There's a better way to predict a technology's future: Follow the rate of change

Evaluating a rising technology is often a binary operation, stuck in time. Does it work well? Yes or no? Has adoption lived up to expectations? Are the products and services built on the tech meeting revenue forecasts? Or not?

- Steven Rosenbush

All perfectly reasonable questions. Except that many of today's foundational technologies would at one point or another have gotten a categorical "no."

The transformational impacts of the printing press, electrification and the telephone were hardly obvious in the very early going. In the 1980s, for instance, AT&T decided not to pursue the cellphone business, pegging the technology as largely a local business, the Wall Street Journal later reported. (AT&T eventually reversed course and in 1993 bought a cellphone business.) The Xerox PARC lab famously developed a graphical user interface in the 1970s, but left it to others, like Steve Jobs, to lead its commercialization.

Now the world is deep into a new era, and everyone is trying to call the future of AI, electric vehicles, self-driving cars, robotics, bitcoin, nuclear fusion and quantum computing.

Luckily, it's possible to get better answers about the future of technology. But we need to start with better questions.

In 2019, venture capitalist Vinod Khosla invested $50 million in OpenAI, twice the biggest initial investment he had ever made. It was a year before OpenAI released GPT-3, the generative AI model that provided the foundation for the conversational ChatGPT app in 2022.

And Khosla had begun the investment process in 2018, at a time when he judged that the performance of AI-based products like virtual assistants could be poor, even laughable, relative to humans.

Yet he invested in OpenAI anyway. I wondered how he knew.

"It was the rate of change," Khosla told me when I asked.