How to Prepare for Human-Machine Partnerships at Work
Why these authors say: become a valuable partner to machines surrounding you
(There have been many scary stories lately about how robots and artificial intelligence will increasingly replace human jobs in the coming years. So, you may be nervous about what the future holds for you and your career. In this excerpt from their new book Human/Machine: The Future of Our Partnership With Machines, technology consultants and authors Daniel Newman and Olivier Blanchard, share their insights and advice.)
Over the course of the next few decades, machine learning, smart automation and artificial intelligence will transform business operations as radically as the internet, cloud computing and mobility did. The principal difference between these two waves of technology disruption is their potential impact on job creation.
It isn’t all that difficult to see how new business solutions could decimate the white-collar workforce in the way that machine shop and manufacturing automation decimated the blue-collar workforce.
Agility Is Your Key to the Future at Work
Note our use of “may” and “could” rather than “will.” We don’t know how companies, workers, legislators and educators will manage this shift or how quickly they will adapt to this new paradigm, evolve to meet its challenges and turn threat into opportunity. What we do know, however, is that the more agile you are, and the quicker to adapt, the better your chances.
We choose not to treat humans and machines as competitors because they don’t have to be. They shouldn’t be.
Some will lose their jobs and never recover from that loss. Others will use this new wave of disruption to their advantage and come out ahead. The choice begins with a combination of awareness and will. Survival belongs to the most adaptable.
Humans and Machines Are Not Competitors
We choose not to treat humans and machines as competitors because they don’t have to be. They shouldn’t be. In our view, the most productive and ultimately rewarding role of machines is to augment human capabilities.
In order to understand how technological disruption can be an opportunity rather than a threat, ask yourself the most basic technological question of all: How can I use this technology to augment myself?
3 Ways to Prepare for the AI-Driven Economy
Here are actions we can all take to begin preparing for the coming AI-driven economy:
1. Focus on adaptation, not technology. While we cannot predict accurately what new technologies and business models will emerge in the next few decades, we can predict with 100% certainty that change is inevitable, and, therefore, that the ability to change quickly and efficiently is the most critical trait that every worker, decision-maker and organization must prioritize.
But, how do you learn to become adaptable? The same way you learn to do or become anything else:
- by identifying people and organizations that have done it well
- by studying what they did to get there
- by putting those lessons into practice and learning how to get good at it
2. In a world of automation, focus on being the most well-rounded human being you can be. Let us assume for a moment that the worst-case scenario is realized: work automation results in humans being forced to compete against machines rather than humans and machines working together symbiotically.
How would humans make themselves more valuable to employers? A) by being better at performing tasks that machines are also able to perform or B) by being better at performing tasks that machines are not well-equipped to perform. The answer is, of course, B.
What kinds of tasks are we talking about? Tasks involving leadership, judgment, insight, creativity, abstract thinking, intuition, empathy, cultural awareness, motivation, collaboration, encouragement, courage and strategic vision.
It stands to reason that human workers who can demonstrate exceptional judgement, creativity, empathy, intuition, awareness and vision will find themselves in very high demand, no matter how much machine learning, smart automation and artificial intelligence have infiltrated an organization’s business processes.
The best strategy for human workers may be to focus on what makes them better humans rather than on becoming better technology users.
3. Unless you are in a highly specialized role or a STEM field, familiarize yourself with a breadth of technologies and technology-use cases rather than a narrow stack of specialized tools. The quickest path to adaptability and agility is to become as versatile as possible. That means becoming comfortable and at least moderately capable with as diverse a portfolio of technologies as you can.
No matter how advanced machine learning, smart automation and artificial intelligence get in the next 30 years, they will not develop better complex business decision-making skills than humans. Incomplete information and programmatic biases will continue to limit machines’ ability to see the whole field. Additionally, they will always lack the context, nuance, instincts and critical thinking of humans.
The fix: adopt a human–machine partnership approach to solving it. If humans are limited in their ability to process vast amounts of data and crunch them quickly, humans can be exceptional at interpreting, validating, gauging meaningfulness and making sense of new information.
Principles for Every Job
The principles outlined above are industry-agnostic. You can apply them to every job.
If you happen to be an accountant and worry about machine learning, smart automation and artificial intelligence eventually taking over your profession, be among the first in your market to leverage these technologies to augment your existing capabilities (or simply scale them without hiring new staff), and start focusing on injecting more customer care and personal touches into your professional relationships to increase their value to customers, partners and stakeholders.
If you happen to be a physician or health care professional with an outpatient practice, be among the first in your market, hospital or group to automate tedious tasks (from appointment-scheduling to record-keeping); capture more patient data to create a more effective health monitoring and analysis practice; empower patients to use sensors, apps and data analytics tools on their own to better help you help them; and rely on prescriptive solutions to identify potential problems and treatments you might not have otherwise considered.
Where to Get Help
Human workers looking to learn about new technologies can do so at little or no cost by using search engines to identify and access sources of information ranging from videos, news articles, white papers and infographics to user guides, training manuals and demonstrations.
Training in the use of these new technologies can be a little trickier, but depending on where you happen to live, training programs may be offered at little to no cost.
If your employer does not yet offer the kind of training you are looking for, talk to HR about either creating that training or helping you gain access to it. If your employer is not helpful, reach out to professional organizations and see if they can help you. If they are not helpful either, reach out to technology providers directly, and ask about any training and acclimatization programs that might be available to you.
Invest in Learning — Now
We don’t want to make this all sound easy or trivial. What we also know is that the time and effort you invest in learning how to use new technologies and better partner with machines offer the highest probability of job security and career agility in the coming decades.
The more time and effort you invest in this now, the more opportunity you are likely to enjoy when machine learning, smart automation and artificial intelligence begin to replace human workers at a much higher rate of speed than they do now.
Your best bet is to become a more valuable human partner to the machines that surround you.
(This extract from Human/Machine: The Future Of Our Partnership With Machines by Daniel Newman and Olivier Blanchard is ©2019 and reproduced with permission from Kogan Page Ltd.)