THE HISTORY & CURRENT STATE OF AI

These days, it’s almost impossible to have a conversation without AI coming up. Whether you realize it or not, it’s made its way into nearly every part of our lives. Maybe your kids are using it to help with homework, your company is exploring it to boost efficiency, or — if you’re anything like my wife, it’s become your interior decorating assistant. You’ve probably even heard the question, “Did you try using AI for that?” more times than you can count.

Here’s the thing, AI might feel like a brand-new technology, it has roots dating back to the 1950's just 5 years after the development of the worlds first computer ENIAC. It has a surprisingly rich backstory that shows us how we got here and hints at where things are headed. So before we look at what’s next, let’s quickly look back.

The 1950s

During this time, interest in AI grew within the computer science community. Alan Turing published his landmark paper “Computing Machinery and Intelligence,” where he posed the now-famous question, “Can machines think?” Around the same time, Arthur Samuel developed a checkers-playing program that could learn and improve independently — one of the earliest examples of machine learning. And in 1956, John McCarthy organized the Dartmouth Workshop, where he coined the term “Artificial Intelligence.” That workshop is widely considered the birth of AI as a formal field of study.

The 1960s & 1970s

This timeframe showcased some massive progress in the industry. The first industrial robot, Unimate, began working on a General Motors assembly line in New Jersey, an enormous step toward automation in manufacturing. Around the same time, Joseph Weizenbaum developed ELIZA, a program designed to mimic a psychotherapist by responding to typed text. He called it a "chatterbot" — which is honestly a better name than the one we stuck with: "chatbot. We also saw early experiments in autonomous vehicles, most notably The Stanford Cart, a robotic system that could navigate obstacles independently. This era is often seen as the foundational phase — laying the groundwork for much of the AI innovation we see today.

The 1980s & 1990s

As breakthroughs in AI continued to accumulate, public interest and funding started to waver, until a few landmark moments brought the spotlight back. One key moment you may remember is the legendary chess match in 1997, in which IBM's Deep Blue defeated world champion Garry Kasparov, marking the first time a computer beat a reigning champion under standard tournament conditions.

Around this same period, AI systems began tackling increasingly complex tasks. For example, expert systems like ALACRITY were developed to analyze thousands of rules for strategic decision-making.

The 2000s

The 2000s ushered in a wave of technological innovation, with AI playing a quiet but critical role behind the scenes. This decade gave us the first generation of the Roomba. This robotic vacuum could navigate rooms and avoid obstacles on its own. NASA successfully landed two Mars rovers, Spirit and Opportunity, both used onboard AI systems to autonomously explore and navigate the Martian surface without constant human control. Meanwhile, companies like Facebook, Twitter, and Netflix began integrating AI into their business to personalize content, recommend media, and optimize user engagement, laying the foundation for much of what we experience today. 

The 2010s-Present Day

This period aligns most closely with what we experience in our everyday lives — the rise of AI-enhanced consumer tools, more intelligent search engines, and the widespread use of terms like “Deep Learning” and “Big Data.” The 2010s saw major milestones, including the release of virtual assistants like Siri and Alexa and rapid advances in machine learning. In 2015, public concern around AI’s military applications gained traction when Elon Musk, Steve Wozniak, Stephen Hawking, and over 3,000 others signed an open letter urging world governments to ban the development of autonomous weapons. Around the same time, Facebook conducted an experiment in which two AI chatbots tasked with negotiating started using a non-standard form of English to optimize their communication.

Perhaps most notably, OpenAI released its public language model — GPT-3 — which wasn’t the first of its kind but was by far the most powerful and realistic. It could generate human-like writing with uncanny fluency, marking a turning point in public awareness and the adoption of generative AI.

*The Future

*Looking forward, the future of AI isn't just about faster algorithms or smarter chatbots — it's about redefining what’s possible. In the next 5 to 10 years, we’ll likely see AI woven into nearly every business function — from fully autonomous customer service agents to AI-augmented strategy teams making data-driven decisions in real time. Personalized AI assistants will become as common as email, capable of scheduling, writing, researching, and even managing digital relationships. Creative industries will be reshaped as AI co-authors stories, designs, videos, and music at scale. In the medical field, AI will help diagnose conditions before symptoms arise. Education will shift toward AI-powered, hyper-personalized learning. And as AI grows more capable, regulatory frameworks, ethics debates, and AI-human collaboration will move from tech circles into boardrooms and households alike. The future isn’t just automated — it’s intelligent, adaptive, and increasingly collaborative. The only question is: are we prepared to lead it, or be led by it?

To showcase how powerful AI is this final "The Future paragraph was written and copy/pasted solely from ChatGPT4o. "We asked AI what it considered the future of AI will look like"