The Psychology of Viral Technologies

ChatGPT's success caught even its creators off guard. The technology itself wasn't new—it was just packaged differently. In her latest piece for Learning Curve, Rhea Purohit explores how psychological factors, rather than technical capabilities, often drive the adoption of revolutionary technologies. Drawing parallels between ChatGPT's meteoric rise and the original Macintosh's role in popularizing personal computing, she reveals how understanding human psychology might be the key to unlocking AI's true potential.—Kate Lee

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Nearly two years ago, on November 20, 2022, ChatGPT was released. 

The app went viral. 

The world was excited, scared, and maybe a little skeptical.

But for the first few months, executives at OpenAI were…confused. 

Why?

In purely technical terms, ChatGPT wasn’t a giant leap forward in the state of the art. In fact, it wasn’t new at all. OpenAI’s GPT models had been around since 2018, the original ChatGPT was a fine-tuned version of GPT 3.5, and most of the technology inside it had been available as an API long before its release. Even so, ChatGPT became one of the fastest growing apps on the internet, with an estimated 100 million monthly active users two months after its launch. 

OpenAI executives were bemused.

Jan Leike, who at the time led OpenAI’s alignment team, which worked on making AI systems behave as per user intent, said in an interview after the chatbot’s release, “I would love to understand better what’s driving all of this—what’s driving the virality…It’s not a fundamentally more capable model than what we had previously.” 

Later in the conversation, Leike answered his own question: “[W]e made it more aligned with what humans want to do with it.” He continued, “It talks to you in dialogue, it’s easily accessible in a chat interface, it tries to be helpful. That’s amazing progress, and I think that’s what people are realizing.” 

ChatGPT went viral because it wrapped AI’s growing potential in a remarkably familiar interface—chat. It didn’t create new capabilities, but presented existing ones in a different way. ChatGPT redefined our relationship with AI as a culture—and what moved the needle was a change in the way we think about LLMs, not the raw power of the technology itself.

The technical barriers to advances in AI matter, but the psychological ones that hold us back from adopting them are just as important. Even the most sophisticated models might fail to deliver on the promise of AI if the average individual, for deeply human reasons, decides not to use them. Let’s take a closer look at the psychology of how we adopt new technology as a culture—and how that influences the way we build with AI, and use it in our work and lives.

History doesn’t repeat itself, but it rhymes 

Revolutions are sometimes grounded in shifts in perception. This is not a new idea—twelve years ago, advertising messiah of the Ogilvy Group Rory Sutherland echoed a similar world view. “The next revolution may not be technological at all, it could be psychological—a better understanding of what people value, how they behave, and how they choose could generate just as much economic value as the invention of a hovering car or some new form of electronics,” he said.  

Hovering cars aren’t here just yet, but if you stop and think about the devices we use everyday, you’ll notice many are the result of a change in our thinking—not in our technology.

Take the way you’re reading this article, for example.

As you scroll through this piece, whether you’re reading on your phone, your laptop, inside the beveled edges of your inbox, or on Every’s website, you’re interacting with a computer through graphical user interfaces (GUI). 

GUI is a way of interacting with computers through intuitive visual elements like buttons, icons, and menus. Before GUI, using a PC meant typing long strings of green alpha-numeric characters on a black screen. GUI—along with the mouse’s functionality to point-and-click on these visual elements—enabled the personal computing revolution. And the computer credited with popularizing this technology is the original model of the Macintosh, which was released in 1984.