Back when I first started working in IT, SAP was all the rage. Everyone wanted one, regardless of if they actually found the functionality available useful or necessary. And because of software consultancy, a lot of consultants made a lot of money making SAP implementations for purposes they were not suited for, sold to clients who didn’t know what they were buying, made by people who didn’t really know what they were doing. And so SAP got a bad reputation among a lot of developers. And business owners as well, to be honest.

The current situation with AI and Machine Learning reminds me a lot of that time. It seems like everyone has an opinion to offer on AI or an application to put Machine Learning to. Unfortunately, I’m also starting to hear a lot of people who don’t work in IT talking about how clueless tech bros are trying to solve every problem with Machine Learning. And often, they forget to listen to the people trying to say that they’re solving the wrong problem.

The thing is, as a developer, this is a super easy mistake to make. Most of the people I’ve met who stay as developers and don’t use it as a springboard to management love problem solving. It’s so easy to learn something new and be so excited to solve a problem with this new tool you’ve learned that suddenly every problem starts looking like a nail.

Lost Opportunities

So I have a confession; I am one of those developers learning Machine Learning and loving it and wanting to put it to use immediately if not sooner. It is honestly kind of addicting. It is such a satisfying combination of problem-solving and the kind of magic that programming can be at its best.

The thing is, this has happened before, several times. What follows has also happened before. It’s called AI Winter. The enthusiasm leads to hype which leads to disappointment which then leads to scaling way, way down on the research and development. And AI, even in its current forms, has so much to give us.

Are there ethical problems with our unrecognized prejudices carrying over? Absolutely. Are those problems going to be problems on steroids if not mitigated? You betcha! But those are all problems that can be mitigated as long as the developers are aware of them. The trouble being, of course, that unfortunately mostly the people developing AI and ML systems are the very people who cannot seem to admit that those prejudices exist to begin with. At least not in themselves.

While I hope that we are heading toward a golden age of AI and Machine Learning, I’m also worried that we are, instead, heading toward another AI Winter. And there’s still so much we could do with this technology.

What do you think AI and Machine Learning should be used for?