If your job is process oriented — for example, calculating make-goods for improperly filled orders — your whole department will be automated soon. Don’t let the pink slip surprise you. If you analyze numbers in Excel, craft a narrative about them, and move them around spreadsheets, your employable days are numbered. Any white-collar job you can learn to do in a few days, even if it takes a lifetime to master, is threatened. (Poker takes minutes to learn and a lifetime to master; so professional pokers players are at risk. Read “Can Alexa Lie?” for details.)
FOMO is driving adoption
Fear of missing out (FOMO) is motivating tech-savvy CEOs to get serious about data, prompting them to deploy machine learning systems across their enterprises as quickly as possible. No CEO wants to learn that their goods or services are losing market share because competitive offerings (built by both human and robot workers) are much cheaper. Soon, machine learning systems will become table stakes for every company — department by department, system by system, function by function. You might not recognize it’s happening until you’re laid off.
Industrial-scale automation is coming, but it’s not here yet. In the interim, some work will be fully automated, and some will still require human expertise. People will be needed due to limits of evolving technology, or because of cost/benefit, or simply because humans still need to be involved.
No matter how this unfolds, you must personally harness the power of machine learning, robots, automation, AI, cognitive computing, data science tools, etc., by partnering with them. To survive and prosper as robots take over the business world, you will need to become the best man/machine partner of your peers. Here’s how to start.
Step 1: Invent the future
Consider your job. Think about all the ways it may be done in the future. Anything is possible. Imagine AI is smarter than you are. Imagine robots can do anything. Imagine you are tasked with automating your job, every keystroke, every phone call, every in-person meeting — everything.
Write down which areas will most likely be automated first. It may only be small parts of the process. List everything you do and all your responsibilities, and write down how they will be done when machines rule the world.
Step 2: Start reading
Read everything you can about data, data science, machine learning, AI, and automation. Everything you need to know is available online. Find every company that is working on automating cognitive tasks associated with your business. Look for partners, vendors, consultants, well-read bloggers — anyone who can help you understand what you need to do. Immerse yourself in the subject. This is your new full-time job.
Step 3: Be “that person”
This is the hardest step. Dig deep. Become “that person” in your department who “knows this stuff.” Figure out where to use data for better decision-making and what tools to use to automate certain tasks, and then become expert in them. Your current lack of knowledge is unimportant. You can learn, so learn!
Step 4: Propose a test project
After you have figured out which vendors, partners, processes, tools, consultants and colleagues need to be combined to accomplish your test project, build a short, uncomplicated presentation (if needed) to articulate what you will try to accomplish and what benchmarks you will use to measure success. You will be surprised at how quickly management says yes. If management does not say yes, you are working in a company that is not going to exist much longer, so look for a job where you get permission to use your new knowledge.
Step 5: Show your results
Build another presentation that describes the problem you identified and solved with data science, data scientific research, machine learning, and the automation or
the automated systems you built, conscripted, used, partnered with, purchased, etc. Make it super easy and obvious to understand.
Step 6: Revel in your success and repeat
With your initial success will come a “hallway handle,” something that gets thrown around by two coworkers passing in the hall, like, “Hey, what are you working on?” “Joe’s data project.” Embrace it, own it, love it. It’s your pathway to gainful employment for the next decade and beyond.
This will work
One of the biggest problems facing white-collar workers today is a misunderstanding of man/machine partnerships. There is very little chance that robots (as we are defining them here) will take every white-collar job in the next few years. They don’t have to. They only have to take yours.
The way to prosper in an ever-more-automated world is to create your competitive advantage by becoming the best possible man/machine partner. If you let the machines do what they do best, combine that with what you do best, and, most importantly, demonstrate the value of you and your machine skills to management, you will not only survive the attack of the machines, you will be stronger for it.