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A recent dinner Box CEO Aaron Levie hosted for the tech press went the usual way: Reporters grilled Levie and other execs on whether the AI bubble is about to burst. Then the conversation morphed into one about the downsides of AI, as it threatens to take our jobs, etc.
Levie quipped that the conversation required a kind of doublethink. The same people who were citing studies showing no return on investment for companies implementing AI were now talking about the risk of proving too much ROI.
It was a great point, but also a reminder that many paradoxes apply to AI. The most relevant to this conversation is probably the productivity paradox, made famous by economist Robert Solow, who remarked in 1987 that “you can see the computer age everywhere but in the productivity statistics.”
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In the 1980s, the number of people who could see, up close, the impact computers were about to make was relatively small. The same is true with AI. Aside from impressive consumer chatbots, AI has mostly been a “back-end” technology, helping companies streamline and speed up operations. To make generative AI like LLMs work reliably, companies have to build extensive infrastructure around them.
Eventually, the scaffolding that enables a new technology wave begins to extend out to the broader population, and that’s when the change becomes visceral for most people.
We are in the midst of what could be the biggest technology wave in human history. At the same time, you could view it as just a continuation of the “computer age.”