Automatic for the People

Seven predictions for the future of knowledge work

“The main business of humanity is to do a good job of being human beings, […] not to serve as appendages to machines, institutions, and systems.”

― Kurt Vonnegut, Player Piano

Since the advent of computing technology, countless divergent futures have been prophesied by visionaries in various fields, from economists to science fiction authors. Many of these projected futures have at their core the question: how will computing change society, and what will be the role of humans in work when machines have largely solved the bulk of repetitive labor? In short, what kinds of work will still be available, and how will we facilitate such work? We find ourselves tasked with confronting these questions not as some far-off fantasy, but right here and now.

Over a century’s worth of dystopian fiction (and cranky economists) has bestowed upon us a library of insights into the kind of future that we want to avoid. But what of what we want? The time has come to look at the immediate and near-term reality of society with its current technological maturity, and turn our minds to the positive side of the script. How can we transition humanely and intelligently into a new era of work that accurately aligns with and benefits from the freedoms and opportunities granted by technology?

“Prediction is very difficult, especially about the future,” is a Danish proverb once attributed to Niels Bohr, who aptly iterated the phrase during his attempts to unravel the miracles of the atom. Making predictions is indeed complicated, and all the more so when the system we are trying to predict is a complex one. 

The future of knowledge work is a complex system with many agents that interact with each other at small scales and then spontaneously self-organize to exhibit non-trivial global structures and behaviors at larger scales. It is — in a philosophical sense — a miracle of nature, and on a level such that any grand predictions on its course should necessarily be met with careful consideration. 

With this humbling backdrop in mind, below are my seven predictions for how knowledge work changes over the coming five years:  

1. Complex problems will dominate the workday, rather than routine tasks. Routine tasks that are characterized by mature process knowledge will be largely automated. Complex activities are more challenging. In these settings, workers must form teams with complementing skills and interact continuously to create and execute a course of action. The typical knowledge worker will be engaged in projects for about 80% of the time (up from today’s share of roughly 10%). Diverse teams are smarter when it comes to solving complex problems. An optimal mix of mind, experiences, gender, ethnicities, age, workstyle, and very importantly, pluralism, a tolerance for non-conformist views and divergent thinking will increase so-called cognitive diversity. 

Today, most project teams are rather homogenous and not cognitively diverse. Without finding new ways to facilitate heterogenous teamwork, these teams will inevitably fail to realize their enhanced potential for achieving complex, creative, and non-routine work together.

2. Recruitment will focus on soft skills, rather than hard skills. For both hiring and team assembly, hard skills will no longer be the primary selection criterion. Soft skills and in particular those that an organization or team is currently lacking will be actively searched for and added. Teams with the right blend of talent, personality, and motivation are built for their purpose. As a consequence, impressive credentials alone will no longer be sufficient to get the job. The result will be diversity in the ultimate sense of the word. 

Today, hiring and team selection are undermined by biases and poorly understood assumptions. Team members, while individually impressive, perform poorly together. Meanwhile, the search space when assembling a team is very narrow. Herein is where the need arises for a more all-embracing and holistic candidate search system that is able to identify opportunities for cohesive team action based on sound social principles, not mere human bias.

3. The talent pool will become global, rather than remain local. Talent is equally distributed and opportunities will soon be too. Technology is leveling the playing field and COVID-19 accelerated this development. A decentralized global workforce, the so-called ‘human cloud’, will grow further. This transition will be characterized by intense labor arbitrage in the digital services sector, analogous in scale and significance to the Industrial Revolution during the 18th and 19th centuries.

Today, hiring for a role is limited to the best candidates in an immediate area, or those, still fewer perhaps, who are able and willing to relocate within commuting distance to the office. The majority of the global talent pool is left out by default. But this will change, as it is even now changing before our eyes with rapid global adoption of remote working tools and technologies. Soon enough, the phrase, “Going to work,” might be rendered literally inaccurate; a relic of the past where we automatically perceived work itself as a physically distant activity, performed someplace else.

4. Teams will be distributed, rather than co-located. Technological and social developments will result in more agile and more decentralized organizational models. The Coasean case for large hierarchical, bureaucratic, and rigid organizations will be mostly gone. Talent will have more flexibility in how, when, where, and for whom it works. 

Today, most organizations have big offices for a largely overqualified and underutilized workforce. They can afford to be vague about the skills they need and they generally treat internal resources as if they were free. As distressingly inefficient that this is, there is also an easy solution at hand: administering human capital in ways that most closely align with the fluid nature of distributed teamwork.

5. Organizations will become ‘talent-light’ and hire on-demand, rather than entertaining an underutilized workforce. More knowledge workers will have at-will contracts and work on multiple projects for multiple organizations concurrently. This availability of on-demand talent will make medium-to-large-sized organizations shrink their workforce and become more ‘talent-light’. They will tap into the on-demand talent and deploy it dynamically if, when, and where required. 

Today, most organizations focus on in-person and synchronous meetings. Yet, if we are to enable meaningful knowledge work in a complex environment, there is an open and unfulfilled need to rethink communication strategies with a view to facilitating talent that can be hired and put to work at equal convenience to all parties. 

6. Most communication will be in writing, rather than verbal. A strong preference for verbal and synchronous communication excludes large parts of the population from their participation in the knowledge economy. Moving to written communication will allow organizations to seamlessly work across time zones. 

Today, most organizations are way out of their depth when it comes to managing workforce logistics, dynamically deploying talent, and building optimal teams. They will move away from a built-in expectation of synchronous communication (treating it as supplementary rather than essential to the communication process) in favor of an approach that encourages asynchronous communication at the core of team collaboration.

7. New algorithms will enable knowledge workers and organizations, rather than disable them.  Software solutions will tackle the problem of workforce logistics and build optimal teams that are fit for purpose. Those approaches will employ data-driven optimization algorithms to support unbiased and evidence-based decisions. In a fast-paced world, organizational survival depends on matching the right people quickly and efficiently to today’s problems. 

With the reward that large, even the most traditional and rigid organizations will change. This is why there is a need to start figuring out those algorithms now. Without sufficiently sophisticated and carefully created algorithmic engines, which are in agreement with everything outlined here, there will be little benefit gained from all the other advances in technology going forward. 

I’m optimistic about the future of knowledge work. Technology will enable organizations and knowledge workers alike, to transition and become more humane and more inclusive. Human capital will become tangible on a global scale and knowledge work will be ‘automatic for the people’. 

And please, challenge me! I’d love to read your suggestions for the shape of knowledge work in the comments below.