I’ve noticed a trend recently with a lot of AI-related features being added to software. They’re being branded as “copilot” solutions. Yes, Microsoft Copilot was the first to use the name and the rest are just trying to jump in on the brand recognition, much like using “GPT” last year. The word “copilot” is so generic that it’s unlikely to be to be trademarked without adding more, like the company name or some other unique term. That made me wonder if the goal of using that term was simply to cash in on brand recognition or if there was more to it.
No Hands
Did you know that an airplane can land entirely unassisted? It’s true. It’s a feature commonly called Auto Land and it does exactly what it says. It uses the airports Instrument Landing System (ILS) to land automatically. Pilots rarely use it because of a variety of factors, including the need for minute last-minute adjustments during a very stressful part of the flight as well as the equipment requirements, such as a fairly modern ILS system. That doesn’t even mention that use of Auto Land snarls airport traffic because of the need to hold other planes outside ILS range to ensure only one plane can use it.
The whole thing reminds me of when autopilot is used on most flights. Pilots usually take the controls during takeoff and landing, which are the two more critical phases of flight. For the rest, autopilot is used a lot of the time. That’s the boring sections where you’re just flying a straight line between waypoints on your flight plan. That’s something that automated controls excel at doing. Pilots can monitor but don’t need to have their full attention on the readings every second of the flight.
Pilots will tell you that taking the controls for the approach and landing is just smart for many reasons, chief among them that it’s something they’re trained to do. More importantly, it places the overall control of the landing in the hands of someone that can think creatively and isn’t just relying on a script and some instrument readings to land. Yes, that is what ILS was designed to do but someone should always be there to ensure that what’s been sent is what should be followed.
Pilot to Copilot
As you can guess, the parallels in this process for using AI in your organization are a good match. AI may have great suggestions and may even come up with more novel ways of making you more productive but it’s not the only solution to your problems. I think the copilot metaphor is perfectly illustrated with the rush to have GPT chatbots write reports and articles last year.
People don’t like writing. At least, that’s the feeling that I got when I saw how many people were feeding prompts to OpenAI and having it do the heavy lifting. Not every output was good. Some of it was pretty terrible. Some of it was riddled with errors. And even the things that looked great still had that aura of something like the uncanny valley of writing. Almost right but somehow wrong.
Part of the reason for that was the way that people just assumed that the AI output was better than anything they could have come up with and did no further editing to the copy. I barely trust my own skills to publish something with minimal editing. Why would a trust a know-it-all computer algorithm? Especially with something that has technical content? Blindly accepting an LLM’s attempt at content creation is just as crazy as assuming that there’s no need to doublecheck math calculations if the result is outside of your expectations.
Copilot works for this analogy because copilots are there to help and to be a check against error. The old adage of “trust by verify” is absolutely the way they operate. No pilot would assume they were infallible and no copilot would assume everything the pilot said was right. Human intervention is still necessary in order to make sure that the output matches the desired result. The biggest difference today is that when it comes to AI art generation or content creation a failure to produce a desired result means wasted time. In a situation with an autopilot on an airline making a mistake in landing the results are more horrific.
People want to embrace AI to take away the drudgery of their jobs. It’s remarkably similar to how automation was going to take away our jobs before we realized it was really going to take away the boring, repetitive parts of what we do. Branding AI as “autopilot” will have negative consequences for adoption because people don’t like the idea of a computer or an algorithm doing everything for them. However, copilots are helpful and can take care of boring or menial tasks leaving you free to concentrate on the critical parts of your job. It’s not going to replace us as much as help us.
Tom’s Take
Terminology matters. Autopilot is cold and restrictive. Having a copilot sounds like an adventure. Companies are wise not to encourage the assumption that AI is going to take over jobs and eliminate workers. The key is that people should see the solution as offering a way to offload tasks and ask for help when needed. It’s a better outcome for the people doing the job as well as the algorithms that are learning along the way.
