As larger chunks of more professions are taken over by automation, where should you as a human worker look to add value?
Your workdays thus far have been filled with a lot of manual processes and administrative work. But now that so many of these traditional tasks are being completed by software and algorithms, what’s the next phase of human employment? As a futurist focusing on the workplace, I tell people that this is their opportunity to be more strategic, but what does that mean, exactly? I believe it’s time to zero in on these four skills that machines won’t do as well as humans anytime in the foreseeable future.
Leadership is commonly defined as the art of motivating a group of people to act towards achieving a common goal. I recently asked a few of my colleagues to describe the best leaders they know in one word, and heard “inspirational,” “persuasive,” “socially intelligent,” and “assertive.” Machines can learn a lot about our businesses and industries, and at some point soon, they will likely have more knowledge than even the most tenured and experienced human leaders. But will they understand the art of motivation? Will they be inspirational or persuasive in pushing others to do their best? Even if machines become super-intelligent, they won’t master human persuasion anytime soon. It’s hard to believe that a robot leader will be able to identify the exact combination of words that will encourage an employee to take a job he doesn’t want for the same amount of money. And it’s unlikely that human employees would be satisfied with a robot leader’s degree of personal trust and accountability.
Intelligent software can already put your photos together in an aesthetically pleasing design, re-create paintings similar to those done by Gaugin or Renoir, and even write a human-interest piece that resembles the one you read in the New York Times Magazine last week. But to date, it can’t reliably make a work that touches the human soul out of nothing at all. Rather, for the foreseeable future, machines will depend on humans to feed them rules and guidance before undertaking creative endeavors. They will also need humans to recognize whether the work completed by artificially intelligent algorithms is any good or whether the intention just doesn’t translate – because machines won’t know the difference.
In their paper, Judgment Calls, Accenture researchers Ryan Shanks, Sunit Sinha, and Robert Thomas commented that judgment is human work that involves applying intellectual curiosity, experience and expertise to critical business decisions and practices when the information available is insufficient to suggest a successful course of action. “Computers can certainly make choices based on data that is available to them; but that is a very different thing than a judgment,” they wrote. “Judgments are made based on values, and values emerge from our experience of life. Computers don’t yet experience a life as we know it, and so they don’t develop what we would call values. That places a fundamental limit on the roles that they can play in our lives and society.”
Intuition is the ability to understand and decide on a path forward based on instinctive feeling rather than conscious reasoning. Smart as they are, even sophisticated deep learning programs definitely lack certain instincts. On the other hand, the human digestive system and its neurotransmitters have a tight relationship with the human brain. In your professional endeavors, you should never to discount immediate, visceral reactions and to pay attention to the physical sensations that accompany work situations. For instance, if you feel on edge as you’re about to sign with a new business partner, it’s worth taking a step back and evaluating whether the deal is truly right for the organization.
What parts of your job have machines automated so far? With what strategic tasks do you now fill your day instead?
Posted in Team & Project Management, Team Productivity | Tagged automation, communication, creativity, deep learning, efficiency, human employment, human skills, Leadership, motivation, productivity, skill acquisition, technology