15 years ago, I sat with Mind Over Machines Founder and CEO Tom Loveland in a General Motors plant north of Baltimore. We had come that day to learn about manufacturing innovation from the GM plant manager and UAW shop steward, who together taught us an important lesson in human-machine interaction.
“When that machine hits the factory floor, it’s only as good as its human operator.” It can only gain value with human fine-tuning–sort of the opposite of how your car loses value the second you drive it off the lot.
AI is a new piece of equipment, not a new Tahoe. Your work with AI determines the value of your AI. We say that AI is like a junior employee or an average student, because you have to invest time in their potential to maximize their contributions.
Here’s an example of kickstarting and then fine-tuning AI to work for a client, in collaboration with their internal expert teams:
You may wonder about AI that can do QA, code review, and documentation: doesn’t that replace the skilled human operator from the auto plant comparison? No, because work is being redistributed. The reconfigured workflow can help humans focus on the bridge between function and customer service and satisfaction. When repetitive work is taken care of, humans can observe, optimize, and use their strategic reasoning. What’s more, people can step back to think of what data hasn’t even been taken into the system before—this breathes new life into ever-important stage of gathering offline data for your system to use.
Adjustments will continue with your AI, just as you invest in the development of your employees for years or decades so they can do their best work.
The French scientific philosopher Henri Poincaré said: “No doubt it is hard for a master to teach what does not satisfy him entirely, but the satisfaction of the master is not the sole object of education. We have first to concern ourselves with the pupil’s state of mind, and what we want it to become.” He continues, “The educator must make the child pass through all that his fathers have passed through, more rapidly, but without missing a stage.”
We are teaching AI. We are working with AI. AI must work for us and with us. Our own learning and the learning of our systems depends on us.
Sam Hopkins is Senior Advisor at Mind Over Machines
