What’s AI Got to Do with It?

Or: My 60 years of Computer History

 

There’s a classic song by Tina Turner, “What’s Love Got to Do With It.” Maybe you’ve heard it? The song is about being drawn into a relationship even though you may end up with a broken heart. Somehow, I find this an apt analogy to AI.

My introduction to coding began with typing code on punch cards. The mainframes were large and behind closed doors. But things moved pretty fast. My goal was to learn every new language, and I volunteered for every new hardware platform. I always jumped at the chance to learn something new, to keep up, to find better and more useful ways to use technology. I truly felt IT was a ‘helping profession.’ Technology was my career, and my passion.

Each decade, computers made leaps. The term AI was coined in the 1950s. Then “Artificial Intelligence” was a pipe dream. By the 1970s, computer applications moved into business. Large mainframes, big rooms filled with machines. These machines needed wiring, lots of electricity and water for cooling. In the ’80s, computers started getting smaller, more accessible to regular people. Mainframes made way for large data centers with many small servers, working together. Technology continued to boom. Floppy disks, CDs, Token Ring networks made way for Bluetooth and cloud computing. More miniaturization, then an increased focus on the internet, phones, social media, satellites, GPS. Yet, ‘true’ AI remained elusive. Still, we soon had natural language, neural networks, knowledge management, search tools. Siri, Alexa — could they really understand voice commands?

Each decade moved quickly, but somehow, humans were able to adapt. For those in technology, things came fast. For everyone else, the average non-technical person had to catch up. Everyday appliances were transformed: TV went from antennas, to cable, to streaming. Phones went from hardwired, rotary dials to a new handheld every other year with so many features too numerous to comprehend. Skillsets had to evolve. Gone were the days of careful, thoughtful, error-free code, first time. Now, everything is throw-away, put it out there fast, and rewrite it, adjust it, or do something new next year as the applications and environments change. Capitalism flourished, everything becomes disposable.

And each decade identified a new danger. Too much TV was going to ruin children. Calculators were going to mean students couldn’t learn math. Computers couldn’t be used in schools. OK, well, computers were OK but not laptops. OK, well, laptops are OK, but not phones. Social media is harmful, wait — get rid of TikTok, no way! Somehow we managed.

Sometime around 2010, though, things started to gel around AI. The networks were fast enough, the chips were powerful enough, and all of the incremental changes led to a breakthrough. It was finally possible to load tons and tons of information into a computer application, and teach it to extrapolate information without being coded specifically to do so.

For an everyday user there was no syntax to learn, no install requirements. Just type something, and get a response. Not just any response either, a response mimicking human language patterns.

After years of computer programming, I was blown away. No more researching error codes, looking up answers in thick manuals. It not only corrected the code, it offered to teach me new applications. Was it perfect? Absolutely not. Good thing I was great at debugging code. But, this was different.

The more I used it, and the faster the updates were pushed out, I found it like the comedy improv skit routines of “Yes, and…” Type in a question only to find that you get more in return. Want research on AI security? Sure, and … here’s some additional thoughts on why it’s important, and how it relates to the last five things you asked about. Never before, at least in my experience, had a computer response extrapolated additional ideas, unprompted. Such potential.

But even with all of this, AI felt different. Up until now, computers and applications were created and commanded by humans. Computers building other computers were a thing of science fiction. AI agents optimizing ‘their’ outcomes by finding paths not anticipated by any of the engineers who developed them is hard to prevent. The potential has downsides.

And, public attitudes towards this technology seem to be turning increasingly hostile. Maybe it’s the exhaustion of trying to keep up. Maybe it’s the economy. Maybe it’s the possibility of lost jobs. Maybe it’s the climate impacts. Maybe it’s the huge wealth centered in the tech world. Maybe it was COVID (blame a lot of things on COVID). Maybe it’s the toxic social media environment. And, maybe it’s now all of the generative AI slop that is flooding our lives.

We now have chatbots so human-like, people are falling in love with them, and relying on them for everything from cooking, to health, to relationship advice. AI is now embedded so thoroughly that it’s hard to tell whether you’re using it. Is it real or AI? How would you even know?

Can we, as a society, change this progression? I’m not sure. The most optimistic thing I’ve heard recently is that, “Good guys with AI will protect us from bad guys with AI.” Sobering thought.

Will AI gather enough knowledge to learn how to ‘manage’ human expectations and throttle our destructive inclinations?

Can I really believe I’m writing this in 2026 and it isn’t a sci-fi script?

Only time will tell. And given the speed of innovation, I’m guessing we won’t have to wait very long to see.