pace of work was speeding up, and the amount of information at our fingertips was dramatically increasing. We were also seeing changes in where we worked, moving away from fixed workplaces. And work was becoming more collaborative, networked, dynamic, and multidisciplinary than ever.
Fast forward just a few months and we are now seeing that enforced working from home has tested our agility and responsiveness to their limits. It has forced us to adapt to change more rapidly than we ever thought possible. And it has shone a light on where our existing technologies have been lacking, and how our work processes have needed reinventing.
As the pandemic has evolved, many of us have found that we’ve been able to be as productive as we were before, or even more so. But the picture is very mixed across the world, and for different kinds of work. And we’ve discovered that even for a knowledge worker with the most up to date technology, some kinds of work are more difficult to achieve in an all-remote world. Added to this, for many, the pressures of combining work and home life are proving to have profound effects on our health and well-being.
These radical changes, taken together, provide a unique opportunity to reflect and think deeply about the future of work that we want, and the kind of life that we aspire to as individuals, organisations and society. It leads us to ask how we can invent a more fulfilling future, and one that takes into account the broader scope of our lives, not just the hours we spend working. Part of this is developing technologies that ensure we support what people do best: being social, being creative, and using our insight, ingenuity, judgment, and emotional intelligence. We are freer to do this if the systems we build play to the strengths of digital technologies: connecting us across space and time, taking care of repetitive and routine actions in intelligent ways, securely storing vast quantities of information, constructing and mining large datasets, and creating new kinds of representations to which we can apply our judgment. By getting these human-machine partnerships right, we can move toward a human-centric future of work.