
I came across a maxim many years ago in a blog post written by Chris Dixon, a startup guy who is now a partner with Andreessen Horowitz, the Silicon Valley VC outfit. In 2010 Dixon wrote: “The next big thing will start out looking like a toy,” a phrase inspired by Harvard professor Clay Christensen. Dixon’s post made a big impression on me at the time. I had just started writing for GigaOm in San Francisco, covering the intersection of media and technology, and it really fit a lot of what was happening. For example, I (and many others) had initially dismissed Twitter as a toy, a goofy app with no real purpose. My then-boss Om Malik was one of the first to write about it in 2006, and said it seemed annoying and not very useful for much. But somehow this goofy and annoying toy became a central player in things like the Arab Spring (which was quickly followed by the Arab Winter) and turned into a billion-dollar colossus that played a pivotal role in the rise of everyone from Donald Trump to Snoop Dog. Lesson learned!
A more recent example of this phenomenon with a much darker outcome is artificial intelligence, or at least the version we all know now as ChatGPT and other similar products (the GPT stands for “generative pre-trained transformer”). Large-language models. Since it feels like only yesterday that OpenAI released ChatGPT, it’s easy to remember how goofy and useless it seemed at the time. Sure, you could ask it to answer to something you could easily have Googled, and it would respond in an artificially human sort of way. How cute! Then came the image and video versions, where you could make your picture look like The Flintstones, or generate a creepy-looking video of someone with too many fingers, or Will Smith’s face melting while he tried to eat spaghetti. Remember those? So fun. But then slowly it started happening: the toy started to become more useful, and in the process it started to become a lot more frightening (to me anyway).
At the same time AI engines like Claude from Anthropic and Gemini from Google were helping to solve math problems or discovering new pharmaceuticals, these tools – or similar ones – were also being used by the ICE division of Homeland Security to surveil a huge proportion of the population, in what I and others have described as a modern Panopticon. Not that long ago, taking photos from license-plate readers and combining them with facial recognition from visual ID systems, and then combining that with images from Ring doorbells or traffic cameras, and adding data from social media or shopping apps or what have you would have been a Sisyphean task for human beings – technically feasible but hugely time intensive. This provided what some like to call “privacy through obscurity.” But the kinds of searches and indexing and comparisons and matching of databases that I’ve just described is literally child’s play for an AI engine.
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