Engagement as a Productivity Indicator
5 minute read
The Federal Reserve Bank of Richmond is one of 12 regional Federal Reserve Banks that make up the U.S. central banking system. Mind Over Machines has enjoyed a close working relationship with the Richmond Fed’s Baltimore branch since our CEO Tom Loveland took on Maryland’s “tech tax” in 2007. Over the years, the Bank has come to count on our MINDs for a holistic view of tech in business and culture.
The Richmond Fed invited us to take part in an industry round-table to present on technology trends impacting the economy. “When we call on Tom and [VP of Innovation & Strategy] Tim Kulp, we know we aren’t going to get program code and industry jargon,” says Vice President and Regional Executive Andy Bauer. “Mind Over Machines helps us understand the latest in technology and how it is being used to transform the way businesses operate as well as the opportunities and challenges of technological change for the workforce.”
Cloud Computing & the Productivity Supply Chain
If you’ve ever heard Tim Kulp present, you know he tends to take accepted norms and turn them on their heads. The Richmond Fed round-table was no exception. There was no talk of robots coming for our jobs. Instead of focusing on the imminent transformative powers of AI, Tim examined the impact of the cloud computing transformation that’s already here. We always hear about ‘supply chain productivity,’ but have you ever pondered the productivity supply chain? And wouldn’t it just figure, the infernal IT industry that’s always disrupting would be the first to feel the effects of disruption?
The cloud is no longer for remote storage and operational savings. Today’s cloud computing accelerates innovation. The solution that would’ve taken your internal IT team months to build now comes pre-built and ready to snap into your ecosystem. Wow! This is going to make productivity skyrocket, right? Not so fast.
What happens to that internal IT team when hardware is replaced by DevOps and introverted code-junkie developers are tasked with project management? The productivity supply chain starts to crack. When workers feel accountable for results, they are engaged. Engagement breeds productivity. In a cloud computing environment, your IT employees aren’t accountable; Azure, AWS and Google are. Tech job unemployment is at record lows, but workers feel unhappy, unappreciated and unable to grow. They are disengaged. Productivity is suffering.
Education as Strengths Development
Education is the obvious answer. It’s the only thing that can keep all us lemmings from going over the productivity cliff. But maybe not the kind of “education” you have in mind. It doesn’t have to be all STEM all the time. In fact, it really shouldn’t be.
The World Economic Forum predicts the new AI-enabled economy of the not-so-distant future will actually create 58 million more jobs than it displaces. But how do workers prepare to be accountable, engaged, and thus productive in these new jobs? Tim advocates focusing on the liberal arts, mastering the things that make us most human, with STEM as a constant undercurrent providing the tools that enable humanity to excel.
Most of these Fourth Industrial Revolution jobs fall into a three-pronged typology. We will need trainers, maintainers and explainers. Trainers are the people who teach AI systems to do jobs. A couple examples from very different realms: If a customer service chatbot needs to be as human as possible, you need great actors coaching it. “We’ll also need master mechanics. If you can teach a robot how to fix a car – how to really fix it, not just how the manual says to fix it – you are just as valuable as the person who writes code for the robot,” Tim explains.
The Explainers are the people who marry data science knowledge with business process design. They bridge the digital and physical worlds. They’ll be the ones explaining why the algorithm made the decision it made on your home loan or your prison sentence.
Yes, the Maintainers are the computer scientists who keep the systems running. Certainly we will always need great STEM minds, but we shouldn’t be trying to turn everybody into one. It’s far better to identify your strengths – what you’re good at, what you love – and skill up for bringing that passion to the brave, new automated world.
To put it another way: It isn’t about the STEM; it’s about the roots. To be engaged and productive in an AI-driven economy, we need to get back to what makes us uniquely human. That’s the message Tim brought to the Richmond Fed, and it’s the message our MINDs bring to the business world every day.