The past three posts of this blog series have been rather…bleak…in scope and communication. I’m not interested in adding on to the ever-increasing levels of dread this world has. Instead, let’s take a look at a different facet of automation: working with machines and tweaking your skills so that you’re irresistible to companies that have a ~50% machine workforce.
If you’re confused at what I mean by “machine,” think of any chatbot you interact with on a site like Zara. That is a digital chatting machine, or digital chatting robot, or a chatting robot—chatbot. If you need an example of a physical machine, search up a Tesla factory and take a gander at how many machines they have (literally) running around the place. Thus the need for sophisticated and meticulous machine interaction is born.
This is not my original idea, so I must give credit to the book, “Human + Machine: Reimagining Work in the Age of AI” by Paul R. Daugherty and H. James Wilson. This book, while being a fantastic read for anyone who is starting their journey in understanding the future of automation, takes a different approach at communicating how the world will change.
Instead of bleakness, or, as I like to refer to it, the “we’re all f***ed” attitude, the authors imagine a future where humans and machines collaborate efficiently and effectively. It’s not just their opinion, mind you—the first half of the book, around 101 pages, is dedicated to explaining the present state of human-machine collaboration (HRC), in retail, factory floors, call centres, etc.
To provide a slight spoiler to the book, this incredible chart is given:
The left block highlights the human-oriented tasks; the right block, machine-specific. The middle portion is the most interesting and prescient: tasks that require HRC. This is what should be the focus of all Millennials, Gen Z’s, and Gen Alpha’s. Becoming automated is one thing, one which I’ve discussed (almost) to death.
HRC, however, is totally different. Those who learn how to augment themselves with AI and, subsequently, are able to work well with AI would be the top contenders for companies. In this case, AI should be looked at as a collaborator rather than a replacer. The competition, then, will be with others who are equally- or better-suited to work with AI in the workplace.
Human skills, like emotional intelligence and body languages cues, are important in every role (after all, for now, humans are the dominant species on Earth—lizard people and aliens notwithstanding).
Machine skills, like coding, can be obtained with some focus, time, money, patience, and skill; trusting the majority of the global workforce to adopt programming skills for the foreseeable future is possible but unlikely.
The “missing middle” as the authors call it can adopt the best of both worlds. Using machines to better serve and interact with humans, while creating more powerful machines in the process, serves both parties equally.
How do you benefit? Similar to being totally replaced, understanding where machines—physical and digital—are heading is a crucial first step. What jobs are they taking? Which ones are they augmenting? Next, using the chart as a reference point, decide how you could augment your skills and capabilities with machines. How could you boost your productivity/output utilizing machine intelligence? What do you bring to the table regarding helping machine intelligence flourish?
The future of jobs isn’t about you; its about collaboration. In fact, it’s not unlikely that for your job interview, you’d be interacting with both a human interviewer and a machine that analyzes your posture, eye contact, tone, body language, etc. In the interview itself, you may be asked to interact with a machine/make recommendations on improving it. If you talk condescendingly to the machine, you could lose the job altogether—if you talk to it like a baby, you also may not get the job, but also creep the interviewer out. HRC is the future, whether you like it or not and whether or not you’re prepared.